NIH-funded collaboration to develop steerable robotic needles for lung biopsies

What started as graduate school research with steerable needles in blocks of gelatin could help pulmonologists more accurately reach sites in the peripheral lung to biopsy them.

A collaboration between that doctoral student – now Associate Professor of Mechanical Engineering Robert Webster; Dr. Fabien Maldonado a pulmonologist at Vanderbilt University Medical Center; and a colleague at the University of North Carolina has resulted in a $2 million National Institutes of Health R01 grant.

Robert Webster, associate professor of mechanical engineering, left, and Dr. Fabien Maldonado, a VUMC pulmonologist, and colleagues are developing a steerable robotic needle to more safely biopsy lung nodules that are difficult to reach. (photo by Joe Howell)

The grant will be used to develop a steerable robotic needle to safely biopsy hard-to-reach lung nodules. The work builds on preliminary research funded by a Vanderbilt Institute for Surgery and Engineering seed grant and a separate NIH grant with UNC that concluded a year ago.

Webster began to design a beveled, steerable tip needle in 2004.

“We were just doing things in blocks of gelatin to see if we could get steerable needles to go where we wanted them to go. At the time, we had no idea that the lung was where this technology would be most useful for doctors — we were thinking about applications in the prostate and liver,” Webster said.

Once at Vanderbilt, Webster continued his work on steerable, robotic surgery needles.

However, Webster needed a clinical collaborator to help advance the system from a crude lab prototype to a real-world medical device usable in the operating room.

Enter Fabien Maldonado, M.D., who joined VUMC in July 2015 from the Mayo Clinic. He is an interventional pulmonologist who commonly uses bronchoscopy as a minimally invasive way to diagnose and treat lung diseases. He reached out to Webster on the recommendation of a colleague to see if they could collaborate on a novel approach.

“We started talking about his research that covers a variety of fields, but specifically the field of lung cancer, which is a huge part of my practice and a huge health care issue,” said Maldonado, assistant professor of Medicine.

“It was not until Fabien came to Vanderbilt and I started talking to him that I finally had someone who could give me the clinical insight I needed in order to make this system work the way it needed to work,” Webster added. “That was the missing piece for me. That has led now to really good proposals and lots of different projects we are working on.”

He and Maldonado, working with Ron Alterovitz and Rick Feins at UNC, discovered “the amazing potential of steerable needles in the lung” through an NIH R21 project last year. The team has designed a system that will reach suspicious nodules by deploying a steerable needle from a bronchoscope’s tip.

In the new R01 grant, Ron Alterovitz, Ph.D., associate professor in the Department of Computer Science at the University of North Carolina-Chapel Hill, is the principal investigator, with Maldonado and Webster as co-investigators.

Lung cancer kills more than 150,000 Americans each year and early diagnosis great improves the likelihood of survival. A definitive diagnosis requires biopsy.

Existing approaches make accurate biopsy challenging or impossible for many nodules. The new system will harness the capabilities of a new class of steerable needles to extend the range of bronchoscopes and reliably and safely access nodules throughout the lung, including in the peripheral zone, Maldonado said.

“It will be technically innovative in that it will combine three types of continuum devices that have not previously been unified, will integrate biopsy collection with a bevel tip steerable needle for the first time ever, and will provide a novel physician interface for visualizing and controlling steerable needles in the lung,” Webster said.

He also credited the Vanderbilt Institute for Surgery and Engineering (VISE) with dramatically accelerating this important collaboration.

“We are deeply indebted to VISE for a seed grant that helped us gather preliminary data for NIH proposals, as well as provided a Physician-in-Residence grant that enabled Fabien to spend a day a week in the research lab. This kind of support is just not available at other universities.

“Dedicated research time for physicians like Fabien has been the key to accelerating NIH proposals that otherwise would have taken years to mature …if they ever did at all,” Webster said.

This project is funded by National Institutes of Health Grant R01EB024864.

Media Inquiries:
Kathy Whitney, (615) 322-4747
[email protected]

Posted on Wednesday, November 8, 2017 in needlescopic surgery, NIH, R01, Robert Webster, steerable needles, ViSE, VUMC,Mechanical Engineering, News, News Sidebar, Research

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  • Drones Distribute Swarms of Sterile Mosquitoes to Stop Zika and Other Diseases

    /image/Mjk4NTExMw.jpeg

    Photo: Dan Vostok/Getty Images Bug Off: Of the 3,000 mosquito species in the world, just three spread most human diseases.      

    The deadliest animal on Earth, by far, is the mosquito. Each year, mosquitoes infect about 700 million people with diseases such as malaria, dengue fever, West Nile virus, and Zika. Millions of people die annually from mosquito-borne illnesses, and many of those diseases can’t be cured with drugs. It’s best to avoid being bitten in the first place, but this is becoming more difficult as the insects expand their range, migrating north with warming climates.

    For decades, government agencies and nonprofit organizations have tried to prevent the spread of mosquito-borne diseases in developing countries by spraying large areas with insecticides. But that process is expensive, especially as mosquitoes develop resistance to commonly used chemicals. The United States Agency for International Development (USAID) has begun to look for other mosquito control methods.

    One approach is to breed male mosquitoes in captivity, expose them to radiation that renders them sterile, and release them into the wild. These mosquitoes, being mosquitoes, don’t understand that they can no longer successfully reproduce, and do their best to make it happen anyway. In large enough numbers, the sterile males will outcompete wild males for female mosquitoes, which can reduce local populations by as much as 90 percent.

    This method has been around for half a century, but spreading sterile mosquitoes in the developing world is a challenge. Roads are nonexistent or in poor condition, so it may not be possible to release insects from a car or truck, and using a crewed aircraft is too expensive.

    img/image/Mjk4NTE1Nw.jpeg Photos: WeRobotics Mosquito Control: To spread sterile mosquitoes, WeRobotics will dump them into the white container on top of this drone attachment. They’ll fall into the green box, which has a rotating component to slowly drop them into the chute below.       

    In 2016, USAID funded an organization called WeRobotics, based in Wilmington, Del., to engineer a system that can deploy sterile mosquitoes from autonomous drones instead. USAID and WeRobotics want to see whether drones can replace conventional aircraft as a way to manage mosquito populations over hundreds of square kilometers. “We hope to greatly increase the area that we can cover by using drones,” says WeRobotics’ cofounder Adam Klaptocz.

    Klaptocz and his colleagues started WeRobotics to explore ways that drones can have a positive social impact. Over the past few years, they’ve set up community robotics labs in developing nations around the world. WeRobotics and its partners have used drones to map roads in Nepal, deliver medicine in Peru, and coordinate humanitarian efforts in the Caribbean after Hurricane Maria.

    The company’s latest project is testing a prototype drone-based mosquito control system in South America. The challenge here is not the drone itself—it’s how you carry and release mosquitoes from that drone. “Mosquitoes are very fragile animals,” Klaptocz explains. “If you put hundreds of thousands of them into a very small box, they’re going to damage themselves, and damaged mosquitoes will not be able to compete with wild mosquitoes.”

    The goal is to pack as many mosquitoes as possible into the drone. However, clumping is a problem because the insects form “a big collection of legs and wings,” he says. The trick, according to Klaptocz, is to keep them inside a precooled container: “Between 4 °C and 8 °C, they’ll fall asleep, and you can pack them up fairly densely.”

    It’s also important to control the release of the mosquitoes, rather than dumping them out all at once. “We tried different systems to get the mosquitoes out of the holding canister, including vibrations and a treadmill,” he says. “Right now, we’re using a rotating element with holes through which individual mosquitoes can fall.” Once the mosquitoes fall out of the canister, they spend a few seconds in a secondary chamber warming up to the outside air temperature before exiting the drone, to make sure they’re awake and ready to fly.

    It’s not yet clear that drones will be much more effective than humans with backpacks at dispersing mosquitoes, says Robert Malkin, an expert on new health-care technologies at Duke University. And sustaining any kind of operation in remote areas with little infrastructure will be a challenge. “But it could work,” he says. “It sounds like a cool project.”

    WeRobotics will conduct its first experiments for USAID with sterilized male mosquitoes in late 2017 or early 2018, somewhere in South or Central America. “Our next step is running controlled tests, where we mark the insects, release them, and recapture them in traps to measure whether they’re healthy or not,” says Klaptocz.

    WeRobotics’ deployment system works with different kinds of mosquitoes and any model of drone. For future projects, it could carry and release male mosquitoes that have been genetically modified to have sterile offspring; male mosquitoes that have been infected with a bacteria called Wolbachia pipientis, which makes their offspring sterile; or female Wolbachia-infected mosquitoes, which are less likely to transmit diseases when they bite.

    But before they begin any live mosquito testing, WeRobotics must work with local communities to win their support. “We’re trying to control disease vectors,” Klaptocz explains. “But practically, what we’re doing is releasing a whole bunch of mosquitoes into communities and flying drones over them. Engagement with these communities has to be done from the beginning, by talking to people and involving them in the process.”

    A version of this article appears in the December 2017 print magazine as “Drones Make a Special Delivery—Mosquitoes.”

    Correspondence: Revisiting the theoretical cell membrane thermal capacitance response

    Shapiro et al.1 have shown that the thermal transients generated when short wave infrared light is absorbed in neural tissue are accompanied by an increase of the cell membrane’s electrical capacitance. This capacitance change elicits capacitive membrane currents which are unrelated to any specific ion channels and which can explain infrared neural stimulation (INS) and a variety of other thermal neurotechnologies. Their findings on the thermal capacitance increase have since been supported by experiments from several additional groups2,3,4,5, thus becoming an important contribution to our understanding of thermal neurostimulation. In addition to their primarily experimental study, Shapiro et al.1 also suggested a theoretical explanation of the increase in capacitance with temperature, in which the membrane capacitance was modeled according to the principles of Gouy–Chapman–Stern theory1, 6. In this theoretical approach, the membrane capacitance is determined by calculating the overall capacitance of the phospholipid core region in series with the capacitances of the intracellular and extracellular extra-membranal boundary regions; ionic concentrations are obtained when diffusion and electrical forces on the different ions reach equilibrium (following a Poisson–Boltzmann distribution, Fig. 1a).

    Fig. 1

    Fig. 1

    Predicted membrane electrical capacitance after temperature increase. a Theoretical Gouy–Chapman–Stern (GCS) model which includes phospholipid (hydrophobic) core and extra-membranal boundary sub-regions. The model is shown under conventional charge notation9 and the non-standard notation of Genet et al.1, 6, where the charge derivative has opposite direction to the current convention9. b Membrane-equivalent electrical circuit reproduced from Shapiro et al.1; the membrane current is marked according to the convention1, 9. c Illustration of potential distribution at the extra-membranal boundary regions. Temperature elevation leads to higher potential gradients, which according to the classical capacitor formula corresponds to a reduction in capacitance of the extra-membranal regions. d Discrepancy between capacitance measurement (reproduced from Shapiro et al.1) and sign-corrected model simulations (PE:PC bilayers1, laser parameters: duration −10 ms, energy −7.3 mJ)

    Full size image

    As implemented by Shapiro et al.1, this model demonstrated agreement with experimentally measured currents. However, this seemingly complete theoretical explanation, and several subsequent analyses by other groups7, 8 who closely followed it, are incorrect due to a modeling error. Intuitive energetic considerations regarding the ionic double layer capacitance on each side of the membrane predict that in order to maintain equilibrium, the additional thermal energy input will be offset by correspondingly higher electrical energy and absolute potentials (Fig. 1c). This stronger potential difference corresponds to a capacitance decrease, which is opposite to the experimental measurements. We have traced the modeling error back to a reliance on Genet et al.6 non-standard notation for membrane mobile charge (see also Fig. 1a): “Let Q denote the total capacitive charge in the extracellular space (the total charge within the cytoplasm will be –Q; Q > 0 for a resting cell)”6. Under this notation (also used by several related theoretical studies7, 8), the derivative of the mobile membrane charge is , where Im is a membrane current conventionally defined positive for a current flowing from the intracellular to the extracellular domain9, charging the intracellular side of the membrane capacitor. Our reanalysis using a sign-corrected model predicts a decrease, rather than an increase in membrane capacitance with temperature (Fig. 1d).

    Given this discrepancy, a revised explanation for the membrane capacitance’s thermal increase observed in Shapiro et al.’s key experiments1 is therefore needed. By examining the biophysics literature on thermal membrane effects10,11,12, we identified membrane structural dimensional changes as a plausible, predictive mechanism for this phenomenon. This topic and its theoretical and predictive (validation) consequences are explored in Plaskin et al.13.

    Low-intensity pulsed ultrasound improves behavioral and histological outcomes after experimental traumatic brain injury


    Animals and Surgical Procedures

    All animal experiments were performed according to the guidelines of and were approved by the Animal Care and Use Committee of National Yang-Ming University. The animals were blindly randomized to different treatment groups by using computer-generated random numbers. All outcome measurements described below were also performed in a blinded manner. The TBI model was induced by controlled cortical impact (CCI) injury in mice. Male C57BL/6 J mice (8 weeks old, about 22–25 g in weight) were intraperitoneally anesthetized with sodium pentobarbital (65 mg/kg; Rhone Merieux, Harlow, UK) and placed in a stereotaxic frame. A 5 mm craniotomy was performed over the right parietal cortex, centered on the coronal suture and 0.1 mm lateral to the sagittal suture, and injury to the dura was avoided. A CCI device (eCCI Model 6.3; Custom Design, Richmond, VA, USA) was used to perform unilateral brain injury by a pneumatic piston device with a rounded metal tip (2.5 mm in diameter) that was angled at 22.5° to the vertical so that the tip was perpendicular with the brain surface at the center of the craniotomy. A velocity of 4 m/s and a deformation depth of 2 mm below the dura were applied. The bone flap was immediately replaced and sealed, and the scalp was sutured closed. Mice were placed in a heated cage to maintain body temperature while recovering from anesthesia. Sham-operated mice received craniotomy as described before, but without CCI; the impact tip was placed lightly on the dura before sealing the wound. After the trauma or sham surgery, animals were housed under the conditions mentioned above.

    Pulsed Ultrasound Apparatus

    The pulsed ultrasound setup was similar to that used in our previous study (Fig. 1a)19. LIPUS exposures were generated by a 1.0-MHz, single-element focused transducer (A392S, Panametrics, Waltham, MA, USA) with a diameter of 38 mm and a radius of curvature of 63.5 mm. The half-maximum of the pressure amplitude of the focal zone had a diameter and length of 3 mm and 26 mm, respectively. The transducer was applied with a duty cycle of 5% and a repetition frequency of 1 Hz. The transducer was mounted on a removable cone filled with deionized and degassed water whose tip was capped by a polyurethane membrane, and the center of the focal zone was about 2.0 mm away from the cone tip. The mice were anesthetized with isoflurane mixed with oxygen during the sonication procedure. The sonication was precisely targeted using a stereotaxic apparatus (Stoelting, Wood Dale, IL, USA). The acoustic wave was delivered to the targeted region in the injured cortical areas. A function generator (33220A, Agilent Inc., Palo Alto, USA) was connected to a power amplifier (500–009, Advanced Surgical Systems, Tucson, AZ) to create the US excitation signal. A power meter/sensor module (Bird 4421, Ohio, USA) was used to measure the input electrical power. LIPUS was applied for a sonication time of 5 min at an acoustic power of 0.51 W (corresponding to a spatial-peak temporal-average intensity (ISPTA) of 528 mW/cm2) 5 mins after TBI and subsequently daily for a period of 3 or 27 days (Fig. 1b,c). Mice were sacrificed for analysis at 1, 4, or 28 days. The intensity of the LIPUS exposures was selected based on data from our previous studies17,20 and a pilot study in which a sonication time of 5 min or 15 min at an acoustic power of 0.11 W or 0.51 W was tested; a sonication time of 5 min at an acoustic power of 0.51 W attenuated brain water content and there was no significant difference between the other two LIPUS-treated TBI groups and the non-treated TBI group (Table 1).

    Figure 1

    Figure 1

    Experimental design. (a) Schematic diagram of low-intensity pulsed ultrasound setup. (b) LIPUS was performed daily from day 0 to day 3 (red point) in normal brain. (c) LIPUS was performed daily from day 0 to day 27 or day 3 (red point) in a TBI mouse.

    Full size image
    Table 1: Effects of different LIPUS treatment protocols on brain water content in TBI mice at 1 day.

    Full size table

    Neurological Function Evaluation

    Behavioral assessments (neurological severity scores (mNSS), rotarod, and beam walk) were performed before and at days 1, 4, 7, 14, 21, and 28 after CCI21. The mNSS includes a composite of motor, sensory, reflex, and balance tests. The mNSS rates neurological functioning on a scale of 0–18 from normal to maximal deficit (Table 2). In addition, mice were pretrained for 3 days for both the rotarod and beam walk tests. Moreover, three trials were recorded 1 h before CCI to determine baseline values. The rotarod task measures balance and motor activity. The speed of rotation was gradually accelerated from 6 to 42 rpm within 7 min. Each mouse was placed on a 3 cm rotating rod, and the latency to fall was recorded for all trials. The beam walk is used to evaluate fine motor coordination and function by measuring the ability of an animal to traverse an elevated beam22. The time for the mouse to traverse the beam (not to exceed 60 s) and the hindlimb performance as it crossed the beam (based on a 1 to 7 rating scale) were recorded. A score of 7 was given when animals traversed the beam with two or less footslips; 6 was given when animals traversed the beam with less than 50% footslips; 5 was given for more than 50% but less than 100% footslips; 4 was given for 100% footslips; 3 was given for traversal with the affected limb extended and not reaching the surface of the beam; 2 was given when animals were able to balance on the beam but not traverse it; 1 was given when animals could not balance on the beam21.

    Brain Water Content Determination

    Mice were sacrificed at day 1 and day 4, two time points associated with the maximum appearance of edema after TBI23,24,25. Brain water content was measured in a 4 mm coronal tissue section of the ipsilateral hemisphere 2 mm from the frontal pole. Brain samples were weighed on an electric analytical balance to obtain the wet weight and then dried at 100 °C for 24 h to obtain the dry weight. Brain edema was evaluated by measuring brain water content using the formula of (wet weight-dry weight)/wet weight × 100%.

    Assessment of Blood-Brain Barrier Permeability

    BBB permeability was measured by Evans blue (EB) extravasation at day 1 or day 4 after TBI22,23. EB (Sigma, St. Louis, MO) with a concentration of 100 mg/kg was injected via the tail vein and allowed to circulate for 1 h. The animals were then perfused with saline via the left ventricle until colorless perfusion fluid appeared from the right atrium. After perfusion and brain removal, the ipsilateral hemispheres were cut into 4-mm-thick sections (2 mm from the frontal pole) before measuring the amount of EB extravasated. The uninjured right hemispheres of sham-operated mice acted as the control. Samples were weighed and then soaked in 50% trichloroacetic acid solution. After homogenization and centrifugation, the extracted dye was diluted with ethanol (1:3), and the amount present measured using a spectrophotometer (Infinite M200, Tecan, Mechelen, Belgium) at 620 nm.

    Histological Evaluation

    One, 4, and 28 days following TBI, mice were sacrificed by transcardial perfusion with phosphate-buffered saline (PBS), and then the tissues were fixed with 4% paraformaldehyde. Brains were collected and post-fixed in 4% paraformaldehyde overnight and transferred to PBS containing 30% sucrose for cryoprotection. Coronal sections were cut in a cryostat at 10 μm from the level of the olfactory bulbs to the visual cortex and used for cresyl violet histology, FJB staining, or immunohistochemistry.

    Cresyl violet staining

    The contusion area was quantified using coronal sections stained with cresyl violet at 20 rostral-caudal levels that were spaced 200 μm apart. Sections were digitized and analyzed using a 1.5× objective and Image J software (Image J, National Institutes of Health, Bethesda, MD, USA). The contusion area was calculated using all cresyl violet-stained sections containing contused brain, and the contusion volume was computed by summation of the areas multiplied by the interslice distance (200 μm). The preservation of cerebral tissue was evaluated by the ratio of the volume of the ipsilateral remaining cerebral hemisphere to the volume of the corresponding contralateral cerebral hemisphere.

    Fluoro-jade B staining

    FJB staining was used to label degeneration neurons of the brain. Sections were rehydrated in graded ethanol (50%, 75%, and 100%; 5 min each) and distilled water. Sections were then incubated in a solution of 0.06% potassium permanganate for 15 min, rinsed in distilled water for 2 min, and incubated in a 0.001% solution of FJB (Chemicon, Temecula, CA, USA) for 30 min. FJB staining was quantified on stained sections at the level of 0.74 mm from the bregma. Three sections per animal were viewed and photographed under a microscope. FJB-positive cells were counted by sampling an area of 920 × 860 μm2 (FJB staining) immediately adjacent to the cortical contusion margin in 3 randomly selected, non-overlapping fields using a magnification of 20x. The total number of FJB-positive cells was expressed as the mean number per field of view.

    Immunohistochemistry staining

    After quenching of endogenous peroxidase activity and blocking of nonspecific binding with 10% normal goat serum, sections were allowed to react with the primary antibodies (rabbit anti-myeloperoxidase [MPO; a neutrophil marker; 1:1000; Dako 019-19741, Carpinteria, CA, USA] or rabbit anti-Iba1 [a microglia/macrophage marker; 1:1000; Wako 019-19741, Osaka, Japan]) at 4 °C overnight. Further colorimetric detection was processed according to the instructions of a Vectastain Elite ABC Kit (Vector Laboratories, Burlingame, CA, USA) with the use of diaminobenzidine as a peroxidase substrate. The specificity of the staining reaction was assessed in several control procedures, including omission of the primary antibody and substitution of the primary antibody with non-immune rabbit serum. Brain sections from day 1 or day 4 after CCI were used as positive controls for cresyl violet, FJB, MPO and Iba1 staining methods22,23.

    Magnetic resonance imaging

    Magnetic resonance imaging (MRI) was performed using a 3 TMRI system (TRIO 3T MRI, Siemens MAGNETOM, Germany). Brain edema was assessed by T2-weighted images obtained on day 1 and day 4 post-injury. The parameters for the T2-weighted imaging were as follows: repetition time/echo time = 3500/75 ms, matrix = 125 × 256, field of view = 25 × 43 mm, and section thickness = 1.0 mm. The imaging plane was located across the center of the lesion site. After normalizing image intensities between pre- and post-TBI, areas of hyperintensity represent edema regions. The regions of interest (ROI) were manually outlined by a blinded operator with the ROI tool of the MRI system software (NUMARIS/4, Version syngo MR B17, Siemens MAGNETOM). Edema volumes were assessed from T2-weighted images by summing up the edema area measured from six slices and multiplying by the slice thickness (1.0 mm).

    Western blotting analysis

    One and 4 days after TBI, a 4-mm coronal section was taken from the injured area over the parietal cortex and then homogenized by T-Per extraction reagent supplemented with the Halt Protease Inhibitor Cocktail (Pierce Biotechnology, Inc.). Samples containing 30 μg protein were resolved on 12% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to Immun-Blot® polyvinyldifluoride (PVDF) membranes (Bio-Rad, CA, USA). After blotting, the membranes were blocked for at least 1 h in blocking buffer (Hycell, Taipei, Taiwan), and then the blots were incubated overnight at 4 °C in a solution with antibodies against zonula occludens-1 (ZO-1, 1:200, 61–7300) and claudin-5 (1:1000, 34–1600) procured from Invitrogen (Camarillo, CA, USA). After being washed with PBST buffer, the membrane was incubated with the secondary antibodies for 1 h at room temperature. After being washed with PBST buffer, signals were developed using a Western Lightning ECL reagent Pro (Bio-Rad, California, USA). The gel image was captured using an ImageQuant™ LAS 4000 biomolecular imager (GE Healthcare Life Sciences, Pennsylvania, USA) and analyzed using a gel image system (ImageJ) to estimate the integral optical density of the protein bands.

    Statistics

    All data are shown as means ± standard error of the mean (SEM). The Shapiro-Wilk test was first performed to assess the normality of the data. Differences between two groups were performed using Student’s t test. A two-way analysis of variance (ANOVA) followed by Tukey’s test was performed to determine the individual and interactive effects of LIPUS on behavioral tasks and the expressions of ZO-1 and claudin-5. The level of statistical significance was set at p value ≤ 0.05.

    Knowledge on demand shapes technology’s future in education –Schmidt Lecture Nov. 15

    As education technologies continue to converge, the 2018 forecast is for an exponential pace of technological change.

    David Wilson

    Students today effortlessly connect to the tools, methodologies and strong communities that can and will nurture their innate curiosity, said David E. Wilson, a popular speaker who leads a global team at National Instruments responsible for defining and promoting the software technologies of NI’s platform in education and industry.

    Wilson will deliver the School of Engineering’s Schmidt Family Annual Educational Technologies Lecture on Wednesday, Nov. 15, at 4:10 p.m. in Featheringill Hall’s Jacob Believed in Me Auditorium. A reception will follow in Adams Atrium at 5 p.m.

    Wilson’s lecture – Knowledge on Demand – is open to the university community.

    “We have witnessed active learning evolve from sequential instructor-oriented methods to an on-demand, knowledge-when-you-need-it paradigm in a relatively short period of time, thanks to the Internet and the democratization of education,” Wilson said.

    Wilson believes there is still a fundamental case to be made for learning in a sequential order – building up a foundation of knowledge critical to any education.

    “But, educators today are teaching a generation that does not precede each lesson with ‘when will I ever use this?’ Instead, they are asking, ‘How can I begin to solve my problem now?’”

    Wilson will talk about the possibilities of this new paradigm. “What is the impact of this concept as it relates to science and engineering disciplines, and how do we integrate it into the learning process?”

    The focus of the Schmidt Family Annual Educational Technologies Lectureship is to explore advances in digital learning and their applicability to innovation and practice in the Vanderbilt University School of Engineering.” Douglas C. Schmidt, associate chair for computer science and professor of electrical engineering and computer science, and his parents, retired Navy Capt. Raymond P. Schmidt and Roberta R. Schmidt, created the lectureship.

    Contact: Brenda Ellis, (615) 343-6314
    [email protected]

    Posted on Wednesday, November 8, 2017 in Douglas C. Schmidt, education technology, knowledge on demand, Schmidt Family Annual Educational Technologies Lecture,Alumni, Electrical Engineering and Computer Science, Home Features, News, News Sidebar

    Haemodynamic Recovery Properties of the Torsioned Testicular Artery Lumen

    In large arteries, experimental and theoretical studies have shown that twist buckling starts when lumen pressure exceeds the critical pressure at a given length16. Other possible biomechanical factors in the aetiology of arterial buckling are high blood pressure (hypertension), reduced wall elasticity due to lamina/elastic fibre degradation, decreased critical pressure and axial stretch/tension17,18,19. However, detailed haemodynamic characteristics of buckled millimetre-sized arteries, such as TAs, have not been studied in the literature.

    Modulation of intramural pressure and flow can be employed to remove the torsional buckling acutely. Our results documented the flow rate necessary to open the buckled TA increased as the twist angle increased. We have also presented the quantitative association between the opening pressures of the twisted arteries and the twist angles (Fig. 4). As the twist angle increased, the opening pressure of the artery lumen had an increasing trend for all test specimens. That might be because higher torque is generated on the artery at high twist rates, as shown in the study by Garcia et al.20. In their study, they torsioned porcine common carotid arteries at four different axial stretch ratios (SR), and reported increased buckling torques for increased SR. We estimated that this ratio was very low in our case, and therefore assumed a constant value (see Limitation section for further detail). It should be emphasized that, in an intact testicle, the tissue mass around the buckled arterial segment would require an additional flow volume/pressure which will exceed the predictions of the present in vitro study. While this contribution is believed to be low due to small distal mass, detailed mechanical tests are needed for its exact value.

    Removal of buckling in the TA can also be achieved through an increase in the arterial diameter. The study by Cakmak et al. showed the ID of the human TA increased from 1.65 mm to 2.03 mm in 5 minutes under 10 Hz frequency external electro-stimulation15. The same study reported the volumetric flow rate augmentation for the corresponding diameter changes as 8 ml/min and 17 ml/min, respectively. In our study, Fig. 5A shows that a flow rate of 17 ml/min is indeed sufficient to open 90°, 180° and 270° buckling of the TAs with an approximately equivalent diameter of 2 mm. Although the two studies were performed on different model systems, and the diameter values were measured differently, the flow rate and pressure scales of humans and rams were found to be very close to each other. However, due to significant differences in the length of the test sample (Lsample) versus the actual human artery length (Lhuman), the corresponding torsional angles (θ) should be adjusted through a linear relation for small angles; θhuman = θsample.Lhuman/Lsample. When we extrapolated human data15 to our volumetric flow data, diameter and the degree of torsion (Fig. 5A), we could conclude that the increase in volume flow may increase pressure, and thus may open the ~180° buckled arteries in humans. We can also suggest that the same technique could be effective for torsions up to 360°, but not for torsions any higher than that. Unfortunately, in the current clinical setting, urologists have no diagnostic preoperative imaging techniques to determine what degree of torsion a testicle has, and it is anecdotally believed that torsional levels reaching 720° is not uncommon. For this reason, when used in clinics, the proposed mechanism to open a buckled artery should involve a trial-and-error protocol of gradually increasing blood flow. Hence, more studies need to be conducted to validate the consistency of the stimulation technique and related volume flow and diameter changes.

    To obtain the relationship between flow rate and pressure drop, the pressure drop measurements were processed with our theoretical model, which calculates head losses in the dynamic setup (see Supplementary Information for details). This model extracted the pressure drop values in the TA for corresponding flow rates and vessel diameters. Pressure drops increased in response to increased flow rates, as expected from the Poiseuille flow calculations. Our pressure drop results were consistent with the human TA findings in the literature. We calculated a pressure drop of 0.21 mmHg in 1 cm of artery under 18.84 ml/min flow rate (Fig. 2), while Waites and Moule found the corresponding pressure drop as 0.208 mmHg21.

    Khalafvand and Han have shown on the porcine carotid artery that the critical buckling pressure does not change with the flow rate under steady state conditions22. In addition, the pulsatile flow decreased this critical buckling value by 17–23%. In line with their findings, our experiments demonstrated that pressure was the more influential haemodynamic parameter. The influence of wall shear stress created by blood flow on the arterial geometry was found to be minor. Another result from the same study was that a pressure change of 50 mmHg caused the middle of the carotid artery to deflect 30 mm, whereas we observed approximately 0.8 mm of deflection in our test samples for the same pressure change. Considering that our TA specimen was 5 times shorter than their carotid artery, we may conclude that increasing the specimen length would also increase the degree of deflection. Our results confirmed a substantial increase in TA deflection following the initiation of C-shaped buckling within the pressure range of 10 and 50 mmHg.

    The luminal pressure increase should be controlled for the vessels that are likely to undergo C-shaped buckling after opening the torsional buckling. In particular, arteries with smaller twist angles have lesser critical C-shaped buckling pressures due to the lesser torque load on the artery. In our study, C-shaped buckling was observed in all vessels of various diameters with different initial twist angles after a critical flow rate of >20 mL/min was reached. This level of flow rate should be avoided to eliminate C-shaped buckling after detorsion of the twisted vessel. The resistance in peripheral capillaries could also be decreased to prevent this buckling mode. However, such substantial decrease in capillary resistance would also decrease the total pressure in the vessel lumen, and may propagate torsional buckling due to low pressure levels. Our results for critical buckling angle in relation with the vessel lumen pressure data could help determine the optimal pressure levels as a preliminary guide for further studies on the therapeutic methodologies targeting the recovery of twisted arteries.

    Limitation and Conclusion

    The arteries, in vivo, operate under a finite SR that decreases by aging and as a result of vascular diseases. This ratio has a substantial effect on the critical buckling pressure and surface deflection. For instance, an increase in SR from 1.3 to 1.5 results in a difference in critical buckling pressure of up to 10–15 mmHg22. Since we avoided stretching the vessels in the axial direction, we employed very low SRs as 1.1 and 1.3 in our experiments. An increase in vessel diameter due to a low axial SR under lumen pressure would reduce the twist angle needed to reach the shear strain for buckling to occur. Our experiments were performed for outer diameters varying between 0.175 cm and 0.24 cm. That is a relatively narrow range for human TA. For comparative purposes, a TA with larger diameter could be tested in future studies.

    In dynamic experiments, a theoretical model was used to extract the pressure drop in the isolated TA segment. For each hydrodynamic component of the set-up, the corresponding head loss formulas are highly sensitive to small vessel diameters and taper angle variations between the connections. Since our vessels were not fully cylindrical, and the connections were not arranged in a perfectly symmetric way, it was not possible to measure each connection parameter accurately. Furthermore, the pressure loss was calculated under the assumption of Poiseuille model, although the flow in the dynamic set-up was not fully developed due to the short inlet region and curved (deformed) pipe and artery geometry. Despite this assumption, our results are within the physiological range, and are thus significant for clinical estimates.

    The current study elucidates the pressure-flow interactions and the corresponding dynamic surface deformation patterns of the torsioned TAs under different twist angles in a controlled organ culture system. The proposed haemodynamic approach offers a non-invasive alternative to the standard scrotal exploration and orchidopexy treatments but its clinical adoption requires parallel developments in imaging and optimization of clinical protocol alternatives. These findings, based on live TA, suggest a novel therapeutic approach in which the augmentation of volume flow can increase lumen pressure, resulting in opening and rescue of the twisted arteries in a twist angle dependent manner.

    Findings probe cell cooperation, ‘en mass’ migration

    New research findings are revealing secrets about how living cells “cooperate” with each other, joining into groups that migrate collectively and alter tissue.

    This image shows the group migration of cells, with red indicating the cell nuclei and the green representing the cell’s “cytoskeleton.” (Purdue University photo/Bumsoo Han)

    The research focused on cells called fibroblasts, which are found in connective tissue and produce the “extracellular matrix,” a scaffold-like material between cells in living tissue.

    “Fibroblast migration plays a key role during various physiological and pathological processes such as wound healing and cancer metastasis,” said Bumsoo Han, a Purdue University professor of mechanical and biomedical engineering. “Although migration of individual fibroblasts has been well studied, migration in-vivo often involves simultaneous locomotion of groups of fibroblasts, so-called ‘en masse migration.”

    New findings were published in October in the Journal of the Royal Society Interface.

     “Specifically, we hypothesized that a group of migrating cells can significantly deform the matrix, whose mechanical microenvironment dramatically changes compared with the un-deformed state,” he said. “Because the cells cooperate, they can exert greater force in deforming the matrix compared to single cells alone. The alteration of the matrix microenvironment reciprocally affects cell migration.”

    The hypothesis was tested by measuring the extracellular matrix deformation during en masse migration on collagen “hydrogels.” Findings showed the grouped cells act collectively to deform the matrix before and during the migration.

    “We found that cells on soft collagen hydrogels migrate along tortuous paths, but, as the matrix stiffness increases, cell migration patterns become aligned with each other and show coordinated migration paths,” he said.

    The research is related to work led by Andrew Mugler, a Purdue assistant professor of physics and astronomy, who co-authored a recent paper in the journal Physical Review Letters. The two researchers have collaborated for about two years.

    “The common theme of both papers is how these cells cooperate,” Han said.

    Findings will aid efforts to learn more about the en masse cell migration and its relationship to processes including cancer metastasis.

    The Interface paper’s lead author is Purdue graduate student Altug Ozcelikkale. That paper probes how the cells “cooperate mechanically,” while the PRL paper focuses on how they cooperate chemically, Han said.

    The research is ongoing, with future work investigating the multiple chemical and environmental cues involved in the collective cell behavior. 

    Source: Purdue Newsroom

    An algorithm for the beat-to-beat assessment of cardiac mechanics during sleep on Earth and in microgravity from the seismocardiogram

    The algorithm may be subdivided into three phases:

    1. 1.

      Data segmentation and artifact removal

    2. 2.

      SCG fiducial point extraction

    3. 3.

      Congruency check & CTI Estimation

    Obviously, we may obtain correct CTI values only from a good performance of the algorithm in detecting the AO, AC, MO and MC fiducial points. Given the large number of available heart beats, the algorithm was designed to maximize its precision, i.e. its ability to correctly identify true FPs, even at the cost of false negatives.

    The algorithm makes use of both ECG and SCG signals. As schematized in Fig. 4, for each recording ECG and SCG were pre-processed before feeding the algorithm. In particular, the ECG trace was manually edited from artifacts by a proprietary software previously developed (the average ECG artifact rate was <0.5%), while the SCG signal was filtered by a forward-reverse application of a band pass Butterworth filter (5–40 Hz) to remove baseline drifts and noise.

    Figure 4

    Figure 4

    Scheme of the whole signal processing and of the algorithm phases.

    Full size image

    In the following description, the subscript “ Rdelay ” indicates the time delay of a given FP or event with respect to the ECG R peak, e.g. AO Rdelay means the time delay of AO from the corresponding R peak. All abbreviations used in the algorithm description are summarized in Table 2.

    Table 2: List of abbreviations used in the algorithm description. The superscript i indicates the current beat, i+1 the first next beat and i+2 the second next beat.

    Full size table

    Phase 1–Data segmentation and artifact removal

    Goal of this phase was to split each recording into individual heart beats and identify and remove both gross artifacts caused by marked body movements and smaller artifacts due to smooth bumps, small movements, shifts between clothes layers, etc.

    In detail

    1. 1.

      In each valid ECG complex the position of the R peak was identified and stored.

    2. 2.

      On the basis of the R peak timing, the ECG and the SCG were then split into individual heart beats. We considered as a heart beat a signal segment starting from −200 ms from the relevant R peak till −200 ms from the following R peak (see Fig. 3). The −200 ms offset was adopted to include in the beat also the corresponding ECG P wave, although this information was not considered in the present study.

    3. 3.

      Gross artifacts were identified by checking the SCG amplitude and variance within each heart beat. Beats with the maximal peak to peak amplitude greater than 50 mg or a variance greater than 28 mg2 were excluded from the subsequent analyses. Those threshold values were empirically derived from the analysis of a sample of beats randomly extracted from all recordings.

    4. 4.

      Smaller artifacts were identified in the remaining beats by computing the envelope of the SCG. The envelope was obtained by calculating the absolute value of the SCG signal and then filtering the output by a 31-sample FIR filter with a triangular window. As shown in Fig. 5(a) the typical envelope curve is characterized by two main peaks, S1 and S2, corresponding to the first and second heart sound.

      Figure 5

      Figure 5

      Scheme of FP identification. Panel a: ECG with the indication of the Te point, SCG with its envelope curve and indication of the S1 and S2 areas, MC, AO, AC and MO fiducial points, ICP and IRP anchor points and definition of the IRPRdelay used for the AC and MO identification. Inset b: definition of the threshold points used for the estimation of MC and AO in the S1si window. Inset c: definition of the D1 and D2 distances used for the scoring of the peaks in the S2si window for the identification of the IRP anchor point used for the localization of AC and MO.

      Full size image

    We considered as normal the beats in which the envelope amplitude of S1 was higher than that of S2 AND + 10 ms ≤S1Rdelay ≤ +160 ms AND +300 ms ≤ S2Rdelay ≤ +480 ms.

    Beats not satisfying all the above three criteria were considered as artifacts and discarded from the subsequent analyses.

    Phase 2- SCG Feature extraction

    Goal of this phase was to identify in each beat the FPs associated with the opening and closure of the aortic and mitral valves. The search for each FP was done in two steps. In the first step we localized the interval where the FP should have been searched for. This was done by identifying two anchor points in the SCG waveform, the Isovolumic Contraction Point, ICP, to estimate MC and AO, and the Isovolumic Relaxation Point, IRP, to estimate AC and MO (see Fig. 5). In the second step, the FP was finally localized by a pattern analysis starting from the relevant anchor point. This policy was adopted since we observed that the selected anchor points are the clearer displacements within the SCG waveform. As their names suggest, they correspond to the SCG vibrations produced during the isovolumic contraction and the isovolumic relaxation phases of the heart cycle, respectively. Concerning the ICP and IRP localization it should be pointed out that while the relative position of ICP with respect to the R peak is mostly independent from the heart rate, this is not the case for the IRP position which, on the contrary, is largely influenced by changes in the beat length. This aspect was taken into account in the design of the algorithm.

    MC And AO Identification

    In the SCG signal under the S1 envelope peak we localized a search interval, S1si, starting and ending 25 and 75 ms after the R peak respectively. The ICP was the deepest minimum within S1si that satisfies the following condition: |ICP Rdelay  − ICP Rdelayref |≤ +30 ms, being ICP Rdelayref the ICP Rdelay observed in the last valid beat before the current beat and taken as a “reference”. That is, the ICP was accepted if it occurred within a given delay from the R peak and if this delay was sufficiently close to that observed in the previous reference beat.

    In the beats were the ICP was identified, the AO fiducial point was assumed to be the first peak following the ICP within 50 ms and with a distance (in amplitude) from ICP greater or equal to 0.7*|ICP d |, being ICP d the ICP peak amplitude (see Fig. 5(b)). This threshold was set in order to exclude spurious peaks occasionally occurring in proximity of the anchor point. The MC fiducial point was assumed to be the first peak preceding the ICP within 50 ms and satisfying the same amplitude rule of AO.

    AC And MO Identification

    For the localization of the IRP anchor point and then of the AC and MO FPs, we identified, under the S2 envelope peak, a SCG search interval S2si defined as the 60 ms SCG segment centered on the end of the ECG T wave (Te). Te was determined through the procedure proposed in18. This strategy simplified the search for IRP even in presence of important changes in the cardiac rhythm. Indeed, while TeRdelay may change as a function of the cardiac interval, in healthy subjects IRP remains quite close to Te.

    IRP was the highest peak in S2si which met two criteria. The first criterium verifies that the IRP peak be sufficiently pronounced, the second criterium verifies that IRPRdelay be congruent with the IRPRdelay in the adjacent beats.

    In detail:

    First criterium

    Being D the sum of the two distances, D1 and D2 between the IRP peak and the adjacent left and right minima (see Fig. 5(c)), we verified that D ≥ 7 mg.

    Second criterium

    In case at least one of the 20 beats preceding the current beat contained a valid IRP, the IRPRdelay of the valid beat closest to the current beat was taken as reference, IRP Rdelayref, and we verified that

    | IRP R d e l a y − IRP R d e l a y r e f | ≤20ms

    In case no reference beat was available among the previous 20, e.g. because of a sequence of artifacts, we checked the congruency of the current beat vs. the subsequent two beats, provide the IRP could be estimated in those beats and their RR intervals was “relatively” stable, i.e.

    | RRI i − RRI i + 1 | ≤100msAND | IRP R d e l a y i − IRP R d e l a y i + 1 | ≤20msAND | RRI i + 1 − RRI i + 2 | ≤100msAND | IRP R d e l a y i + 1 − IRP R d e l a y i + 2 | ≤20ms

    If the IRP anchor point was identified, because both the above two criteria were met, AC was the first peak preceding IRP if

    10ms≤ | IRP Rdelay − AC Rdelay | ≤40ms

    and MO was the next trough following IRP if

    10ms≤ | MO Rdelay − IRP Rdelay | ≤30ms

    Sometimes a variant to the FP identifications described above was applied. As shown in Fig. 6, AO, AC and MC do not always appear as clear peaks and MO as a clear valley. In about 6% of the analyzed beats, we observed an inflection point in the area where the target peak or valley was expected (on the basis of the FP position detected in the previous beats) and in those cases the inflection point was taken as marker of the FP. In the past we already observed this phenomenon in different subjects during experimental laboratory recordings. One example of the correspondence between MC inflection point and the real closure of the mitral valve is shown in Fig. 7. Data refers to a simultaneous SCG and M-mode ultrasound measure in a healthy volunteer. Although the origin of this phenomenon is still unexplored, we speculate that it might depend on a transient slight physiological de-synchronization between left and right heart mechanics.

    Figure 6

    Figure 6

    Panel a: Examples of beats in which the MC, AO, AC and MC fiducial points are characterized by the expected clear-cut peaks (for MC, AO and AC) or trough (for MO). Panel b: other beats in which the FPs are marked only by an inflection point.

    Full size image
    Figure 7

    Figure 7

    Example of SCG inflection point corresponding to the mitral valve closure. M-mode ultrasoung image from a healthy subject.

    Full size image

    Improvement of FPs Time Resolution

    At this stage of the procedure, the time position of each detected FP was identified with a 5 ms resolution (the original signal was sampled at 200 Hz). Let’s term this time “Coarse FP Time Position”, CFTP. We further refined the FP estimate by obtaining a “HiRes FP Time Position”, HRFTP, with the resolution of 1 ms. The Nyquist–Shannon sampling theorem guarantees that this was possible because the signal is bandlimited to 40 Hz and sampled at 200 Hz, thus the interpolation can accurately reconstruct the signal and determine the actual locations of the FPs at a higher resolution. As schematized in Fig. 8, for each FP we considered a 101-sample window centered on its CFTP, then we interpolated the data window by the sync function, re-sampled the interpolating function at 1 kHz and repeated the FP estimation on the hi-res samples in a 10 ms window centered on the CFTP.

    A clarification: although only the 10 ms windows was used to refine the FP time location, the sync function was applied on the larger 101 sample window to minimize possible edge effects on the interpolated curve in the target interval.

    The hi-res time of occurrence of valid AO, AC, MO and MC fiducial points were stored for the subsequent analysis.

    Phase 3–Congruency check and CTI estimation

    In order to detect and eliminate possible residual outliers in the identified FPs, two additional congruency checks were made. The first directly on the FPs and the second on the derived CTIs.

    As to the first check, each FPRdelay was compared with the average FPRdelay, AFPRdelay computed over the preceding 5 beats. In absence of at least one preceding valid value, the current FPRdelay was compared with the AFPRdelay computed over the subsequent 5 beats. The FP was accepted if the difference between the FPRdelay of the current beat and AFPRdelay was lower or equal to 10 ms for MC and AO and 20 ms for AC and MO.

    Then, from the beat-to-beat series of RRI, AO, AC, MO and MC, the CTIs were computed as indicated in section 3.

    Finally, the second congruency check was done on the derived CTIs. In this case we verified that the difference between each CTI (PEP, ICT, LVET and IRT) and the average value of the same CTI observed in the preceding, or following 5 beats, analogously to the first check, was lower or equal to 10 ms for PEP and 20 ms for the remaining indexes. In case a CTI exceeded this limit, the FPs which concurred to its estimation were descarted (e.g. in case a given LVET exceeded the thresholds, the same LVET and the corresponding AO and AC fiducial points used for its estimation were discarded from the final data series).

    For Brain-Computer Interfaces to Be Useful, They’ll Need to Be Wireless

    For decades, brain-computer interfaces have been imagined as a way for people who are paralyzed or those who have lost arms to be able to do everyday tasks like brushing their hair or clicking a TV remote—just by thinking about it.

    Such robotic devices exist today—so far, a handful of patients in research labs around the world have tried them, giving them a limited range of motions. But researchers are still years away from making these devices practical for use in people’s homes, says Andrew Schwartz, distinguished professor of neurobiology at the University of Pittsburgh.

    Speaking at MIT Technology Review’s annual EmTech MIT conference in Cambridge, Massachusetts, on Tuesday, Schwartz said these interfaces will need a number of modifications in order for that to happen. He said he’s working on such a model with Draper Laboratory, based in Cambridge, but hasn’t been able to get funding to move the project along.

    “This is very much on the outskirts of science,” said Schwartz, an early pioneer of these interfaces.

    Today’s brain-computer interfaces involve electrodes or chips that are placed in or on the brain and communicate with an external computer. These electrodes collect brain signals and then send them to the computer, where special software analyzes them and translates them into commands. These commands are relayed to a machine, like a robotic arm, that carries out the desired action.

    The embedded chips, which are about the size of a pea, attach to so-called pedestals that sit on top of the patient’s head and connect to a computer via a cable. The robotic limb also attaches to the computer. This clunky set-up means patients can’t yet use these interfaces in their homes.

    In order to get there, Schwartz said, researchers need to size down the computer so it’s portable, build a robotic arm that can attach to a wheelchair, and make the entire interface wireless so that the heavy pedestals can be removed from a person’s head.

    Schwartz said he hopes paralyzed patients will someday be able to use these interfaces to control all sorts of objects beyond just a robotic arm.

    “Just imagine someone using telemetry going into a smart home and being able to operate all these devices merely by thinking about them,” he said.

    The big hurdle is that the science behind the technology is so complex. The interface relies on translating the “neural code”—that is, the pattern of activity of neurons in the brain—into specific commands that will translate into movements. Currently, the kinds of gestures people are able to perform with these interfaces are limited because scientists know little about all the different patterns in which the neurons fire.

    For example, Schwartz and his team have been able to get monkeys, as well as a few human participants, to grasp objects using a brain-computer interface and a robotic arm. But applying force to objects, such as by pushing or pulling, is more complicated and requires a different set of neural codes that the computer algorithms need to learn. 

    “We don’t have a good understanding yet of how motion and force are mixed together to allow us to interact with objects,” Schwartz said. Scientists will need to study the brain more to figure out what these signals look like.