Molecular characterization of human peripheral nerves using desorption electrospray ionization mass spectrometry imaging.

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is a molecular imaging method that can be used to elucidate the small-molecule composition of tissues and map their spatial information using two-dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI-MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for which are known to carry various nerve fiber types were harvested from a fresh cadaveric donor: mixed, motor and sensory (sciatic and femoral); cutaneous, sensory (sural); and autonomic (vagus). Tissue samples were harvested to include the nerve bundles in addition to surrounding connective tissue. Samples were flash-frozen, embedded in optimal cutting temperature compound in cross-section, and sectioned at 14 µm. Following DESI-MSI analysis, identical tissue sections were stained with hematoxylin and eosin. In this proof-of-concept study, a combination of multivariate and univariate statistical methods was used to evaluate molecular differences between the nerve and adjacent tissue and between nerve subtypes. The acquired mass spectral profiles of the peripheral nerve samples presented trends in ion abundances that seemed to be characteristic of nerve tissue and spatially corresponded to the associated histology of the tissue sections. Principal component analysis (PCA) supported the separation of the samples into distinct nerve and adjacent tissue classes. This classification was further supported by the K-means clustering analysis, which showed separation of the nerve and background ions. Differences in ion expression were confirmed using ANOVA which identified statistically significant differences in ion expression between the nerve subtypes. The PCA plot suggested some separation of the nerve subtypes into four classes which corresponded with the nerve types. This was supported by the K-means clustering. Some overlap in classes was noted in these two clustering analyses. This study provides emerging evidence that DESI-MSI is an effective tool for metabolomic profiling of peripheral nerves. Our results suggest that peripheral nerves have molecular profiles that are distinct from the surrounding connective tissues and that DESI-MSI may be able to discriminate between nerve subtypes. DESI-MSI of peripheral nerves may be a valuable technique that could be used to improve our understanding of peripheral nerve anatomy and physiology. The ability to utilize ambient mass spectrometry techniques in real time could also provide an unprecedented advantage for surgical decision making, including in nerve-sparing procedures in the future.

Bridging 3D Slicer and ROS2 for Image-Guided Robotic Interventions.

Developing image-guided robotic systems requires access to flexible, open-source software. For image guidance, the open-source medical imaging platform 3D Slicer is one of the most adopted tools that can be used for research and prototyping. Similarly, for robotics, the open-source middleware suite robot operating system (ROS) is the standard development framework. In the past, there have been several "ad hoc" attempts made to bridge both tools; however, they are all reliant on middleware and custom interfaces. Additionally, none of these attempts have been successful in bridging access to the full suite of tools provided by ROS or 3D Slicer. Therefore, in this paper, we present the SlicerROS2 module, which was designed for the direct use of ROS2 packages and libraries within 3D Slicer. The module was developed to enable real-time visualization of robots, accommodate different robot configurations, and facilitate data transfer in both directions (between ROS and Slicer). We demonstrate the system on multiple robots with different configurations, evaluate the system performance and discuss an image-guided robotic intervention that can be prototyped with this module. This module can serve as a starting point for clinical system development that reduces the need for custom interfaces and time-intensive platform setup.

Sensor-Based Automated Detection of Electrosurgical Cautery States.

In computer-assisted surgery, it is typically required to detect when the tool comes into contact with the patient. In activated electrosurgery, this is known as the energy event. By continuously tracking the electrosurgical tools' location using a navigation system, energy events can help determine locations of sensor-classified tissues. Our objective was to detect the energy event and determine the settings of electrosurgical cautery-robustly and automatically based on sensor data. This study aims to demonstrate the feasibility of using the cautery state to detect surgical incisions, without disrupting the surgical workflow. We detected current changes in the wires of the cautery device and grounding pad using non-invasive current sensors and an oscilloscope. An open-source software was implemented to apply machine learning on sensor data to detect energy events and cautery settings. Our methods classified each cautery state at an average accuracy of 95.56% across different tissue types and energy level parameters altered by surgeons during an operation. Our results demonstrate the feasibility of automatically identifying energy events during surgical incisions, which could be an important safety feature in robotic and computer-integrated surgery. This study provides a key step towards locating tissue classifications during breast cancer operations and reducing the rate of positive margins.

Optimizing resource utilization during proficiency-based training of suturing skills in medical students: a randomized controlled trial of faculty-led, peer tutor-led, and holography-augmented methods of teaching.

BACKGROUND: Suturing is a fundamental skill in undergraduate medical education. It can be taught by faculty-led, peer tutor-led, and holography-augmented methods; however, the most educationally effective and cost-efficient method for proficiency-based teaching of suturing is yet to be determined. METHODS: We conducted a randomized controlled trial comparing faculty-led, peer tutor-led, and holography-augmented proficiency-based suturing training in pre-clerkship medical students. Holography-augmented training provided holographic, voice-controlled instructional material. Technical skill was assessed using hand motion analysis every ten sutures and used to construct learning curves. Proficiency was defined by one standard deviation within average faculty surgeon performance. Intervention arms were compared using one-way ANOVA of the number of sutures placed, full-length sutures used, time to proficiency, and incremental costs incurred. Surveys were used to evaluate participant preferences. RESULTS: Forty-four students were randomized to the faculty-led (n = 16), peer tutor-led (n = 14), and holography-augmented (n = 14) intervention arms. At proficiency, there were no differences between groups in the number of sutures placed, full-length sutures used, and time to achieve proficiency. The incremental costs of the holography-augmented method were greater than faculty-led and peer tutor-led instruction ($247.00 ± $12.05, p < 0.001) due to the high cost of the equipment. Faculty-led teaching was the most preferred method (78.0%), while holography-augmented was the least preferred (0%). 90.6% of students reported high confidence in performing simple interrupted sutures, which did not differ between intervention arms (faculty-led 100.0%, peer tutor-led 90.0%, holography-augmented 83.3%, p = 0.409). 93.8% of students felt the program should be offered in the future. CONCLUSION: Faculty-led and peer tutor-led instructional methods of proficiency-based suturing teaching were superior to holography-augmented method with respect to costs and participants' preferences despite being educationally equivalent.

Real-time electromagnetic navigation for breast-conserving surgery using NaviKnife technology: A matched case-control study.

Breast-conserving surgery (BCS) is a mainstay in breast cancer treatment. For nonpalpable breast cancers, current strategies have limited accuracy, contributing to high positive margin rates. We developed NaviKnife, a surgical navigation system based on real-time electromagnetic (EM) tracking. The goal of this study was to confirm the feasibility of intraoperative EM navigation in patients with nonpalpable breast cancer and to assess the potential value of surgical navigation. We recruited 40 patients with ultrasound visible, single, nonpalpable lesions, undergoing BCS. Feasibility was assessed by equipment functionality and sterility, acceptable duration of the operation, and surgeon feedback. Secondary outcomes included specimen volume, positive margin rate, and reoperation outcomes. Study patients were compared to a control group by a matched case-control analysis. There was no equipment failure or breach of sterility. The median operative time was 66 (44-119) minutes with NaviKnife vs 65 (34-158) minutes for the control (P = .64). NaviKnife contouring time was 3.2 (1.6-9) minutes. Surgeons rated navigation as easy to setup, easy to use, and useful in guiding nonpalpable tumor excision. The mean specimen volume was 95.4 ± 73.5 cm3 with NaviKnife and 140.7 ± 100.3 cm3 for the control (P = .01). The positive margin rate was 22.5% with NaviKnife and 28.7% for the control (P = .52). The re-excision specimen contained residual disease in 14.3% for NaviKnife and 50% for the control (P = .28). Our results demonstrate that real-time EM navigation is feasible in the operating room for BCS. Excisions performed with navigation result in the removal of less breast tissue without compromising postive margin rates.

Toward predictive modeling of catheter-based pulmonary valve replacement into native right ventricular outflow tracts.

BACKGROUND: Pulmonary insufficiency is a consequence of transannular patch repair in Tetralogy of Fallot (ToF) leading to late morbidity and mortality. Transcatheter native outflow tract pulmonary valve replacement has become a reality. However, predicting a secure, atraumatic implantation of a catheter-based device remains a significant challenge due to the complex and dynamic nature of the right ventricular outflow tract (RVOT). We sought to quantify the differences in compression and volume for actual implants, and those predicted by pre-implant modeling. METHODS: We used custom software to interactively place virtual transcatheter pulmonary valves (TPVs) into RVOT models created from pre-implant and post Harmony valve implant CT scans of 5 ovine surgical models of TOF to quantify and visualize device volume and compression. RESULTS: Virtual device placement visually mimicked actual device placement and allowed for quantification of device volume and radius. On average, simulated proximal and distal device volumes and compression did not vary statistically throughout the cardiac cycle (P = 0.11) but assessment was limited by small sample size. In comparison to actual implants, there was no significant pairwise difference in the proximal third of the device (P > 0.80), but the simulated distal device volume was significantly underestimated relative to actual device implant volume (P = 0.06). CONCLUSIONS: This study demonstrates that pre-implant modeling which assumes a rigid vessel wall may not accurately predict the degree of distal RVOT expansion following actual device placement. We suggest the potential for virtual modeling of TPVR to be a useful adjunct to procedural planning, but further development is needed.

Comparison of 3D Echocardiogram-Derived 3D Printed Valve Models to Molded Models for Simulated Repair of Pediatric Atrioventricular Valves.

Mastering the technical skills required to perform pediatric cardiac valve surgery is challenging in part due to limited opportunity for practice. Transformation of 3D echocardiographic (echo) images of congenitally abnormal heart valves to realistic physical models could allow patient-specific simulation of surgical valve repair. We compared materials, processes, and costs for 3D printing and molding of patient-specific models for visualization and surgical simulation of congenitally abnormal heart valves. Pediatric atrioventricular valves (mitral, tricuspid, and common atrioventricular valve) were modeled from transthoracic 3D echo images using semi-automated methods implemented as custom modules in 3D Slicer. Valve models were then both 3D printed in soft materials and molded in silicone using 3D printed "negative" molds. Using pre-defined assessment criteria, valve models were evaluated by congenital cardiac surgeons to determine suitability for simulation. Surgeon assessment indicated that the molded valves had superior material properties for the purposes of simulation compared to directly printed valves (p < 0.01). Patient-specific, 3D echo-derived molded valves are a step toward realistic simulation of complex valve repairs but require more time and labor to create than directly printed models. Patient-specific simulation of valve repair in children using such models may be useful for surgical training and simulation of complex congenital cases.

MR-guided perineural injection of the ganglion impar: technical considerations and feasibility.

OBJECTIVE: Perineural ganglion impar injections are used in the management of pelvic pain syndromes; however, there is no consensus regarding the optimal image guidance. Magnetic resonance imaging (MRI) provides high soft tissue contrast and the potential to directly visualize and target the ganglion. The purpose of this study was to assess the feasibility of MR-guided percutaneous perineural ganglion impar injections. MATERIALS AND METHODS: Six MR-guided ganglion impar injections were performed in six human cadavers. Procedures were performed with a clinical 1.5-Tesla MRI system through a far lateral transgluteus approach. Ganglion impar visibility, distance from the sacrococcygeal joint, number of intermittent MRI control steps required to place the needle, target error between the intended and final needle tip location, inadvertent punctures of non-targeted vulnerable structures, injectant distribution, and procedure time were determined. RESULTS: The ganglion impar was seen on MRI in 4/6 (66 %) of cases and located 0.8 mm cephalad to 16.3 mm caudad (average 1.2 mm caudad) to the midpoint of the sacrococcygeal joint. Needle placement required an average of three MRI control steps (range, 2-6). The average target error was 2.2 ± 2.1 mm. In 6/6 cases (100 %), there was appropriate periganglionic distribution and filling of the presacrococcygeal space. No punctures of non-targeted structures occurred. The median procedure time was 20 min (range, 12-29 min). CONCLUSION: Interventional MRI can visualize and directly target the ganglion impar for accurate needle placement and successful periganglionic injection with the additional benefit of no ionizing radiation exposure to patient and staff. Our results support clinical evaluation.

Computerized training system for ultrasound-guided lumbar puncture on abnormal spine models: a randomized controlled trial.

PURPOSE: A randomized controlled trial was carried out to determine whether Perk Tutor, a computerized training platform that displays an ultrasound image and real-time needle position in a three-dimensional (3D) anatomical model, would benefit residents learning ultrasound-guided lumbar puncture (LP) in simulation phantoms with abnormal spinal anatomy. METHODS: Twenty-four residents were randomly assigned to either the Perk Tutor (P) or the Control (C) group and asked to perform an LP with ultrasound guidance on part-task trainers with spinal pathology. Group P was trained with the 3D display along with conventional ultrasound imaging, while Group C used conventional ultrasound only. Both groups were then tested solely with conventional ultrasound guidance on an abnormal spinal model not previously seen. We measured potential tissue damage, needle path in tissue, total procedure time, and needle insertion time. Procedural success rate was a secondary outcome. RESULTS: The needle tracking measurements (expressed as median [interquartile range; IQR]) in Group P vs Group C revealed less potential tissue damage (39.7 [21.3-42.7] cm(2) vs 128.3 [50.3-208.2] cm(2), respectively; difference 88.6; 95% confidence intervals [CI] 24.8 to 193.5; P = 0.01), a shorter needle path inside the tissue (426.0 [164.9-571.6] mm vs 629.7 [306.4-2,879.1] mm, respectively; difference 223.7; 95% CI 76.3 to 1,859.9; P = 0.02), and lower needle insertion time (30.3 [14.0-51.0] sec vs 59.1 [26.0-136.2] sec, respectively; difference 28.8; 95% CI 2.2 to 134.0; P = 0.05). Total procedure time and overall success rates between groups did not differ. CONCLUSION: Residents trained with augmented reality 3D visualization had better performance metrics on ultrasound-guided LP in pathological spine models.

Assessment of lumbar puncture skill in experts and nonexperts using checklists and quantitative tracking of needle trajectories: implications for competency-based medical education.

UNLABELLED: CONSTRUCT: With the current shift toward competency-based education, rigorous assessment tools are needed for procedurally based tasks. BACKGROUND: Multiple tools exist to evaluate procedural skills, each with specific weaknesses. APPROACH: We sought to determine if quantitative needle tracking could be used as a measure of lumbar puncture (LP) performance and added discriminatory value to a dichotomous checklist. Thirty-two medical students were divided into 2 groups. One group was asked to practice an LP once (single practice [SP]) and the other 5 times (multiple practice [MP]). Experts (attending ER physicians, senior ER residents, and a junior anesthesia resident) were used as comparators. Medical students were assessed again at 1 month to assess skill retention. Groups were assessed performing an LP with an electromagnetic tracking device that allows the needle's 3-dimensional movements to be captured and analyzed, and a dichotomous checklist. RESULTS: Quantitative needle metrics as assessed by electromagnetic tracking showed a decreasing trend in needle movement distance with practice and with experience. The SP group made significantly more checklist mistakes initially as compared to the MP group (1.2 vs. 0.3, p <.05). At 1 month, there was a significant increase in both groups' mistakes (SP 3.4 vs. MP 1.3, p =.01). No correlation existed between individuals' needle motion and checklist mistakes. CONCLUSIONS: These findings suggest that quantitative needle tracking identifies students who struggle with needle insertion but are successful at completing the dichotomous checklist.

ImSpect: Image-driven self-supervised learning for surgical margin evaluation with mass spectrometry.

PURPOSE: Real-time assessment of surgical margins is critical for favorable outcomes in cancer patients. The iKnife is a mass spectrometry device that has demonstrated potential for margin detection in cancer surgery. Previous studies have shown that using deep learning on iKnife data can facilitate real-time tissue characterization. However, none of the existing literature on the iKnife facilitate the use of publicly available, state-of-the-art pretrained networks or datasets that have been used in computer vision and other domains. METHODS: In a new framework we call ImSpect, we convert 1D iKnife data, captured during basal cell carcinoma (BCC) surgery, into 2D images in order to capitalize on state-of-the-art image classification networks. We also use self-supervision to leverage large amounts of unlabeled, intraoperative data to accommodate the data requirements of these networks. RESULTS: Through extensive ablation studies, we show that we can surpass previous benchmarks of margin evaluation in BCC surgery using iKnife data, achieving an area under the receiver operating characteristic curve (AUC) of 81%. We also depict the attention maps of the developed DL models to evaluate the biological relevance of the embedding space CONCLUSIONS: We propose a new method for characterizing tissue at the surgical margins, using mass spectrometry data from cancer surgery.

From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery.

PURPOSE: Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real time. However, evaluation of such models with respect to pathology outcomes is necessary for their successful translation into clinical practice. METHODS: Sixteen deep learning models based on established architectures in the literature are trained on 7318 ultrasound images from 33 patients. Models are ranked by an expert based on their contours generated from images in our test set. Generated contours from each model are also analyzed using recorded cautery trajectories of five navigated BCS cases to predict margin status. Predicted margins are compared with pathology reports. RESULTS: The best-performing model using both quantitative evaluation and our visual ranking framework achieved a mean Dice score of 0.959. Quantitative metrics are positively associated with expert visual rankings. However, the predictive value of generated contours was limited with a sensitivity of 0.750 and a specificity of 0.433 when tested against pathology reports. CONCLUSION: We present a clinical evaluation of deep learning models trained for intraoperative tumor segmentation in breast-conserving surgery. We demonstrate that automatic contouring is limited in predicting pathology margins despite achieving high performance on quantitative metrics.

Euclidean and Shape-Based Analysis of the Dynamic Mitral Annulus in Children using a Novel Open-Source Framework.

BACKGROUND: The dynamic shape of the normal adult mitral annulus has been shown to be important to mitral valve function. However, annular dynamics of the healthy mitral valve in children have yet to be explored. The aim of this study was to model and quantify the shape and major modes of variation of pediatric mitral valve annuli in four phases of the cardiac cycle using transthoracic echocardiography. METHODS: The mitral valve annuli of 100 children and young adults with normal findings on three-dimensional echocardiography were modeled in four different cardiac phases using the SlicerHeart extension for 3D Slicer. Annular metrics were quantified using SlicerHeart, and optimal normalization to body surface area was explored. Mean annular shapes and the principal components of variation were computed using custom code implemented in a new SlicerHeart module (Annulus Shape Analyzer). Shape was regressed over metrics of age and body surface area, and mean shapes for five age-stratified groups were generated. RESULTS: The ratio of annular height to commissural width of the mitral valve ("saddle shape") changed significantly throughout age for systolic phases (P < .001) but within a narrow range (median range, 0.20-0.25). Annular metrics changed statistically significantly between the diastolic and systolic phases of the cardiac cycle. Visually, the annular shape was maintained with respect to age and body surface area. Principal-component analysis revealed that the pediatric mitral annulus varies primarily in size (mode 1), ratio of annular height to commissural width (mode 2), and sphericity (mode 3). CONCLUSIONS: The saddle-shaped mitral annulus is maintained throughout childhood but varies significantly throughout the cardiac cycle. The major modes of variation in the pediatric mitral annulus are due to size, ratio of annular height to commissural width, and sphericity. The generation of age- and size-specific mitral annular shapes may inform the development of appropriately scaled absorbable or expandable mitral annuloplasty rings for children.

Preoperative CT and survival data for patients undergoing resection of colorectal liver metastases.

The liver is a common site for the development of metastases in colorectal cancer. Treatment selection for patients with colorectal liver metastases (CRLM) is difficult; although hepatic resection will cure a minority of CRLM patients, recurrence is common. Reliable preoperative prediction of recurrence could therefore be a valuable tool for physicians in selecting the best candidates for hepatic resection in the treatment of CRLM. It has been hypothesized that evidence for recurrence could be found via quantitative image analysis on preoperative CT imaging of the future liver remnant before resection. To investigate this hypothesis, we have collected preoperative hepatic CT scans, clinicopathologic data, and recurrence/survival data, from a large, single-institution series of patients (n = 197) who underwent hepatic resection of CRLM. For each patient, we also created segmentations of the liver, vessels, tumors, and future liver remnant. The largest of its kind, this dataset is a resource that may aid in the development of quantitative imaging biomarkers and machine learning models for the prediction of post-resection hepatic recurrence of CRLM.

Augmented reality visualisation using an image overlay system for MR-guided interventions: technical performance of spine injection procedures in human cadavers at 1.5 Tesla.

OBJECTIVES: To prospectively assess the technical performance of an augmented reality system for MR-guided spinal injection procedures. METHODS: The augmented reality system was used with a clinical 1.5-T MRI system. A total of 187 lumbosacral spinal injection procedures (epidural injection, spinal nerve root injection, facet joint injection, medial branch block, discography) were performed in 12 human cadavers. Needle paths were planned with the Perk Station module of 3D Slicer software on high-resolution MR images. Needles were placed under augmented reality MRI navigation. MRI was used to confirm needle locations. T1-weighted fat-suppressed MRI was used to visualise the injectant. Outcome variables assessed were needle adjustment rate, inadvertent puncture of non-targeted structures, successful injection rate and procedure time. RESULTS: Needle access was achieved in 176/187 (94.1 %) targets, whereas 11/187 (5.9 %) were inaccessible. Six of 11 (54.5 %) L5-S1 disks were inaccessible, because of an axial obliquity of 30˚ (27˚-34˚); 5/11 (45.5 %) facet joints were inaccessible because of osteoarthritis or fusion. All accessible targets (176/187, 94.1 %) were successfully injected, requiring 47/176 (26.7 %) needle adjustments. There were no inadvertent punctures of vulnerable structures. Median procedure time was 10.2 min (5-19 min). CONCLUSIONS: Image overlay navigated MR-guided spinal injections were technically accurate. Disks with an obliquity ≥27˚ may be inaccessible.

Tracked ultrasound snapshots in percutaneous pedicle screw placement navigation: a feasibility study.

BACKGROUND: Computerized navigation improves the accuracy of minimally invasive pedicle screw placement during spine surgery. Such navigation, however, exposes both the patient and the staff to radiation during surgery. To avoid intraoperative exposure to radiation, tracked ultrasound snapshots-ultrasound image frames coupled with corresponding spatial positions-could be used to map preoperatively defined screw plans into the intraoperative coordinate frame. The feasibility of such an approach, however, has not yet been investigated. QUESTIONS/PURPOSES: Are there vertebral landmarks that can be identified using tracked ultrasound snapshots? Can tracked ultrasound snapshots allow preoperative pedicle screw plans to be accurately mapped--compared with CT-derived pedicle screw plans--into the intraoperative coordinate frame in a simulated setting? METHODS: Ultrasound visibility of registration landmarks was checked on volunteers and phantoms. An ultrasound machine with integrated electromagnetic tracking was used for tracked ultrasound acquisition. Registration was performed using 3D Slicer open-source software (www.slicer.org). Two artificial lumbar spine phantoms were used to evaluate registration accuracy of pedicle screw plans using tracked ultrasound snapshots. Registration accuracy was determined by comparing the ultrasound-derived plans with the CT-derived plans. RESULTS: The four articular processes proved to be identifiable using tracked ultrasound snapshots. Pedicle screw plans were registered to the intraoperative coordinate system using landmarks. The registrations were sufficiently accurate in that none of the registered screw plans intersected the pedicle walls. Registered screw plan positions had an error less than 1.28 ± 1.37 mm (average ± SD) in each direction and an angle difference less than 1.92° ± 1.95° around each axis relative to the CT-derived positions. CONCLUSIONS: Registration landmarks could be located using tracked ultrasound snapshots and permitted accurate mapping of pedicle screw plans to the intraoperative coordinate frame in a simulated setting. CLINICAL RELEVANCE: Tracked ultrasound may allow accurate computer-navigated pedicle screw placement while avoiding ionizing radiation in the operating room; however, further studies that compare this approach with other navigation techniques are needed to confirm the practical use of this new approach.

A Review of Low-Cost Ultrasound Compatible Phantoms.

Ultrasound-compatible phantoms are used to develop novel US-based systems and train simulated medical interventions. The price difference between lab-made and commercially available ultrasound-compatible phantoms lead to the publication of many papers categorized as low-cost in the literature. The aim of this review was to improve the phantom selection process by summarizing the pertinent literature. We compiled papers on US-compatible spine, prostate, vascular, breast, kidney, and li ver phantoms. We reviewed papers for cost and accessibility, providing an overview of the materials, construction time, shelf life, needle insertion limits, and manufacturing and evaluation methods. This information was summarized by anatomy. The clinical application associated with each phantom was also reported for those interested in a particular intervention. Techniques and common practices for building low-cost phantoms were provided. Overall, this article aims to summarize a breadth of ultrasound-compatible phantom research to enable informed phantom methods selection.

Real-time integration between Microsoft HoloLens 2 and 3D Slicer with demonstration in pedicle screw placement planning.

PURPOSE: Up to date, there has been a lack of software infrastructure to connect 3D Slicer to any augmented reality (AR) device. This work describes a novel connection approach using Microsoft HoloLens 2 and OpenIGTLink, with a demonstration in pedicle screw placement planning. METHODS: We developed an AR application in Unity that is wirelessly rendered onto Microsoft HoloLens 2 using Holographic Remoting. Simultaneously, Unity connects to 3D Slicer using the OpenIGTLink communication protocol. Geometrical transform and image messages are transferred between both platforms in real time. Through the AR glasses, a user visualizes a patient's computed tomography overlaid onto virtual 3D models showing anatomical structures. We technically evaluated the system by measuring message transference latency between the platforms. Its functionality was assessed in pedicle screw placement planning. Six volunteers planned pedicle screws' position and orientation with the AR system and on a 2D desktop planner. We compared the placement accuracy of each screw with both methods. Finally, we administered a questionnaire to all participants to assess their experience with the AR system. RESULTS: The latency in message exchange is sufficiently low to enable real-time communication between the platforms. The AR method was non-inferior to the 2D desktop planner, with a mean error of 2.1 ± 1.4 mm. Moreover, 98% of the screw placements performed with the AR system were successful, according to the Gertzbein-Robbins scale. The average questionnaire outcomes were 4.5/5. CONCLUSIONS: Real-time communication between Microsoft HoloLens 2 and 3D Slicer is feasible and supports accurate planning for pedicle screw placement.

Development and validation of a radiofrequency ablation treatment planning system for vertebral metastases.

PURPOSE: Bone-targeted radiofrequency ablation (RFA) is widely used in the treatment of vertebral metastases. While radiation therapy utilizes established treatment planning systems (TPS) based on multimodal imaging to optimize treatment volumes, current RFA of vertebral metastases has been limited to qualitative image-based assessment of tumour location to direct probe selection and access. This study aimed to design, develop and evaluate a computational patient-specific RFA TPS for vertebral metastases. METHODS: A TPS was developed on the open-source 3D slicer platform, including procedural setup, dose calculation (based on finite element modelling), and analysis/visualization modules. Usability testing was carried out by 7 clinicians involved in the treatment of vertebral metastases on retrospective clinical imaging data using a simplified dose calculation engine. In vivo evaluation was performed in a preclinical porcine model (n = 6 vertebrae). RESULTS: Dose analysis was successfully performed, with generation and display of thermal dose volumes, thermal damage, dose volume histograms and isodose contours. Usability testing showed an overall positive response to the TPS as beneficial to safe and effective RFA. The in vivo porcine study showed good agreement between the manually segmented thermally damaged volumes vs. the damage volumes identified from the TPS (Dice Similarity Coefficient = 0.71 ± 0.03, Hausdorff distance = 1.2 ± 0.1 mm). CONCLUSION: A TPS specifically dedicated to RFA in the bony spine could help account for tissue heterogeneities in both thermal and electrical properties. A TPS would enable visualization of damage volumes in 2D and 3D, assisting clinicians in decisions about potential safety and effectiveness prior to performing RFA in the metastatic spine.

Metabolically Active Zones Involving Fatty Acid Elongation Delineated by DESI-MSI Correlate with Pathological and Prognostic Features of Colorectal Cancer.

Colorectal cancer (CRC) is the second leading cause of cancer deaths. Despite recent advances, five-year survival rates remain largely unchanged. Desorption electrospray ionization mass spectrometry imaging (DESI) is an emerging nondestructive metabolomics-based method that retains the spatial orientation of small-molecule profiles on tissue sections, which may be validated by 'gold standard' histopathology. In this study, CRC samples were analyzed by DESI from 10 patients undergoing surgery at Kingston Health Sciences Center. The spatial correlation of the mass spectral profiles was compared with histopathological annotations and prognostic biomarkers. Fresh frozen sections of representative colorectal cross sections and simulated endoscopic biopsy samples containing tumour and non-neoplastic mucosa for each patient were generated and analyzed by DESI in a blinded fashion. Sections were then hematoxylin and eosin (H and E) stained, annotated by two independent pathologists, and analyzed. Using PCA/LDA-based models, DESI profiles of the cross sections and biopsies achieved 97% and 75% accuracies in identifying the presence of adenocarcinoma, using leave-one-patient-out cross validation. Among the m/z ratios exhibiting the greatest differential abundance in adenocarcinoma were a series of eight long-chain or very-long-chain fatty acids, consistent with molecular and targeted metabolomics indicators of de novo lipogenesis in CRC tissue. Sample stratification based on the presence of lympovascular invasion (LVI), a poor CRC prognostic indicator, revealed the abundance of oxidized phospholipids, suggestive of pro-apoptotic mechanisms, was increased in LVI-negative compared to LVI-positive patients. This study provides evidence of the potential clinical utility of spatially-resolved DESI profiles to enhance the information available to clinicians for CRC diagnosis and prognosis.