Extracellular fluid viscosity enhances cell migration and cancer dissemination.

Cells respond to physical stimuli, such as stiffness1, fluid shear stress2 and hydraulic pressure3,4. Extracellular fluid viscosity is a key physical cue that varies under physiological and pathological conditions, such as cancer5. However, its influence on cancer biology and the mechanism by which cells sense and respond to changes in viscosity are unknown. Here we demonstrate that elevated viscosity counterintuitively increases the motility of various cell types on two-dimensional surfaces and in confinement, and increases cell dissemination from three-dimensional tumour spheroids. Increased mechanical loading imposed by elevated viscosity induces an actin-related protein 2/3 (ARP2/3)-complex-dependent dense actin network, which enhances Na+/H+ exchanger 1 (NHE1) polarization through its actin-binding partner ezrin. NHE1 promotes cell swelling and increased membrane tension, which, in turn, activates transient receptor potential cation vanilloid 4 (TRPV4) and mediates calcium influx, leading to increased RHOA-dependent cell contractility. The coordinated action of actin remodelling/dynamics, NHE1-mediated swelling and RHOA-based contractility facilitates enhanced motility at elevated viscosities. Breast cancer cells pre-exposed to elevated viscosity acquire TRPV4-dependent mechanical memory through transcriptional control of the Hippo pathway, leading to increased migration in zebrafish, extravasation in chick embryos and lung colonization in mice. Cumulatively, extracellular viscosity is a physical cue that regulates both short- and long-term cellular processes with pathophysiological relevance to cancer biology.

Emergency department imaging utilization post-transcatheter aortic valve replacement: single institution 7-year experience.

PURPOSE: This study aims to highlight presentations, acute findings and imaging phenotypes of patients presenting to the emergency department (ED) within 30 days of a transcatheter aortic valve replacement (TAVR). METHODS: A retrospective review of patients diagnosed with aortic valve disease who underwent a TAVR between Jan 2015 and Nov 2021 at a large academic medical center was completed. From an initial 1271 patients, 146 were included based on their presentation to the ED within 30 days post-TAVR procedure. Patient data, including ED presentation details and imaging results, were recorded and de-identified. RESULTS: Of the 146 post-TAVR patients, there were 168 ED visits within 30 days. The median time to ED after TAVR was 12 days. Respiratory symptoms were the most common complaint (27%). Neurological (23%) and cardiovascular symptoms (18%) followed. Cross-sectional imaging was conducted 250 times across visits, with an average of 1.7 scans per patient. CTs were most frequently used, followed by ultrasounds, especially echocardiograms and duplex extremity vasculature ultrasounds. 30.1% of patients had acute findings from imaging. Specific findings included heart failure (5.5%), access site complications (5.5%), pneumonia (5.5%), intracranial pathologies (3.4% for strokes and 0.7% for hematoma), and pleural effusion (3.4%). Echocardiograms and CTA chest were most associated with significant acute findings. CONCLUSION: Our study highlights the vital role of early and accurate imaging in post-TAVR patients within 30 days post-procedure. As transcatheter approaches rise in popularity, emergency radiologists become instrumental in diagnosing common post-procedural presentations. Continued research is essential to devise post-discharge strategies to curtail readmissions and related costs. Proper imaging ensures prompt, effective care, enhancing overall patient outcomes.

Emergency department imaging utilization of cancer patients treated with bevacizumab: single-institution 8-year experience.

PURPOSE: This study aims to highlight the presentations, imaging, and clinical outcomes of cancer patients presenting to the emergency department (ED) while receiving bevacizumab (Avastin) therapy. METHODS: Our retrospective study was based on data from a single institution to identify cancer patients who presented acutely to the ED between 2014 and 2021 within 3 months of beginning bevacizumab who subsequently received diagnostic imaging with CT, MRI, ultrasound, and/or nuclear medicine ventilation/perfusion (VQ) scans. Data gathered included presenting symptoms grouped by body system, imaging impressions, and clinical outcomes, including hospitalization and discontinuation of bevacizumab after each ED visit. Imaging examinations and patient charts were reviewed by a team of fellowship-trained radiologists, radiology residents, and medical students. RESULTS: A total of 84 patients who presented to the ED were included for analysis. This included 32 (38.1%) males and 52 (61.9%) females, with a mean age of 61.2 years and an age range of 29-91 years. Neurological symptoms were the most common presenting symptoms, followed by abdominal symptoms and respiratory symptoms. Head imaging with CT and MRI was the most common imaging ordered with 55 total examinations, followed by abdominal imaging with 37 CT abdomen/pelvis (A/P) examinations, and then CT chest imaging with 22 examinations. Imaging revealed a serious adverse drug reaction in 21 (25.0%) patients, disease progression in 19 (22.6%), and no acute imaging findings in 44 (52.4%) patients. Imaging diagnoses were significantly associated with treatment planning, with a positive determination of bevacizumab-related serious adverse reaction on imaging leading to discontinuation of bevacizumab (p = 0.001). CONCLUSION: Multimodality imaging was a commonly used assessment tool for cancer patients receiving bevacizumab who presented to the ED. Imaging played a crucial role in diagnosis in these patients, especially of treatment-related serious adverse reactions and disease progression. Positive imaging findings of serious adverse reactions affected patient management including discontinuation of bevacizumab.

Migration and 3D Traction Force Measurements inside Compliant Microchannels.

Cells migrate in vivo through channel-like tracks. While polydimethylsiloxane devices emulate such tracks in vitro, their channel walls are impermeable and have supraphysiological stiffness. Existing hydrogel-based platforms address these issues but cannot provide high-throughput analysis of cell motility in independently controllable stiffness and confinement. We herein develop polyacrylamide (PA)-based microchannels of physiological stiffness and prescribed dimensions for high-throughput analysis of cell migration and identify a biphasic dependence of speed upon confinement and stiffness. By utilizing novel four-walled microchannels with heterogeneous stiffness, we reveal the distinct contributions of apicolateral versus basal microchannel wall stiffness to confined versus unconfined migration. While the basal wall stiffness dictates unconfined migration, apicolateral stiffness controls confined migration. By tracking nanobeads embedded within channel walls, we innovate three-dimensional traction force measurements around spatially confining cells at subcellular resolution. Our unique and highly customizable device fabrication strategy provides a physiologically relevant in vitro platform to study confined cells.

Oropharyngeal cancer outcomes correlate with p16 status, multinucleation and immune infiltration.

Oropharyngeal squamous cell carcinoma (OPSCC), largely fueled by the human papillomavirus (HPV), has a complex biological and immunologic phenotype. Although HPV/p16 status can be used to stratify OPSCC patients as a function of survival, it remains unclear what drives an improved treatment response in HPV-associated OPSCC and whether targetable biomarkers exist that can inform a precision oncology approach. We analyzed OPSCC patients treated between 2000 and 2016 and correlated locoregional control (LRC), disease-free survival (DFS) and overall survival (OS) with conventional clinical parameters, risk parameters generated using deep-learning algorithms trained to quantify tumor-infiltrating lymphocytes (TILs) (OP-TIL) and multinucleated tumor cells (MuNI) and targeted transcriptomics. P16 was a dominant determinant of LRC, DFS and OS, but tobacco exposure, OP-TIL and MuNI risk features correlated with clinical outcomes independent of p16 status and the combination of p16, OP-TIL and MuNI generated a better stratification of OPSCC risk compared to individual parameters. Differential gene expression (DEG) analysis demonstrated overlap between MuNI and OP-TIL and identified genes involved in DNA repair, oxidative stress response and tumor immunity as the most prominent correlates with survival. Alteration of inflammatory/immune pathways correlated strongly with all risk features and oncologic outcomes. This suggests that development of OPSCC consists of an intersection between multiple required and permissive oncogenic and immunologic events which may be mechanistically linked. The strong relationship between tumor immunity and oncologic outcomes in OPSCC regardless of HPV status may provide opportunities for further biomarker development and precision oncology approaches incorporating immune checkpoint inhibitors for maximal anti-tumor efficacy.

Coronary Artery Calcium Scoring: Current Status and Future Directions.

Coronary artery calcium (CAC) scores obtained from CT scans have been shown to be prognostic in assessment of the risk for development of cardiovascular diseases, facilitating the prediction of outcome in asymptomatic individuals. Currently, several methods to calculate the CAC score exist, and each has its own set of advantages and disadvantages. Agatston CAC scoring is the most extensively used method. CAC scoring is currently recommended for use in asymptomatic individuals to predict the risk of developing cardiovascular diseases and the disease-specific mortality. In specific subsets of patients, the CAC score has also been recommended for reclassifying cardiovascular risk and aiding in decision making when planning primary prevention interventions such as statin therapy. The progression of CAC scores on follow-up images has been shown to be linked to risk of myocardial infarction and cardiovascular mortality. While the CAC score is a validated tool used clinically, several challenges, including various pitfalls associated with the acquisition, calculation, and interpretation of the score, prevent more widespread adoption of this metric. Recent research has been focused extensively on strategies to improve existing scoring methods, including measuring calcium attenuation, detecting microcalcifications, and focusing on extracoronary calcifications, and on strategies to improve image acquisition. A better understanding of CAC scoring approaches will help radiologists and other physicians better use and interpret these scores in their workflows. An invited commentary by S. Gupta is available online. Online supplemental material is available for this article. ©RSNA, 2022.

Imaging of the Left Atrial Appendage Before Occluder Device Placement: Evaluation of Virtual Monoenergetic Images in a Single-Bolus Dual-Phase Protocol.

PURPOSE: Preimplantation cardiac computed tomography (CT) for assessment of the left atrial appendage (LAA) enables correct sizing of the device and the detection of contraindications, such as thrombi. In the arterial phase, distinction between false filling defects and true thrombi can be hampered by insufficient contrast medium distribution. A delayed scan can be used to further differentiate both conditions, but contrast in these acquisitions is relatively lower. In this study, we investigated whether virtual monoenergetic images (VMI) from dual-energy spectral detector CT (SDCT) can be used to enhance contrast and visualization in the delayed phase. MATERIALS AND METHODS: Forty-nine patients receiving SDCT imaging of the LAA were retrospectively enrolled. The imaging protocol comprised dual-phase acquisitions with single-bolus contrast injection. Conventional images (CI) from both phases and 40-keV VMI from the delayed phase were reconstructed. Attenuation, signal-, and contrast-to-noise ratios (SNR/CNR) were calculated by placing regions-of-interest in the LAA, left atrium, and muscular portion of interventricular septum. Two radiologists subjectively evaluated conspicuity and homogeneity of contrast distribution within the LAA. RESULTS: Contrast of the LAA decreased significantly in the delayed phase but was significantly improved by VMI, showing comparable attenuation, SNR, and CNR to CI from the arterial phase (attenuation/SNR/CNR, CI arterial phase: 266.0 ± 117.0 HU/14.2 ± 7.2/6.6 ± 3.9; CI-delayed phase: 107.6 ± 35.0 HU/5.9 ± 3.0/1.0 ± 1.0; VMI delayed phase: 260.3 ± 108.6 HU/18.2 ± 10.6/4.8 ± 3.4). The subjective reading confirmed the objective findings showing improved conspicuity and homogeneity in the delayed phase. CONCLUSIONS: The investigated single-bolus dual-phase acquisition protocol provided improved visualization of the LAA. Homogeneity of contrast media was higher in the delayed phase, while VMI maintained high contrast.

Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions In Vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters.

BACKGROUND: Radiomic descriptors from magnetic resonance imaging (MRI) are promising for disease diagnosis and characterization but may be sensitive to differences in imaging parameters. OBJECTIVE: To evaluate the repeatability and robustness of radiomic descriptors within healthy brain tissue regions on prospectively acquired MRI scans; in a test-retest setting, under controlled systematic variations of MRI acquisition parameters, and after postprocessing. STUDY TYPE: Prospective. SUBJECTS: Fifteen healthy participants. FIELD STRENGTH/SEQUENCE: A 3.0 T, axial T2 -weighted 2D turbo spin-echo pulse sequence, 181 scans acquired (2 test/retest reference scans and 12 with systematic variations in contrast weighting, resolution, and acceleration per participant; removing scans with artifacts). ASSESSMENT: One hundred and forty-six radiomic descriptors were extracted from a contiguous 2D region of white matter in each scan, before and after postprocessing. STATISTICAL TESTS: Repeatability was assessed in a test/retest setting and between manual and automated annotations for the reference scan. Robustness was evaluated between the reference scan and each group of variant scans (contrast weighting, resolution, and acceleration). Both repeatability and robustness were quantified as the proportion of radiomic descriptors that fell into distinct ranges of the concordance correlation coefficient (CCC): excellent (CCC > 0.85), good (0.7 ≤ CCC ≤ 0.85), moderate (0.5 ≤ CCC < 0.7), and poor (CCC < 0.5); for unprocessed and postprocessed scans separately. RESULTS: Good to excellent repeatability was observed for 52% of radiomic descriptors between test/retest scans and 48% of descriptors between automated vs. manual annotations, respectively. Contrast weighting (TR/TE) changes were associated with the largest proportion of highly robust radiomic descriptors (21%, after processing). Image resolution changes resulted in the largest proportion of poorly robust radiomic descriptors (97%, before postprocessing). Postprocessing of images with only resolution/acceleration differences resulted in 73% of radiomic descriptors showing poor robustness. DATA CONCLUSIONS: Many radiomic descriptors appear to be nonrobust across variations in MR contrast weighting, resolution, and acceleration, as well in test-retest settings, depending on feature formulation and postprocessing. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Radiomic Features of Primary Rectal Cancers on Baseline T2 -Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study.

BACKGROUND: Twenty-five percent of rectal adenocarcinoma patients achieve pathologic complete response (pCR) to neoadjuvant chemoradiation and could avoid proctectomy. However, pretreatment clinical or imaging markers are lacking in predicting response to chemoradiation. Radiomic texture features from MRI have recently been associated with therapeutic response in other cancers. PURPOSE: To construct a radiomics texture model based on pretreatment MRI for identifying patients who will achieve pCR to neoadjuvant chemoradiation in rectal cancer, including validation across multiple scanners and sites. STUDY TYPE: Retrospective. SUBJECTS: In all, 104 rectal cancer patients staged with MRI prior to long-course chemoradiation followed by proctectomy; curated from three institutions. FIELD STRENGTH/SEQUENCE: 1.5T-3.0T, axial higher resolution T2 -weighted turbo spin echo sequence. ASSESSMENT: Pathologic response was graded on postsurgical specimens. In total, 764 radiomic features were extracted from single-slice sections of rectal tumors on processed pretreatment T2 -weighted MRI. STATISTICAL TESTS: Three feature selection schemes were compared for identifying radiomic texture descriptors associated with pCR via a discovery cohort (one site, N = 60, cross-validation). The top-selected radiomic texture features were used to train and validate a random forest classifier model for pretreatment identification of pCR (two external sites, N = 44). Model performance was evaluated via area under the curve (AUC), accuracy, sensitivity, and specificity. RESULTS: Laws kernel responses and gradient organization features were most associated with pCR (P ≤ 0.01); as well as being commonly identified across all feature selection schemes. The radiomics model yielded a discovery AUC of 0.699 ± 0.076 and a hold-out validation AUC of 0.712 with 70.5% accuracy (70.0% sensitivity, 70.6% specificity) in identifying pCR. Radiomic texture features were resilient to variations in magnetic field strength as well as being consistent between two different expert annotations. Univariate analysis revealed no significant associations of baseline clinicopathologic or MRI findings with pCR (P = 0.07-0.96). DATA CONCLUSION: Radiomic texture features from pretreatment MRIs may enable early identification of potential pCR to neoadjuvant chemoradiation, as well as generalize across sites. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Quantitative nuclear histomorphometric features are predictive of Oncotype DX risk categories in ductal carcinoma in situ: preliminary findings.

BACKGROUND: Oncotype DX (ODx) is a 12-gene assay assessing the recurrence risk (high, intermediate, and low) of ductal carcinoma in situ (pre-invasive breast cancer), which guides clinicians regarding prescription of radiotherapy. However, ODx is expensive, time-consuming, and tissue-destructive. In addition, the actual prognostic meaning for the intermediate ODx risk category remains unclear. METHODS: In this work, we evaluated the ability of quantitative nuclear histomorphometric features extracted from hematoxylin and eosin-stained slide images of 62 ductal carcinoma in situ (DCIS) patients to distinguish between the corresponding ODx risk categories. The prognostic value of the identified image signature was further evaluated on an independent validation set of 30 DCIS patients in its ability to distinguish those DCIS patients who progressed to invasive carcinoma versus those who did not. Following nuclear segmentation and feature extraction, feature ranking strategies were employed to identify the most discriminating features between individual ODx risk categories. The selected features were then combined with machine learning classifiers to establish models to predict ODx risk categories. The model performance was evaluated using the average area under the receiver operating characteristic curve (AUC) using cross validation. In addition, an unsupervised clustering approach was also implemented to evaluate the ability of nuclear histomorphometric features to discriminate between the ODx risk categories. RESULTS: Features relating to spatial distribution, orientation disorder, and texture of nuclei were identified as most discriminating between the high ODx and the intermediate, low ODx risk categories. Additionally, the AUC of the most discriminating set of features for the different classification tasks was as follows: (1) high vs low ODx (0.68), (2) high vs. intermediate ODx (0.67), (3) intermediate vs. low ODx (0.57), (4) high and intermediate vs. low ODx (0.63), (5) high vs. low and intermediate ODx (0.66). Additionally, the unsupervised clustering resulted in intermediate ODx risk category patients being co-clustered with low ODx patients compared to high ODx. CONCLUSION: Our results appear to suggest that nuclear histomorphometric features can distinguish high from low and intermediate ODx risk category patients. Additionally, our findings suggest that histomorphometric features for intermediate ODx were more similar to low ODx compared to high ODx risk category.

Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas.

Purpose To evaluate ability of radiomic (computer-extracted imaging) features to distinguish non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials and Methods For this retrospective study, screening or standard diagnostic noncontrast CT images were collected for 290 patients (mean age, 68 years; range, 18-92 years; 125 men [mean age, 67 years; range, 18-90 years] and 165 women [mean age, 68 years; range, 33-92 years]) from two institutions between 2007 and 2013. Histopathologic analysis was available for one nodule per patient. Corresponding nodule of interest was identified on axial CT images by a radiologist with manual annotation. Nodule shape, wavelet (Gabor), and texture-based (Haralick and Laws energy) features were extracted from intra- and perinodular regions. Features were pruned to train machine learning classifiers with 145 patients. In a test set of 145 patients, classifier results were compared against a convolutional neural network (CNN) and diagnostic readings of two radiologists. Results Support vector machine classifier with intranodular radiomic features achieved an area under the receiver operating characteristic curve (AUC) of 0.75 on the test set. Combining radiomics of intranodular with perinodular regions improved the AUC to 0.80. On the same test set, CNN resulted in an AUC of 0.76. Radiologist readers achieved AUCs of 0.61 and 0.60, respectively. Conclusion Radiomic features from intranodular and perinodular regions of nodules can distinguish non-small cell lung cancer adenocarcinomas from benign granulomas at noncontrast CT. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Nishino in this issue.

3D Printing-Based Integrated Water Quality Sensing System.

The online and accurate monitoring of drinking water supply networks is critically in demand to rapidly detect the accidental or deliberate contamination of drinking water. At present, miniaturized water quality monitoring sensors developed in the laboratories are usually tested under ambient pressure and steady-state flow conditions; however, in Water Distribution Systems (WDS), both the pressure and the flowrate fluctuate. In this paper, an interface is designed and fabricated using additive manufacturing or 3D printing technology-material extrusion (Trade Name: fused deposition modeling, FDM) and material jetting-to provide a conduit for miniaturized sensors for continuous online water quality monitoring. The interface is designed to meet two main criteria: low pressure at the inlet of the sensors and a low flowrate to minimize the water bled (i.e., leakage), despite varying pressure from WDS. To meet the above criteria, a two-dimensional computational fluid dynamics model was used to optimize the geometry of the channel. The 3D printed interface, with the embedded miniaturized pH and conductivity sensors, was then tested at different temperatures and flowrates. The results show that the response of the pH sensor is independent of the flowrate and temperature. As for the conductivity sensor, the flowrate and temperature affect only the readings at a very low conductivity (4 µS/cm) and high flowrates (30 mL/min), and a very high conductivity (460 µS/cm), respectively.

The Undermined ACGME Subcompetency: A Roadmap for Radiology Residency Programs to Foster Residents-as-Educators.

Radiology Residency programs in the United States use a set of six core competencies as laid out by the Accreditation Council for Graduate Medical Education (ACGME) to evaluate the foundational skills of every resident. Despite the fact that educational skills are included under the heading of Practice-Based Learning and Improvement in the ACGME guidelines for radiology residents, it is often underappreciated and undervalued, when compared with medical knowledge or patient care. In this paper, the authors lay out the important role of residents-as-educators and how it can be inculcated as part of formal training during residency. They enunciate five pillars for academic programs to build and maintain the pedagogical skills of their radiology residents: Training, Practicing, Providing Feedback, Mentoring, and Changing the Culture. The authors believe that implementing this will holistically benefit radiology residents as well as radiology in building future educators. The authors also delineate the challenges that programs currently face in implementation and ways to overcome them.

Analysis of ChatGPT publications in radiology: Literature so far.

OBJECTIVE: To perform a detailed qualitative and quantitative analysis of the published literature on ChatGPT and radiology in the nine months since its public release, detailing the scope of the work in the short timeframe. METHODS: A systematic literature search was carried out of the MEDLINE, EMBASE databases through August 15, 2023 for articles that were focused on ChatGPT and imaging/radiology. Articles were classified into original research and reviews/perspectives. Quantitative analysis was carried out by two experienced radiologists using objective scoring systems for evaluating original and non-original research. RESULTS: 51 articles were published involving ChatGPT and radiology/imaging dating from 26 Jan 2023 to the last article published on 14 Aug 2023. 23 articles were original research while the rest included reviews/perspectives or brief communications. For quantitative analysis scored by two readers, we included 23 original research and 17 non-original research articles (after excluding 11 letters as responses to previous articles). Mean score for original research was 3.20 out of 5 (across five questions), while mean score for non-original research was 1.17 out of 2 (across six questions). Mean score grading performance of ChatGPT in original research was 3.20 out of five (across two questions). DISCUSSION: While it is early days for ChatGPT and its impact in radiology, there has already been a plethora of articles talking about the multifaceted nature of the tool and how it can impact every aspect of radiology from patient education, pre-authorization, protocol selection, generating differentials, to structuring radiology reports. Most articles show impressive performance of ChatGPT which can only improve with more research and improvements in the tool itself. There have also been several articles which have highlighted the limitations of ChatGPT in its current iteration, which will allow radiologists and researchers to improve these areas.

3.0-T MR-guided transgluteal in-bore-targeted prostate biopsy under local anesthesia in patients without rectal access: a single-institute experience and review of literature.

PURPOSE: To describe the technique and evaluate the performance of MRI-guided transgluteal in-bore-targeted biopsy of the prostate gland under local anesthesia in patients without rectal access. METHODS: Ten men (mean age, 69 (range 57-86) years) without rectal access underwent 13 MRI-guided transgluteal in-bore-targeted biopsy of the prostate gland under local anesthesia. All patients underwent mp-MRI at our institute prior to biopsy. Three patients had prior US-guided transperineal biopsy which was unsuccessful in one, negative in one, and yielded GG1 (GS6) PCa in one. Procedure time, complications, histopathology result, and subsequent management were recorded. RESULTS: Median interval between rectal surgery and presentation with elevated PSA was 12.5 years (interquartile range (IQR) 25-75, 8-36.5 years). Mean PSA was 11.9 (range, 4.8 -59.0) ng/ml and PSA density was 0.49 (0.05 -3.2) ng/ml/ml. Distribution of PI-RADS v2.0/2.1 scores of the targeted lesions were PI-RADS 5-3; PI-RADS 4-6; and PI-RADS 3-1. Mean lesion size was 1.5 cm (range, 1.0-3.6 cm). Median interval between MRI and biopsy was 5.5 months (IQR 25-75, 1.5-9 months). Mean procedure time was 47.4 min (range, 29-80 min) and the number of cores varied between 3 and 5. Of the 13 biopsies, 4 yielded clinically significant prostate cancer (csPca), with a Gleason score ≥ 7, 1 yielded insignificant prostate cancer (Gleason score = 6), 7 yielded benign prostatic tissue, and one was technically unsuccessful. 3/13 biopsies were repeat biopsies which detected csPCa in 2 out of the 3 patients. None of the patients had biopsy-related complication. Biopsy result changed management to radiation therapy with ADT in 2 patients with the rest on active surveillance. CONCLUSION: MRI-guided transgluteal in-bore-targeted biopsy of the prostate gland under local anesthesia is feasible in patients without rectal access.

Assessing appropriate responses to ACR urologic imaging scenarios using ChatGPT and Bard.

Artificial intelligence (AI) has recently become a trending tool and topic regarding productivity especially with publicly available free services such as ChatGPT and Bard. In this report, we investigate if two widely available chatbots chatGPT and Bard, are able to show consistent accurate responses for the best imaging modality for urologic clinical situations and if they are in line with American College of Radiology (ACR) Appropriateness Criteria (AC). All clinical scenarios provided by the ACR were inputted into ChatGPT and Bard with result compared to the ACR AC and recorded. Both chatbots had an appropriate imaging modality rate of of 62% and no significant difference in proportion of correct imaging modality was found overall between the two services (p>0.05). The results of our study found that both ChatGPT and Bard are similar in their ability to suggest the most appropriate imaging modality in a variety of urologic scenarios based on ACR AC criteria. Nonetheless, both chatbots lack consistent accuracy and further development is necessary for implementation in clinical settings. For proper use of these AI services in clinical decision making, further developments are needed to improve the workflow of physicians.

PTEN Regulates Myofibroblast Activation in Valvular Interstitials Cells based on Subcellular Localization.

Aortic valve stenosis (AVS) is characterized by altered mechanics of the valve leaflets, which disrupts blood flow through the aorta and can cause left ventricle hypotrophy. These changes in the valve tissue result in activation of resident valvular interstitial cells (VICs) into myofibroblasts, which have increased levels of αSMA in their stress fibers. The persistence of VIC myofibroblast activation is a hallmark of AVS. In recent years, the tumor suppressor gene phosphatase and tensin homolog (PTEN) has emerged as an important player in the regulation of fibrosis in various tissues (e.g., lung, skin), which motivated us to investigate PTEN as a potential protective factor against matrix-induced myofibroblast activation in VICs. In aortic valve samples from humans, we found high levels of PTEN in healthy tissue and low levels of PTEN in diseased tissue. Then, using pharmacological inducers to treat VIC cultures, we observed PTEN overexpression prevented stiffness-induced myofibroblast activation, whereas genetic and pharmacological inhibition of PTEN further activated myofibroblasts. We also observed increased nuclear PTEN localization in VICs cultured on stiff matrices, and nuclear PTEN also correlated with smaller nuclei, altered expression of histones and a quiescent fibroblast phenotype. Together, these results suggest that PTEN not only suppresses VIC activation, but functions to promote quiescence, and could serve as a potential pharmacological target for the treatment of AVS.

Fully synthetic hydrogels promote robust crypt formation in intestinal organoids.

Initial landmark studies in the design of synthetic hydrogels for intestinal organoid culture identified precise matrix requirements for differentiation, namely decompression of matrix-imposed forces and supplementation of laminin. But beyond stating the necessity of laminin, organoid-laminin interactions have gone largely unstudied, as this ubiquitous requirement of exogenous laminin hinders investigation. In this work, we exploit a fast stress relaxing, boronate ester based synthetic hydrogel for the culture of intestinal organoids, and fortuitously discover that unlike all other synthetic hydrogels to date, laminin does not need to be supplemented for crypt formation. This highly defined material provides a unique opportunity to investigate laminin-organoid interactions and how it influences crypt evolution and organoid function. Via fluorescent labeling of non-canonical amino acids, we further show that adaptable boronate ester bonds increase deposition of nascent proteins, including laminin. Collectively, these results advance the understanding of how mechanical and matricellular signaling influence intestinal organoid development.

Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study.

Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion. In this study we employed machine learning and statistical atlas-based approaches to explore possible changes in lung shape among COVID-19 patients and evaluated whether the extent of these changes was associated with COVID-19 severity. On a large multi-institutional dataset (N = 3443), three different populations were defined; a) healthy (no COVID-19), b) mild COVID-19 (no ventilator required), c) severe COVID-19 (ventilator required), and the presence of lung shape differences between them were explored using baseline chest CT. Significant lung shape differences were observed along mediastinal surfaces of the lungs across all severity of COVID-19 disease. Additionally, differences were seen on basal surfaces of the lung when compared between healthy and severe COVID-19 patients. Finally, an AI model (a 3D residual convolutional network) characterizing these shape differences coupled with lung infiltrates (ground-glass opacities and consolidation regions) was found to be associated with COVID-19 severity.

Nonlinear Elastic Bottlebrush Polymer Hydrogels Modulate Actomyosin Mediated Protrusion Formation in Mesenchymal Stromal Cells.

The nonlinear elasticity of many tissue-specific extracellular matrices is difficult to recapitulate without the use of fibrous architectures, which couple strain-stiffening with stress relaxation. Herein, bottlebrush polymers are synthesized and crosslinked to form poly(ethylene glycol)-based hydrogels and used to study how strain-stiffening behavior affects human mesenchymal stromal cells (hMSCs). By tailoring the bottlebrush polymer length, the critical stress associated with the onset of network stiffening is systematically varied, and a unique protrusion-rich hMSC morphology emerges only at critical stresses within a biologically accessible stress regime. Local cell-matrix interactions are quantified using 3D traction force microscopy and small molecule inhibitors are used to identify cellular machinery that plays a critical role in hMSC mechanosensing of the engineered, strain-stiffening microenvironment. Collectively, this study demonstrates how covalently crosslinked bottlebrush polymer hydrogels can recapitulate strain-stiffening biomechanical cues at biologically relevant stresses and be used to probe how nonlinear elastic matrix properties regulate cellular processes.