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BackgroundMultiparametric magnetic resonance imaging (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the subjective Prostate Imaging Reporting and Data System (PI-RADS) system and quantitative apparent diffusion coefficient (ADC) are inconsistent. Restriction spectrum imaging (RSI) is an advanced diffusion-weighted MRI technique that yields a quantitative imaging biomarker for csPCa called the RSI restriction score (RSIrs).ObjectiveTo evaluate RSIrs for automated patient-level detection of csPCa.Design setting and participantsWe retrospectively studied all patients (n=151) who underwent 3 T mpMRI and RSI (a 2-min sequence on a clinical scanner) for suspected prostate cancer at University of California San Diego during 2017-2019 and had prostate biopsy within 180 d of MRI.InterventionWe calculated the maximum RSIrs and minimum ADC within the prostate, and obtained PI-RADS v2.1 from medical records.Outcome measurements and statistical analysisWe compared the performance of RSIrs, ADC, and PI-RADS for the detection of csPCa (grade group ≥2) on the best available histopathology (biopsy or prostatectomy) using the area under the curve (AUC) with two-tailed α=0.05. We also explored whether the combination of PI-RADS and RSIrs might be superior to PI-RADS alone and performed subset analyses within the peripheral and transition zones.Results and limitationsAUC values for ADC, RSIrs, and PI-RADS were 0.48 (95% confidence interval: 0.39, 0.58), 0.78 (0.70, 0.85), and 0.77 (0.70, 0.84), respectively. RSIrs and PI-RADS were each superior to ADC for patient-level detection of csPCa (p&nbsp

Objective: To identify postoperative vaginal morphology and position factors associated with prolapse recurrence following vaginal surgery. Design: Secondary analysis of MRIs of the Defining Mechanisms of Anterior Vaginal Wall Descent cross-sectional study. Setting: Eight clinical sites in the US Pelvic Floor Disorders Network. Population: Women who underwent vaginal mesh hysteropexy (hysteropexy) with sacrospinous fixation or vaginal hysterectomy with uterosacral ligament suspension (hysterectomy) for symptomatic uterovaginal prolapse between April 2013 and February 2015. Methods: MRIs (rest, strain) obtained 30-42 months after surgery, or earlier for participants with recurrence who desired reoperation prior to 30 months, were analyzed. Prolapse recurrence was defined as prolapse beyond the hymen at strain on MRI. Vaginal segmentations (at rest) were used to create 3D models placed in a morphometry algorithm to quantify and compare vaginal morphology (angulation, dimensions) and position between groups. Main Outcome Measures: Vaginal angulation (upper, lower, and upper-lower vaginal angles in the sagittal and coronal plane), dimensions (length, maximum transverse width, surface area, volume), and position (apex, mid-vagina) at rest. Results: Of the 82 women analyzed, 12/41 (29%) in the hysteropexy group and 22/41 (54%) in the hysterectomy group had prolapse recurrence. After hysteropexy, recurrences had a more laterally deviated upper vagina (p=0.02) at rest than successes. After hysterectomy, recurrences had a more inferiorly (lower) positioned vaginal apex (p=0.01) and mid-vagina (p=0.01) at rest than successes. Conclusions: Vaginal angulation and position were associated with prolapse recurrence and indicative of vaginal support mechanisms related to surgical technique and unaddressed anatomical defects. Future prospective studies in women before and after prolapse surgery may distinguish these two factors. Funding: Eunice Kennedy Shriver National Institute of Child Health and Human Development-sponsored Pelvic Floor Disorders Network (Grant/Award Number: U10 HD054214, U10 HD041267, U10 HD041261, U10 HD069013, U10 HD069025, U10 HD069010, U10 HD069006, U10 HD054215, U01 HD069031); National Institutes of Health Office of Research on Women’s Health; Boston Scientific Corporation; National Academies of Sciences, Engineering, and Medicine’s Ford Foundation Predoctoral Fellowship Program

PURPOSE: To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. MATERIALS AND METHODS: This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. RESULTS: Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10(−3), 2.8 × 10(-3), and >3.0 ×10(-2) mm(2)/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). CONCLUSION: The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.

There is an increasing need for tactile shear sensors, particularly for medical applications such as orthopedic rehabilitation. Examples include measuring interfacial shear stresses between a residual limb and prosthesis to monitor socket fit and improve residual limb tissue health, and tracking shearing between a foot and shoe for assessing performance in athletes. However, there are considerable challenges in implementing shear force sensors for orthopedic applications due to the requirements for noninvasiveness, low mass, low power, and robustness against motion artifacts, normal force, and/or electromagnetic fields. To address these challenges, we designed, fabricated, and characterized a simple, low-cost, optoelectronic sensor that can measure multi-axial shear stresses. This novel sensor is based on a red, green, and blue (RGB) light-emitting diode (LED) projecting a cyclic illumination of RGB light onto a color pattern surface. As shear strain causes a displacement between the LED and the color pattern, the intensities of the reflected lights change due to the shift of the color pattern position. A photodiode captures the reflected light intensity at each color illumination, allowing the determination of the color pattern surface displacement and the shear along two axes. In this paper, we also report the efficacy of the sensor under benchtop testing conditions, confirming the potential of this technology for shear monitoring in orthopedic devices such as protheses or shoes. Future efforts will focus on miniaturization and packaging of the sensors, and characterizing their performance for the aforementioned medical applications.

In a phase III randomized trial, adding a radiation boost to visible tumor(s) on MRI improved prostate cancer disease-free and metastasis-free survival without additional toxicity. However, radiation oncologists’ ability to identify prostate tumors is critical and represents a major barrier to widely adopting intraprostatic tumor radiotherapy boost for patients. We previously developed a quantitative diffusion MRI biomarker for prostate cancer, called the Restriction Spectrum Imaging restriction score (RSIrs), that has been shown to improve radiologist identification of clinically significant prostate cancer.42 radiation oncologists (participants) from multiple, international institutions contoured prostate tumors on 40 patient cases using standard MRI with or without RSIrs map, producing 1646 target volumes. Use of RSIrs maps significantly improved all evaluated accuracy metrics, including participants’ percent overlap with consensus expert target volume (73% vs. 42%, pPatient SummaryAdding an extra boost of radiation to tumor(s) visible on MRI has been shown to prevent cancer recurrence and cancer spread beyond the prostate without adding additional side effects; however, drawing the prostate tumor on MRI is difficult, and most radiation oncologists have not been trained to do this. We have developed an advanced MRI technique (RSIrs maps) that increases tumor visibility. We found that RSIrs maps improve radiation oncologists’ accuracy in targeting prostate tumors.

BackgroundT2-weighted MRI is standard for detecting clinically significant prostate cancer (csPCa) by identifying visible lesions that stand out from the background prostate.PurposeTo determine whether patients with csPCa have abnormalT2-weighted signal in non-lesion, background prostate tissue (BP).MethodsThis retrospective study included two patient cohorts who underwent 3T MRI examination for suspected csPCa. Median (urine-normalized)T2-weighted signal was computed for BP and compared between patients with and without csPCa. csPCa discrimination performance ofT2-weighted BP signal was evaluated using area under receiver operating characteristic curves (AUC).T2andS0(a proxy for proton density) were computed and compared between patients with and without csPCa.T2was also recomputed using larger buffers around csPCa lesions. csPCa discrimination performance was compared between two predictors: Restriction Spectrum Imaging (RSI)C1and RSIC1normalized by global prostate medianT2-weighted signal.ResultsCohort 1: 46 patients (age: 64±10 years). Cohort 2: 151 patients (65±8 years). Urine-normalizedT2-weighted signal was systematically lower in BP of subjects with csPCa (p≤0.034) and indicated the presence of cancer (cohort 1: AUC=0.80; cohort 2: AUC=0.68). BPT2was significantly lower in csPCa patients (p≤0.011), whileS0was not (p≥0.30). BPT2measurements were stable to within 5% with buffers from 0 to 30 mm around visible lesions. csPCa discrimination improved with incorporation of BPT2-weighted signal (cohort 1: AUC=0.72 for RSIC1alone, versus 0.81 with BPT2-weighted signal; cohort 2: AUC=0.63 versus 0.76).ConclusionLowerT2-weighted signal in BP suggests the presence of csPCa.

The lower–extremity system acts like a spring in the running stance phase. Vertical stiffness (Kvert) and leg stiffness (Kleg) reflect the whole–body center of mass (COM) and leg–spring system loading and response in running, while joint stiffness (Kjoint) represents joint–level dynamic loading and response. This study aimed to investigate whether Kjoint is associated with Kvert and Kleg across different running speeds. Twenty healthy subjects were recruited into a treadmill running study (1.8 to 3.8 m/s, with 0.4 m/s intervals). We found that Kjoint accounted for 38.4% of the variance in Kvert (p = 0.046) and 42.4% of the variance in Kleg (p = 0.028) at 1.8 m/s; Kjoint also accounted for 49.8% of the variance in Kvert (p = 0.014) and 79.3% of the variance in Kleg (p < 0.0001) at 2.2 m/s. Kknee had the strongest unique association with Kvert and Kleg at 1.8 and 2.2 m/s. Kjoint was associated with Kleg at a wider range of speeds. These findings built a connection between joint stiffness and limb stiffness within a certain range of running speeds. Kknee may need to be considered as an important factor in future limb stiffness optimization and general running performance enhancement.

Goal : The purpose of this study was to provide an initial examination of the utility of the Beta Process - Auto Regressive - Hidden Markov Model (BP-AR-HMM) for the prior identification of gait events. A secondary objective was to determine whether the output of the model could be used for classification and prediction of locomotion states. Methods: In this study we utilized the output of the BP-AR-HMM to develop user-independent identification of gait events and gait classification from an idealized three-dimensional acceleration signal. The input acceleration data were collected from two walking (1.4 and 1.6 ms−1) and two running (2.6 and 3.0 ms−1) steady state speeds, and during two dynamic walk to run and run to walk transitions (1.8–2.4 and 2.4–1.8 ms−1) on an instrumented force treadmill. Results: The BP-AR-HMM identified 9 unique states. Of these, two states, 4 and 1, were utilized to estimate initial contact and toe off, respectively. The lead time from the first instance of state 4 to initial contact was 0.13 ± 0.02 s. Similarly, the first instance of state 1 occurred 0.14 ± 0.03 s before toe off. Two other states (3 and 7) were examined for possible utilization in a probabilistic model for the prediction of pending locomotion state transitions. Conclusion: The identification of gait events prior to their occurrence by the BP-AR-HMM appears to be an approach that can minimize the quantity of sensor data in an offline approach. Furthermore, there is evidence it could also be used as a basis to build a probabilistic model to estimate locomotion transitions.

Background Diffusion magnetic resonance imaging (MRI) is integral to detection of prostate cancer (PCa), but conventional apparent diffusion coefficient (ADC) cannot capture the complexity of prostate tissues and tends to yield noisy images that do not distinctly highlight cancer. A four-compartment restriction spectrum imaging (RSI4 ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI4 -C1 , yielded greatest tumor conspicuity. Purpose To evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI4 -C1 ) as a quantitative voxel-level classifier of PCa. Study type Retrospective. Subjects Forty-six men who underwent an extended MRI acquisition protocol for suspected PCa. Twenty-three men had benign prostates, and the other 23 men had PCa. Field strength/sequence A 3 T, multishell diffusion-weighted and axial T2-weighted sequences. Assessment High-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI4 -C1 and conventional ADC. Classifier images were also generated. Statistical tests Voxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. RSI4 -C1 was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR90 ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05. Results RSI4 -C1 outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR90 (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P Data conclusion RSI4 -C1 yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection and facilitate clinical applications like targeted biopsy and treatment planning. Evidence level 3 TECHNICAL EFFICACY: Stage 2.

OBJECTIVES Early diagnosis of Cesarean scar pregnancies (CSP) remains difficult. This study describes a novel sonographic marker, the FundAl Retroflexion (FAR) angle, that may be used in the first trimester. The objective of the study is to compare the FAR angle between CSP and normal pregnancies. METHODS For this case-control study, we reviewed images from our institution's database that were acquired from January 2016 to December 2019. All cases of CSP and randomly selected controls, defined as patients with history of Cesarean delivery and normal implantation, that underwent ultrasound evaluation at

Background Diffusion-weighted (DW) echo-planar imaging (EPI) is prone to geometric distortions due to B0 inhomogeneities. Both prospective and retrospective approaches have been developed to decrease and correct such distortions. Purpose The purpose of this work was to evaluate the performance of reduced-field-of-view (FOV) acquisition and retrospective distortion correction methods in decreasing distortion artifacts for breast imaging. Coverage of the axilla in reduced-FOV DW magnetic resonance imaging (MRI) and residual distortion were also assessed. Study type Retrospective. Population/phantom Breast phantom and 169 women (52.4 ± 13.4 years old) undergoing clinical breast MRI. Field strength/sequence A 3.0 T/ full- and reduced-FOV DW gradient-echo EPI sequence. Assessment Performance of reversed polarity gradient (RPG) and FSL topup in correcting breast full- and reduced-FOV EPI data was evaluated using the mutual information (MI) metric between EPI and anatomical images. Two independent breast radiologists determined if coverage on both EPI data sets was adequate to evaluate axillary nodes and identified residual nipple distortion artifacts. Statistical tests Two-way repeated-measures analyses of variance and post hoc tests were used to identify differences between EPI modality and distortion correction method. Generalized linear mixed effects models were used to evaluate differences in axillary coverage and residual nipple distortion. Results In a breast phantom, residual distortions were 0.16 ± 0.07 cm and 0.22 ± 0.13 cm in reduced- and full-FOV EPI with both methods, respectively. In patients, MI significantly increased after distortion correction of full-FOV (11 ± 5% and 18 ± 9%, RPG and topup) and reduced-FOV (8 ± 4% both) EPI data. Axillary nodes were observed in 99% and 69% of the cases in full- and reduced-FOV EPI images. Residual distortion was observed in 93% and 0% of the cases in full- and reduced-FOV images. Data conclusion Minimal distortion was achieved with RPG applied to reduced-FOV EPI data. RPG improved distortions for full-FOV images but with more modest improvements and limited correction near the nipple. Evidence level 3 TECHNICAL EFFICACY: Stage 1.

Purpose: Diffusion-weighted MRI (DW-MRI) is a contrast-free modality that has demonstrated ability to discriminate between predefined benign and malignant breast lesions. However, how well DW-MRI discriminates cancer from all other breast tissue voxels in a clinical setting is unknown. Here we explore the voxelwise ability to distinguish cancer from healthy breast tissue using signal contributions from the newly developed three-component multi-b-value DW-MRI model. Experimental Design: Patients with pathology-proven breast cancer from two datasets (n = 81 and n = 25) underwent multi-b-value DW-MRI. The three-component signal contributions C1 and C2 and their product, C1C2, and signal fractions F1, F2, and F1F2 were compared with the image defined on maximum b-value (DWImax), conventional apparent diffusion coefficient (ADC), and apparent diffusion kurtosis (Kapp). The ability to discriminate between cancer and healthy breast tissue was assessed by the false-positive rate given a sensitivity of 80% (FPR80) and ROC AUC. Results: Mean FPR80 for both datasets was 0.016 [95% confidence interval (CI), 0.008–0.024] for C1C2, 0.136 (95% CI, 0.092–0.180) for C1, 0.068 (95% CI, 0.049–0.087) for C2, 0.462 (95% CI, 0.425–0.499) for F1F2, 0.832 (95% CI, 0.797–0.868) for F1, 0.176 (95% CI, 0.150–0.203) for F2, 0.159 (95% CI, 0.114–0.204) for DWImax, 0.731 (95% CI, 0.692–0.770) for ADC, and 0.684 (95% CI, 0.660–0.709) for Kapp. Mean ROC AUC for C1C2 was 0.984 (95% CI, 0.977–0.991). Conclusions: The C1C2 parameter of the three-component model yields a clinically useful discrimination between cancer and healthy breast tissue, superior to other DW-MRI methods and obliviating predefining lesions. This novel DW-MRI method may serve as noncontrast alternative to standard-of-care dynamic contrast-enhanced MRI.

BACKGROUND Multicompartmental modeling outperforms conventional diffusion-weighted imaging (DWI) in the assessment of prostate cancer. Optimized multicompartmental models could further improve the detection and characterization of prostate cancer. PURPOSE To optimize multicompartmental signal models and apply them to study diffusion in normal and cancerous prostate tissue in vivo. STUDY TYPE Retrospective. SUBJECTS Forty-six patients who underwent MRI examination for suspected prostate cancer; 23 had prostate cancer and 23 had no detectable cancer. FIELD STRENGTH/SEQUENCE 3T multishell diffusion-weighted sequence. ASSESSMENT Multicompartmental models with 2-5 tissue compartments were fit to DWI data from the prostate to determine optimal compartmental apparent diffusion coefficients (ADCs). These ADCs were used to compute signal contributions from the different compartments. The Bayesian Information Criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness-of-fit. Tumor contrast-to-noise ratio (CNR) and tumor-to-background signal intensity ratio (SIR) were computed for conventional DWI and multicompartmental signal-contribution maps. STATISTICAL TESTS Analysis of variance (ANOVA) and two-sample t-tests (α = 0.05) were used to compare fitting residuals between prostate regions and between multicompartmental models. T-tests (α = 0.05) were also used to assess differences in compartmental signal-fraction between tissue types and CNR/SIR between conventional DWI and multicompartmental models. RESULTS The lowest BIC was observed from the 4-compartment model, with optimal ADCs of 5.2e-4, 1.9e-3, 3.0e-3, and >3.0e-2 mm2 /sec. Fitting residuals from multicompartmental models were significantly lower than from conventional ADC mapping (P

Objectives We hypothesized that: (1) fetal frontal horn (FH) morphology and their proximity to the cavum septi pellucidi (CSP) can assist in suspecting complete agenesis of the corpus callosum (cACC) and partial agenesis of the corpus callosum (pACC) earlier than known indirect ultrasound (US) findings; (2) FHs assist in differentiating a true CSP from a pseudocavum; and (3) magnetic resonance imaging (MRI) is useful in learning FH morphology and pseudocavum etiology. Methods Thirty-two patients with cACC and 9 with pACC were identified on an Institutional Review Board-approved retrospective review. Of the 41 cases, 40 had prenatal US, and 21 had prenatal MRI; 17 had follow-up neonatal US, and 14 had follow-up neonatal MRI. Variables evaluated retrospectively were the presence of a CSP or a pseudocavum, ventricle size and shape, and FH shape (comma, trident, parallel, golf club, enlarged, or fused). Displacement between the inferior edge of the FH and the midline or cavum/pseudocavum was measured. Results Fetal FHs had an abnormal shape in 77% ≤20 weeks' gestation, 86% ≤24 weeks, and 90% >24 weeks. Frontal horns were laterally displaced greater than 2 mm in 85% ≤20 weeks, 91% ≤24 weeks, and 95% >24 weeks. The CSP was absent in 100% of cACC cases and 78% of pACC cases, and a pseudocavum was present in 88% of cACC cases and 78% of pACC cases across gestation. Magnetic resonance imaging confirmed US pseudocavums to be focal interhemispheric fluid or an elevated/dilated third ventricle. Conclusions Frontal horns assist in assessing ACC ≤24 weeks and throughout gestation. Pseudocavums, often simulating CSPs, are common in ACC. Frontal horn lateral displacement and abnormal morphology, recognized by MRI correlations, are helpful in differentiating a pseudocavum from a true CSP. A normal CSP should not be cleared on screening US unless normally shaped FHs are seen directly adjacent to it.

This report presents a case of necrotizing pancreatitis resulting in a large hepatic subcapsular hematoma that led to development of hepatic ischemia and early stages of liver failure. Following surgical decompression, liver function dramatically improved, but large areas of peripheral hepatic infarction had developed. This case demonstrates the risks of a rapidly expanding hepatic subcapsular hematoma, emphasizes the importance of recognizing and aggressively treating active bleeding, and cautions against administering anticoagulation and tissue-plasminogen activator in this clinical scenario. Keywords: Hepatic hematoma, Hepatic infarct, Necrotizing pancreatitis

Diffusion-weighted MRI (DW-MRI) offers a potential adjunct to dynamic contrast-enhanced MRI to discriminate benign from malignant breast lesions by yielding quantitative information about tissue microstructure. Multi-component modeling of the DW-MRI signal over an extended b-value range (up to 3000 s/mm2) theoretically isolates the slowly diffusing (restricted) water component in tissues. Previously, a three-component restriction spectrum imaging (RSI) model demonstrated the ability to distinguish malignant lesions from healthy breast tissue. We further evaluated the utility of this three-component model to differentiate malignant from benign lesions and healthy tissue in 12 patients with known malignancy and synchronous pathology-proven benign lesions. The signal contributions from three distinct diffusion compartments were measured to generate parametric maps corresponding to diffusivity on a voxel-wise basis. The three-component model discriminated malignant from benign and healthy tissue, particularly using the restricted diffusion C1 compartment and product of the restricted and intermediate diffusion compartments (C1 and C2). However, benign lesions and healthy tissue did not significantly differ in diffusion characteristics. Quantitative discrimination of these three tissue types (malignant, benign, and healthy) in non-pre-defined lesions may enhance the clinical utility of DW-MRI in reducing excessive biopsies and aiding in surveillance and surgical evaluation without repeated exposure to gadolinium contrast.

To report the radiological features of intestinal ascariasis and to review the clinical implications of this re-emerging disease for adult population of the USA. This retrospective observational study involved 12 adult patients, whose radiological examinations disclosed unsuspected presence of ascaris in their intestinal tract. They were evaluated by computed tomography of the abdomen with oral contrast, small bowel series with barium, and magnetic resonance enterography. This series included 7 men and 5 women, who ranged in age from 19 to 72 years (mean age 48 years). The typical configuration of ascaris within the bowel loops was demonstrated on CT of the abdomen in 5 patients, small bowel examination with barium in 3, and by MR enterography in another 4 cases. Our study highlights the radiological appearances of intestinal ascariasis and the clinical implications of this resurging disease. The practicing radiologists should be aware of these findings, particularly when examining patients who have immigrated from or traveled to the endemic regions.

Background Malignancies are molecularly complex and become more resistant with each line of therapy. We hypothesized that offering matched, individualized combination therapies to patients with treatment-naïve, advanced cancers would be feasible and efficacious. Patients with newly diagnosed unresectable/metastatic, poor-prognosis cancers were enrolled in a cross-institutional prospective study. Methods A total of 145 patients were included in the study. Genomic profiling (tissue and/or circulating tumor DNA) was performed in all patients, and PD-L1 immunohistochemistry, tumor mutational burden, and microsatellite status assessment were performed in a subset of patients. We evaluated safety and outcomes: disease-control rate (stable disease for ≥ 6 months or partial or complete response), progression-free survival (PFS), and overall survival (OS). Results Seventy-six of 145 patients (52%) were treated, most commonly for non-colorectal gastrointestinal cancers, carcinomas of unknown primary, and hepatobiliary malignancies (53% women; median age, 63 years). The median number of deleterious genomic alterations per patient was 5 (range, 0–15). Fifty-four treated patients (71%) received ≥ 1 molecularly matched therapy, demonstrating the feasibility of administering molecularly matched therapy. The Matching Score, which reflects the percentage of targeted alterations, correlated linearly with progression-free survival (R2 = 0.92; P = 0.01), and high (≥ 60%) Matching Score was an independent predictor of improved disease control rate [OR 3.31 (95% CI 1.01–10.83), P = 0.048], PFS [HR 0.55 (0.28–1.07), P = 0.08], and OS [HR 0.42 (0.21–0.85), P = 0.02]. Serious adverse event rates were similar in the unmatched and matched groups. Conclusions Personalized combination therapies targeting a majority of a patient’s molecular alterations have antitumor activity as first-line treatment. These findings underscore the feasibility and importance of using tailored N-of-1 combination therapies early in the course of lethal malignancies. Trial registration I-PREDICT (NCT02534675) was registered on August 25, 2015.

Introduction: Simulations based on computational musculoskeletal models are powerful tools for evaluating the effects of potential biomechanical interventions, such as implementing a novel prosthesis. However, the utility of simulations to evaluate the effects of varied prosthesis design parameters on gait mechanics has not been fully realized due to the lack of a readily-available limb loss-specific gait model and methods for efficiently modeling the energy storage and return dynamics of passive foot prostheses. The purpose of this study was to develop and validate a forward simulation-capable gait model with lower-limb loss and a semi-active variable-stiffness foot (VSF) prosthesis. Methods: A seven-segment 28-DoF gait model was developed and forward kinematics simulations, in which experimentally observed joint kinematics were applied and the resulting contact forces under the prosthesis evolved accordingly, were computed for four subjects with unilateral below-knee amputation walking with a VSF. Results: Model-predicted resultant ground reaction force (GRFR) matched well under trial-specific optimized parameter conditions (mean R2: 0.97, RMSE: 7.7% body weight (BW)) and unoptimized (subject-specific, but not trial-specific) parameter conditions (mean R2: 0.93, RMSE: 12% BW). Simulated anterior-posterior center of pressure demonstrated a mean R2 = 0.64 and RMSE = 14% foot length. Simulated kinematics remained consistent with input data (0.23 deg RMSE, R2 > 0.99) for all conditions. Conclusions: These methods may be useful for simulating gait among individuals with lower-limb loss and predicting GRFR arising from gait with novel VSF prostheses. Such data are useful to optimize prosthesis design parameters on a user-specific basis.

Burnsed-Torres, ML, Wichmann, TK, Clayton, ZS, and Hahn, ME. Comparison of the Gauntlet test with standard laboratory measures of aerobic fitness. J Strength Cond Res XX(X): 000-000, 2019-The purpose of this study was to validate whether the Gauntlet test (GT) can accurately estimate individual aerobic endurance performance compared with standard laboratory-based physiological tests. The GT required athletes to complete 5 maximal effort running stages, with a 1-minute break between each stage, with the goal of achieving the best overall time. Eighteen men (n = 9) and women (n = 9) (age, 23.5 ± 4.13 years; body mass index, 23.1 ± 7.62 kg·m; 5k time, 22 ± 7 minutes; 10k time, 47 ± 15 minutes; V[Combining Dot Above]O2max, 52.3 ± 8 ml·kg·min) completed a lactate threshold test and V[Combining Dot Above]O2max test (laboratory measures). Four to 14 days later, subjects completed the GT on an outdoor track. Blood lactate (bLa), V[Combining Dot Above]O2max, and heart rate (HR) were recorded during the laboratory session. Blood lactate, HR, stage completion time, and overall completion time were recorded during the GT. Linear regression correlation analyses revealed a significant inverse association between V[Combining Dot Above]O2max (mL·kg·min) and GT completion time (r = -0.88, P < 0.0001). In addition, there were significant correlations between V[Combining Dot Above]O2max maximum HR and GT maximum HR (r = 0.89, P < 0.0001) and V[Combining Dot Above]O2max 3-minute post bLa and GT 3-minute post bLa (r = 0.63, P = 0.0029). Sex-specific analysis showed significant inverse associations between female and male GT completion time and V[Combining Dot Above]O2max (r = -0.70, P = 0.0352; r = -0.94, P < 0.0002). Bland-Altman plots were used to evaluate concordance between GT completion time, V[Combining Dot Above]O2max, maximum HR, and 3-minute post bLa. Results suggest the GT is a valid assessment to accurately estimate aerobic endurance performance similar to standard laboratory methods.

The primary footwear components of interest to improve performance are midsole material, weight, and longitudinal bending stiffness. Little is known about the effects of varied longitudinal bending...

Introduction: The current work probes the effectiveness of multimodal touch screen tablet electronic devices in conveying science, technology, engineering, and mathematics graphics via vibrations and sounds to individuals who are visually impaired (i.e., blind or low vision) and compares it with similar graphics presented in an embossed format. Method: A volunteer sample of 22 participants who are visually impaired, selected from a summer camp and local schools for blind students, were recruited for the current study. Participants were first briefly (∼30 min) trained on how to explore graphics via a multimodal touch screen tablet. They then explored six graphic types (number line, table, pie chart, bar chart, line graph, and map) displayed via embossed paper and tablet. Participants answered three content questions per graphic type following exploration. Results: Participants were only 6% more accurate when answering questions regarding an embossed graphic as opposed to a tablet graphic. A paired-samples t test indicated that this difference was not significant, t(14) = 1.91, p = .07. Follow-up analyses indicated that presentation medium did not interact with graphic type, F(5, 50) = 0.43, p = .83, nor visual ability, F(1, 13) = 0.00, p = .96. Discussion: The findings demonstrate that multimodal touch screen tablets may be comparable to embossed graphics in conveying iconographic science and mathematics content to individuals with visual impairments, regardless of the severity of impairment. The relative equivalence in response accuracy between mediums was unexpected, given that most students who participated were braille readers and had experience reading embossed graphics, whereas they were introduced to the tablet the day of testing. Implications for practitioners: This work illustrates that multimodal touch screen tablets may be an effective option for general education teachers or teachers of students with visual impairments to use in their educational practices. Currently, preparation of accessible graphics is time consuming and requires significant preparation, but such tablets provide solutions for offering “real-time” displays of these graphics for presentation in class.

Cancer treatments have evolved from indiscriminate cytotoxic agents to selective genome- and immune-targeted drugs that have transformed outcomes for some malignancies.1 Tumor complexity and heterogeneity suggest that the “precision medicine” paradigm of cancer therapy requires treatment to be personalized to the individual patient.2–6 To date, precision oncology trials have been based upon molecular matching with predetermined monotherapies.7–14 Several of these trials have been hindered by very low matching rates, often in the 5–10% range,15 and low response rates. Low matching rates may be due to the use of limited gene panels, restrictive molecular matching algorithms, lack of drug availability or the deterioration and death of end-stage patients before therapy can be implemented. We hypothesized that personalized treatment with combination therapies would improve outcomes in patients with refractory malignancies. As a first test of this concept, we implemented a cross-institutional, prospective study (I-PREDICT, NCT02534675) that used tumor DNA sequencing and timely recommendations for individualized treatment with combination therapies. We found that administration of customized multi-drug regimens was feasible, with 49% of consented patients receiving personalized treatment. Targeting of a larger fraction of identified molecular alterations, yielding a higher “matching score,” was correlated with significantly improved disease control rates, as well as longer progression-free and overall survival rates, as compared to when fewer somatic alterations were targeted. Our findings suggest that the current clinical trial paradigm for precision oncology, which pairs one driver mutation with one drug, may be optimized by treating molecularly complex and heterogeneous cancers with combinations of customized agents.

Progression of age can influence gait characteristics. Previous research has investigated lower extremity joint mechanics between young and elderly people in locomotion, however little is known about whether differences exist between young and middle age people. Ten young healthy subjects (22.8 ± 5.3 years) and ten middle age healthy subjects (50.7 ± 6.0 years) engaged in treadmill walking (from 0.8 to 2.0 m/s) and running (from 1.8 to 3.8 m/s). The middle age group had higher ankle plantar flexor moment angular impulse (p = 0.002), total support moment impulse (p = 0.016), and hip stance positive work (p = 0.029) across walking speeds. Additionally, the middle age group had higher knee flexion angle at ground contact in walking (p = 0.005) and running (p = 0.037). These findings indicate that moderate age affects changes in ankle and hip kinetic characteristics in walking, and knee kinematic patterns in both walking and running.

The forefoot functions as the base of support during late stance, rotating about the dual-axis of the metatarsophalangeal joints. Previous research has shown that joint axis definition affects estimated joint moments about the forefoot. However, little is known about how metatarsophalangeal joint center definition affects estimated joint kinetics. This study compared moments about the metatarsophalangeal joint using four different defined joint centers. There was a significant difference (p .001) in peak moments between joint center definitions, differing by up to 0.488 N-m/kg for the slow and 0.878 N-m/kg for the fast running speeds tested. Additionally, there was a significant difference (p .001) for when peak plantar flexor moment occurred during the slower running condition. The more posteriorly oriented joint centers resulted in higher moments and earlier onset of the plantar flexor moment. In addition to careful modeling of the metatarsophalangeal joint axis, it is recommended that joint center definition should be considered as well.

PurposeMultiparametric MRI (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the qualitative PI-RADS system and quantitative apparent diffusion coefficient (ADC) yield inconsistent results. An advanced Restrictrion Spectrum Imaging (RSI) model may yield a better quantitative marker for csPCa, the RSI restriction score (RSIrs). We evaluated RSIrs for patient-level detection of csPCa.Materials and MethodsRetrospective analysis of men who underwent mpMRI with RSI and prostate biopsy for suspected prostate cancer from 2017-2019. Maximum RSIrs within the prostate was assessed by area under the receiver operating characteristic curve (AUC) for discriminating csPCa (grade group ≥2) from benign or grade group 1 biopsies. Performance of RSIrs was compared to minimum ADC and PI-RADS v2-2.1via bootstrap confidence intervals and bootstrap difference (two-tailed α=0.05). We also tested whether the combination of PI-RADS and RSIrs (PI-RADS+RSIrs) was superior to PI-RADS, alone.Results151 patients met criteria for inclusion. AUC values for ADC, RSIrs, and PI-RADS were 0.50 [95% confidence interval: 0.41, 0.60], 0.76 [0.68, 0.84], and 0.78 [0.71, 0.85], respectively. RSIrs (p=0.0002) and PI-RADS (prs was comparable to that of PI-RADS (p=0.6). AUC for PI-RADS+RSIrs was 0.84 [0.77, 0.90], superior to PI-RADS or RSIrs, alone (p=0.008, p=0.009).ConclusionsRSIrs was superior to conventional ADC and comparable to (routine, clinical) PI-RADS for patient-level detection of csPCa. The combination of PI-RADS and RSIrs was superior to either alone. RSIrs is a promising quantitative marker worthy of prospective study in the setting of csPCa detection.DisclosuresMEH reports honoraria from Multimodal Imaging Services Corporation and research funding from General Electric Healthcare. AMD is a Founder of and holds equity in CorTechs Labs, Inc, and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc. and receives funding through research agreements with General Electric Healthcare. The terms of these arrangements have been reviewed and approved by the University of California San Diego in accordance with its conflict-of-interest policies. TMS reports honoraria from Multimodal Imaging Services Corporation, Varian Medical Systems, and WebMD; he has an equity interest in CorTechs Labs, Inc. and also serves on its Scientific Advisory Board. These companies might potentially benefit from the research results. The terms of this arrangement have been reviewed and approved by the University of California San Diego in accordance with its conflict-of-interest policies.

Passive energy storage and return (ESR) feet are current performance standard in lower limb prostheses. A recently developed semi-active variable-stiffness foot (VSF) prosthesis balances the simplicity of a passive ESR device with the adaptability of a powered design. The purpose of this study was to model and simulate the ESR properties of the VSF prosthesis. The ESR properties of the VSF were modeled as a lumped parameter overhung beam. The overhung length is variable, allowing the model to exhibit variable ESR stiffness. Foot-ground contact was modeled using sphere-to-plane contact models. Contact parameters were optimized to represent the geometry and dynamics of the VSF and its foam base. Static compression tests and gait were simulated. Simulation outcomes were compared to corresponding experimental data. Stiffness of the model matched that of the physical VSF (R2: 0.98, root-mean-squared error (RMSE): 1.37 N/mm). Model-predicted resultant ground reaction force (GRFR) matched well under optimized parameter conditions (R2: 0.98, RMSE: 5.3% body weight,) and unoptimized parameter conditions (R2: 0.90, mean RMSE: 13% body weight). Anterior–posterior center of pressure matched well with R2 > 0.94 and RMSE

Persons with ankle osteoarthritis (AOA) often seek surgical intervention to alleviate pain and restore function; however, recent research has yielded no superior choice between the two primary options: fusion and replacement. One factor yet to be considered is the effect of footwear on biomechanical outcomes. Comparisons of AOA biomechanics to a normative population are also sparse. The objectives of this study were to 1) determine how footwear uniquely affected gait in persons with ankle fusion and replacement, and 2) provide context for AOA biomechanics via comparisons to a healthy adult sample. Thirty-four persons with AOA performed overground walking trials barefoot and shod prior to surgical intervention, and then received either an ankle fusion (n=14) or replacement (n=20). Two and/or three years post-surgery, patients returned for gait analysis. Nineteen controls performed the same gait procedures during a single study visit. Spatiotemporal variables and peak angles, internal moments, powers, and forces were calculated to quantify gait behavior. Overall, the two surgical groups performed similarly to each other, but demonstrated marked differences from controls both pre- and post-surgery. No significant differences were detected when examining the effect of footwear. The motion of the midfoot with respect to the hindfoot and forefoot may be instrumental in gait biomechanics following an ankle fusion or replacement, and should be considered in future investigations. This article is protected by copyright. All rights reserved.

Ultrasound (US) is the first-line imaging modality when evaluating scrotal pathology. This review will examine some common pathologies that can present diagnostic and clinical ambiguity, including testicular microlithiasis, incidental non-palpable lesions, varicoceles, and testicular infarctions. This review aims to summarize the current literature and evidence-based guidelines for these entities and to describe the important sonographic features for diagnosis as well as discuss associated clinical implications. Current guidelines suggest that management for testicular microlithiasis is dependent on associated patient risk factors and the presence or absence of other findings on ultrasound. Incidental non-palpable lesions are a diagnostic and management challenge and evolving recommendations depend on the size of the lesion and other associated features. Alternatively, varicocele is a relatively straightforward entity to diagnose, but management strategies depend on the patient’s clinical symptoms and fertility status. Testicular infarctions can also have challenging diagnostic and management approaches, especially when they are segmental. In all of these testicular pathologies, patient risk factors, clinical history, and physical exam are important factors to help guide diagnosis and management. In difficult cases, additional modalities including MRI can add to diagnostic certainty. Ultrasound plays a vital role in distinguishing multiple testicular abnormalities, including testicular microlithiasis, incidental non-palpable lesions, varicoceles, and testicular infarctions. This review summarizes the current literature as well as the available evidence-based guidelines to help define the strength and limitations of US. This review helps delineate the indications for follow-up ultrasound, the salient patient risk factors and clinical findings, and the role of other imaging modalities to increase diagnostic accuracy. This review will assist the radiologist in better identifying and managing these testicular abnormalities, and, in some cases, reduce the number of unnecessary radical orchiectomies.

Background Stress fractures are injuries caused by repetitive loading during activities such as running. The application of advanced analytical methods such as machine learning to data from multiple wearable sensors has allowed for predictions of biomechanical variables associated with running-related injuries like stress fractures. However, it is unclear if data from a single wearable sensor can accurately estimate variables that characterize external loading during running such as peak vertical ground reaction force (vGRF), vertical impulse, and ground contact time. Predicting these biomechanical variables with a single wearable sensor could allow researchers, clinicians, and coaches to longitudinally monitor biomechanical running-related injury risk factors without expensive force-measuring equipment. Purpose We quantified the accuracy of applying quantile regression forest (QRF) and linear regression (LR) models to sacral-mounted accelerometer data to predict peak vGRF, vertical impulse, and ground contact time across a range of running speeds. Methods Thirty-seven collegiate cross country runners (24 females, 13 males) ran on a force-measuring treadmill at 3.8–5.4 m/s while wearing an accelerometer clipped posteriorly to the waistband of their running shorts. We cross-validated QRF and LR models by training them on acceleration data, running speed, step frequency, and body mass as predictor variables. Trained models were then used to predict peak vGRF, vertical impulse, and contact time. We compared predicted values to those calculated from a force-measuring treadmill on a subset of data (n = 9) withheld during model training. We quantified prediction accuracy by calculating the root mean square error (RMSE) and mean absolute percentage error (MAPE). Results The QRF model predicted peak vGRF with a RMSE of 0.150 body weights (BW) and MAPE of 4.27 ± 2.85%, predicted vertical impulse with a RMSE of 0.004 BW*s and MAPE of 0.80 ± 0.91%, and predicted contact time with a RMSE of 0.011 s and MAPE of 4.68 ± 3.00%. The LR model predicted peak vGRF with a RMSE of 0.139 BW and MAPE of 4.04 ± 2.57%, predicted vertical impulse with a RMSE of 0.002 BW*s and MAPE of 0.50 ± 0.42%, and predicted contact time with a RMSE of 0.008 s and MAPE of 3.50 ± 2.27%. There were no statistically significant differences between QRF and LR model prediction MAPE for peak vGRF (p = 0.549) or vertical impulse (p = 0.073), but the LR model’s MAPE for contact time was significantly lower than the QRF model’s MAPE (p = 0.0497). Conclusions Our findings indicate that the QRF and LR models can accurately predict peak vGRF, vertical impulse, and contact time (MAPE < 5%) from a single sacral-mounted accelerometer across a range of running speeds. These findings may be beneficial for researchers, clinicians, or coaches seeking to monitor running-related injury risk factors without force-measuring equipment.

PurposeDiffusion MRI is integral to detection of prostate cancer (PCa), but conventional ADC cannot capture the complexity of prostate tissues. A four-compartment restriction spectrum imaging (RSI4) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI4-C1, yielded greatest tumor conspicuity. In this study, RSI4-C1 was evaluated as a quantitative voxel-level classifier of PCa.MethodsThis was a retrospective analysis of 46 men who underwent an expanded-acquisition pelvic MRI for suspected PCa. Twenty-three men had no detectable cancer on biopsy or clinical follow-up; the other 23 had biopsy-proven PCa corresponding to a lesion on MRI (PI-RADS category 3-5). High-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI4-C1 and conventional ADC. Voxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. Specifically, we compared RSI4-C1 and conventional ADC on mean (and 95% CI) for two metrics: area under the curve (AUC) and false-positive rate for a sensitivity of 90% (FPR90). Classifier images were also compared.ResultsRSI4-C1 outperformed conventional ADC, with greater AUC [0.977 (0.951-0.991) vs. 0.921 (0.873-0.949)] and lower FPR90 [0.033 (0.009-0.083) vs. 0.201 (0.131-0.300)].ConclusionRSI4-C1 yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection.

Item does not contain fulltext Background Prostate MRI is used widely in clinical care for guiding tissue sampling, active surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) helps provide a standardized probabilistic approach for identifying clinically significant prostate cancer. Despite widespread use, the variability in performance of prostate MRI across practices remains unknown. Purpose To estimate the positive predictive value (PPV) of PI-RADS for the detection of high-grade prostate cancer across imaging centers. Materials and Methods This retrospective cross-sectional study was compliant with the HIPAA. Twenty-six centers with members in the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel submitted data from men with suspected or biopsy-proven untreated prostate cancer. MRI scans were obtained between January 2015 and April 2018. This was followed with targeted biopsy. Only men with at least one MRI lesion assigned a PI-RADS score of 2-5 were included. Outcome was prostate cancer with Gleason score (GS) greater than or equal to 3+4 (International Society of Urological Pathology grade group >/=2). A mixed-model logistic regression with institution and individuals as random effects was used to estimate overall PPVs. The variability of observed PPV of PI-RADS across imaging centers was described by using the median and interquartile range. Results The authors evaluated 3449 men (mean age, 65 years +/- 8 [standard deviation]) with 5082 lesions. Biopsy results showed 1698 cancers with GS greater than or equal to 3+4 (International Society of Urological Pathology grade group >/=2) in 2082 men. Across all centers, the estimated PPV was 35% (95% confidence interval [CI]: 27%, 43%) for a PI-RADS score greater than or equal to 3 and 49% (95% CI: 40%, 58%) for a PI-RADS score greater than or equal to 4. The interquartile ranges of PPV at these same PI-RADS score thresholds were 27%-44% and 27%-48%, respectively. Conclusion The positive predictive value of the Prostate Imaging and Reporting Data System was low and varied widely across centers. (c) RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Milot in this issue.