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AbstractBackgroundDeformable Image Registration (DIR) is an essential technique required in many applications of radiation oncology. However, conventional DIR approaches typically take several minutes to register one pair of 3D CT images and the resulting deformable vector fields (DVFs) are only specific to the pair of images used, making it less appealing for clinical application.PurposeA deep‐learning‐based DIR method using CT images is proposed for lung cancer patients to address the common drawbacks of the conventional DIR approaches and in turn can accelerate the speed of related applications, such as contour propagation, dose deformation, adaptive radiotherapy (ART), etc.MethodsA deep neural network based on VoxelMorph was developed to generate DVFs using CT images collected from 114 lung cancer patients. Two models were trained with the weighted mean absolute error (wMAE) loss and structural similarity index matrix (SSIM) loss (optional) (i.e., the MAE model and the M+S model). In total, 192 pairs of initial CT (iCT) and verification CT (vCT) were included as a training dataset and the other independent 10 pairs of CTs were included as a testing dataset. The vCTs usually were taken 2 weeks after the iCTs. The synthetic CTs (sCTs) were generated by warping the vCTs according to the DVFs generated by the pre‐trained model. The image quality of the synthetic CTs was evaluated by measuring the similarity between the iCTs and the sCTs generated by the proposed methods and the conventional DIR approaches, respectively. Per‐voxel absolute CT‐number‐difference volume histogram (CDVH) and MAE were used as the evaluation metrics. The time to generate the sCTs was also recorded and compared quantitatively. Contours were propagated using the derived DVFs and evaluated with SSIM. Forward dose calculations were done on the sCTs and the corresponding iCTs. Dose volume histograms (DVHs) were generated based on dose distributions on both iCTs and sCTs generated by two models, respectively. The clinically relevant DVH indices were derived for comparison. The resulted dose distributions were also compared using 3D Gamma analysis with thresholds of 3 mm/3%/10% and 2 mm/2%/10%, respectively.ResultsThe two models (wMAE and M+S) achieved a speed of 263.7±163 / 265.8±190 ms and a MAE of 13.15±3.8 / 17.52±5.8 HU for the testing dataset, respectively. The average SSIM scores of 0.987±0.006 and 0.988±0.004 were achieved by the two proposed models, respectively. For both models, CDVH of a typical patient showed that less than 5% of the voxels had a per‐voxel absolute CT‐number‐difference larger than 55 HU. The dose distribution calculated based on a typical sCT showed differences of ≤2cGy[RBE] for clinical target volume (CTV) D95 and D5, within ±0.06% for total lung V5, ≤1.5cGy[RBE] for heart and esophagus Dmean, and ≤6cGy[RBE] for cord Dmax compared to the dose distribution calculated based on the iCT. The good average 3D Gamma passing rates (> 96% for 3 mm/3%/10% and > 94% for 2 mm/2%/10%, respectively) were also observed.ConclusionA deep neural network‐based DIR approach was proposed and has been shown to be reasonably accurate and efficient to register the initial CTs and verification CTs in lung cancer.

AbstractBackgroundDeep learning auto‐segmentation (DLAS) models have been adopted in the clinic; however, they suffer from performance deterioration owing to the clinical practice variability. Some commercial DLAS software provide an incremental retraining function that enables users to train a custom model using their institutional data to account for clinical practice variability.PurposeThis study was performed to evaluate and implement the commercial DLAS software with the incremental retraining function for definitive treatment of patients with prostate cancer in a multi‐user environment.MethodsCT‐based target organs and organs‐at‐risk (OAR) delineation of 215 prostate cancer patients were utilized. The performance of three commercial DLAS software built‐in models was validated with 20 patients. A retrained custom model was developed using 100 patients and evaluated on the remaining data (n = 115). Dice similarity coefficient (DSC), Hausdorff distance (HD), mean surface distance (MSD), and surface DSC (SDSC) were utilized for quantitative evaluation. A multi‐rater qualitative evaluation was blindly performed with a five‐level scale. Visual inspection was performed in consensus and non‐consensus unacceptable cases to identify the failure modes.ResultsThree commercial DLAS vendor built‐in models achieved sub‐optimal performance in 20 patients. The retrained custom model had a mean DSC of 0.82 for prostate, 0.48 for seminal vesicles (SV), and 0.92 for rectum, respectively. This represents a significant improvement over the built‐in model with DSC of 0.73, 0.37, and 0.81 for the corresponding structures. Compared to the acceptance rate of 96.5% and consensus unacceptable rate (i.e., both reviewers rated as unacceptable) of 3.5% achieved by manual contours, the custom model achieved a 91.3% acceptance rate and 8.7% consensus unacceptable rate. The failure modes of retrained custom model were attributed to the following: cystogram (n = 2), hip prosthesis (n = 2), low dose rate brachytherapy seeds (n = 2), air in endorectal balloon(n = 1), non‐iodinated spacer (n = 2), and giant bladder(n = 1).ConclusionThe commercial DLAS software with the incremental retraining function was validated and clinically adopted for prostate patients in a multi‐user environment. AI‐based auto‐delineation of the prostate and OARs is shown to achieve improved physician acceptance, overall clinical utility, and accuracy.

Objective: The purpose of this study was to describe management and outcomes from a contemporary cohort of children with Wilms tumor complicated by inferior vena caval thrombus. Background: The largest series of these patients was published almost 2 decades ago. Since then, neoadjuvant chemotherapy has been commonly used to manage these patients, and outcomes have not been reported. Methods: Retrospective review of 19 North American centers between 2009 and 2019. Patient and disease characteristics, management, and outcomes were investigated and analyzed. Results: Of 124 patients, 81% had favorable histology (FH), and 52% were stage IV. IVC thrombus level was infrahepatic in 53 (43%), intrahepatic in 32 (26%), suprahepatic in 14 (11%), and cardiac in 24 (19%). Neoadjuvant chemotherapy using a 3-drug regimen was administered in 82% and postresection radiation in 90%. Thrombus level regression was 45% overall, with suprahepatic level showing the best response (62%). Cardiopulmonary bypass (CPB) was potentially avoided in 67%. The perioperative complication rate was significantly lower after neoadjuvant chemotherapy [(25%) vs upfront surgery (55%); P=0.005]. CPB was not associated with higher complications [CPB (50%) vs no CPB (27%); P=0.08]. Two-year event-free survival was 93% and overall survival was 96%, higher in FH cases (FH 98% vs unfavorable histology/anaplastic 82%; P=0.73). Neither incomplete resection nor viable thrombus cells affected event-free survival or overall survival. Conclusions: Multimodal therapy resulted in excellent outcomes, even with advanced-stage disease and cardiac extension. Neoadjuvant chemotherapy decreased the need for CPB to facilitate resection. Complete thrombectomy may not always be necessary.

Abstract Introduction Epilepsy is frequently encountered in the pediatric population and some patients are treated by stimulation of the vagus nerve to reduce their seizure frequency. Vagus nerve stimulation (VNS) may induce central sleep apnea. Adaptive servo ventilation is a known treatment option for central sleep apnea in certain adult patients with heart failure and Cheyne-Stokes respiration but is infrequently utilized in the pediatric population. Report of case(s) A 17-year-old male with a history of intractable generalized epilepsy, VNS placement, obstructive sleep apnea (OSA) and central sleep apnea (CSA) presented to our tertiary care center for management of his sleep disordered breathing. Initial management of sleep disordered breathing included CPAP for OSA. After VNS placement, the patient began to have a high residual apnea-hypopnea index on data card download of his CPAP. Polysomnography (PSG) was performed on CPAP and CSA events were noted that correlated with VNS firing. BiPAP was titrated and was unsuccessful in treating the CSA. VNS adjustment did not impact the sleep disordered breathing. Repeat titration with adaptive servo ventilation successfully treated the OSA and CSA. In follow up, the patient is tolerating ASV with improvement in his nocturnal sleep disordered breathing events and his daytime functioning. Conclusion Central sleep apnea can be induced by vagus nerve stimulation. This unique case documents successful treatment of vagus nerve stimulation induced central sleep apnea by adaptive servo ventilation in an adolescent patient. Support (if any)

AbstractOBJECTIVEInvestigation of learning slopes in early‐onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early‐onset dementia with and without β‐amyloid positivityMETHODData from 310 participants in the Longitudinal Early‐Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determinedRESULTSWorse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric—the learning ratio (LR)—outperformed other learning slope calculations across analysesCONCLUSIONSLearning slopes appear to be sensitive to early‐onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses.Highlights Learning is impaired in amyloid‐positive EOAD, beyond cognitive severity scores alone. Amyloid‐positive EOAD participants perform worse on learning slopes than amyloid‐negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants.

The prevalence of atrial fibrillation (AF) is forecasted to increase manifold, emphasizing the need for efficacious treatments. Pulmonary vein isolation (PVI) to eliminate ectopic triggers is now established as a fundamental component of the invasive treatment of AF, however its efficacy in persistent AF remains suboptimal. The atrial myocardium undergoes adverse fibrotic remodeling as AF progresses, favoring arrhythmia initiation and maintenance. Reductions in left atrial bipolar voltage have been suggested to identify regions of such pathological remodeling, and represent novel targets for ablation to target the arrhythmogenic substrate. Early observational studies targeting these low voltage areas (LVA) have been encouraging, however results from more recent randomized trials are more mixed. Importantly, there is significant heterogeneity in the techniques for identifying LVAs and the strategies for ablation. In reality, the atrial arrhythmogenic substrate is multi-faceted rather than being limited to fibrosis and there remains uncertainty as to how accurately LVAs represent regions of fibrosis. Additionally, bipolar voltage is influenced by numerous physiological and biophysical factors. The present review summarizes the current evidence for LVA ablation in AF. We then analyze the components of the atrial arrhythmic substrate, its relationship to LVAs and the limitations in LVA assessment. Finally we discuss novel techniques for delineating the atrial substrate.

Importance Whether vigorous intensity exercise is associated with an increase in risk of ventricular arrhythmias in individuals with hypertrophic cardiomyopathy (HCM) is unknown. Objective To determine whether engagement in vigorous exercise is associated with increased risk for ventricular arrhythmias and/or mortality in individuals with HCM. The a priori hypothesis was that participants engaging in vigorous activity were not more likely to have an arrhythmic event or die than those who reported nonvigorous activity. Design, Setting, and Participants This was an investigator-initiated, prospective cohort study. Participants were enrolled from May 18, 2015, to April 25, 2019, with completion in February 28, 2022. Participants were categorized according to self-reported levels of physical activity: sedentary, moderate, or vigorous-intensity exercise. This was a multicenter, observational registry with recruitment at 42 high-volume HCM centers in the US and internationally; patients could also self-enroll through the central site. Individuals aged 8 to 60 years diagnosed with HCM or genotype positive without left ventricular hypertrophy (phenotype negative) without conditions precluding exercise were enrolled. Exposures Amount and intensity of physical activity. Main Outcomes and Measures The primary prespecified composite end point included death, resuscitated sudden cardiac arrest, arrhythmic syncope, and appropriate shock from an implantable cardioverter defibrillator. All outcome events were adjudicated by an events committee blinded to the patient’s exercise category. Results Among the 1660 total participants (mean [SD] age, 39 [15] years; 996 male [60%]), 252 (15%) were classified as sedentary, and 709 (43%) participated in moderate exercise. Among the 699 individuals (42%) who participated in vigorous-intensity exercise, 259 (37%) participated competitively. A total of 77 individuals (4.6%) reached the composite end point. These individuals included 44 (4.6%) of those classified as nonvigorous and 33 (4.7%) of those classified as vigorous, with corresponding rates of 15.3 and 15.9 per 1000 person-years, respectively. In multivariate Cox regression analysis of the primary composite end point, individuals engaging in vigorous exercise did not experience a higher rate of events compared with the nonvigorous group with an adjusted hazard ratio of 1.01. The upper 95% 1-sided confidence level was 1.48, which was below the prespecified boundary of 1.5 for noninferiority. Conclusions and Relevance Results of this cohort study suggest that among individuals with HCM or those who are genotype positive/phenotype negative and are treated in experienced centers, those exercising vigorously did not experience a higher rate of death or life-threatening arrhythmias than those exercising moderately or those who were sedentary. These data may inform discussion between the patient and their expert clinician around exercise participation.

AbstractIntroductionRemote smartphone assessments of cognition, speech/language, and motor functioning in frontotemporal dementia (FTD) could enable decentralized clinical trials and improve access to research. We studied the feasibility and acceptability of remote smartphone data collection in FTD research using the ALLFTD Mobile App (ALLFTD‐mApp).MethodsA diagnostically mixed sample of 214 participants with FTD or from familial FTD kindreds (asymptomatic: CDR®+NACC‐FTLD = 0 [N = 101]; prodromal: 0.5 [N = 49]; symptomatic ≥1 [N = 51]; not measured [N = 13]) were asked to complete ALLFTD‐mApp tests on their smartphone three times within 12 days. They completed smartphone familiarity and participation experience surveys.ResultsIt was feasible for participants to complete the ALLFTD‐mApp on their own smartphones. Participants reported high smartphone familiarity, completed ∼ 70% of tasks, and considered the time commitment acceptable (98% of respondents). Greater disease severity was associated with poorer performance across several tests.DiscussionThese findings suggest that the ALLFTD‐mApp study protocol is feasible and acceptable for remote FTD research.HIGHLIGHTS The ALLFTD Mobile App is a smartphone‐based platform for remote, self‐administered data collection. The ALLFTD Mobile App consists of a comprehensive battery of surveys and tests of executive functioning, memory, speech and language, and motor abilities. Remote digital data collection using the ALLFTD Mobile App was feasible in a multicenter research consortium that studies FTD. Data was collected in healthy controls and participants with a range of diagnoses, particularly FTD spectrum disorders. Remote digital data collection was well accepted by participants with a variety of diagnoses.

Key Points Hepatorenal syndrome type 1 (HRS-1) is an often fatal, but potentially reversible, kidney failure in patients with decompensated cirrhosis. Treatment with terlipressin in patients with HRS-1 is associated with a reduction in the need for RRT. Background Hepatorenal syndrome type 1 (HRS-1)—also known as hepatorenal syndrome-AKI (HRS-AKI)—is a rapidly progressing and usually fatal, but potentially reversible, kidney failure occurring in patients with decompensated cirrhosis. A large proportion of patients with HRS-1 require renal replacement therapy (RRT). Terlipressin demonstrated efficacy in reversing HRS and improving renal function in patients with HRS-1 in three phase III, randomized, clinical trials (RCTs; i.e. , OT-0401, REVERSE, and CONFIRM). However, these RCTs were not designed to evaluate the effect of terlipressin on the requirement of RRT. In this study, the effect of terlipressin on RRT requirements in the pooled phase III patient population was assessed. Methods For this retrospective analysis, data from patients who participated in the OT-0401, REVERSE, and CONFIRM studies were integrated in the largest-to-date randomized database ( N =608). Results The need for RRT was significantly decreased in patients in the terlipressin group versus the placebo group by day 30 (28.1% versus 35.9%, respectively; P = 0.040) and day 60 (30.1% versus 37.9%, respectively; P = 0.045) in the pooled population and also postliver transplantation (LT) at day 60 (20.5% versus 40.3%, respectively; P = 0.008) and day 90 (25.3% versus 43.1%, respectively; P = 0.018). More patients were alive and RRT-free by day 90 in the overall population (36.9% versus 28.5%; P = 0.030) and among patients who received an LT (60.0% versus 39.7%; P = 0.010). Random assignment to receive terlipressin was an independent positive predictor of avoidance of RRT ( P = 0.042); while higher baseline serum creatinine (sCr) level and Child-Pugh scores were negatively associated with RRT avoidance ( P < 0.001 and P = 0.040, respectively). Conclusions Terlipressin decreased the requirement of RRT compared with placebo among patients with HRS-1, including those receiving LT. A lower sCr level at the beginning of therapy was associated with avoidance of RRT.

ABSTRACT Most fracture risk assessment tools use clinical risk factors combined with bone mineral density (BMD) to improve assessment of osteoporosis; however, stratifying fracture risk remains challenging. This study developed a fracture risk assessment tool that uses information about volumetric bone density and three‐dimensional structure, obtained using high‐resolution peripheral quantitative compute tomography (HR‐pQCT), to provide an alternative approach for patient‐specific assessment of fracture risk. Using an international prospective cohort of older adults ( n = 6802) we developed a tool to predict osteoporotic fracture risk, called μFRAC. The model was constructed using random survival forests, and input predictors included HR‐pQCT parameters summarizing BMD and microarchitecture alongside clinical risk factors (sex, age, height, weight, and prior adulthood fracture) and femoral neck areal BMD (FN aBMD). The performance of μFRAC was compared to the Fracture Risk Assessment Tool (FRAX) and a reference model built using FN aBMD and clinical covariates. μFRAC was predictive of osteoporotic fracture (c‐index = 0.673, p < 0.001), modestly outperforming FRAX and FN aBMD models (c‐index = 0.617 and 0.636, respectively). Removal of FN aBMD and all clinical risk factors, except age, from μFRAC did not significantly impact its performance when estimating 5‐year and 10‐year fracture risk. The performance of μFRAC improved when only major osteoporotic fractures were considered (c‐index = 0.733, p < 0.001). We developed a personalized fracture risk assessment tool based on HR‐pQCT that may provide an alternative approach to current clinical methods by leveraging direct measures of bone density and structure. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).