Citations

Background: Osteochondritis dissecans (OCD) of the knee is a focal idiopathic alteration of subchondral bone and/or its precursor with risk for instability and disruption of adjacent cartilage. Treatment options focused on preventing premature osteoarthritis vary depending on multiple patient and lesion characteristics, including lesion mobility. Purpose: To differentiate lesion mobility before arthroscopy using a multivariable model that includes patient demographic characteristics and physical examination findings. Study Design: Cohort study (Diagnosis); Level of evidence, 2. Methods: Demographic, preoperative physical examination, and radiographic data were collected from a multicenter national prospective cohort of patients with OCD of the knee. Inclusion criteria included patients <19 years of age and patients with arthroscopically confirmed mobility status based on the Research on Osteochondritis Dissecans of the Knee arthroscopy classification. Multivariable logistic regression analysis using stepwise model selection was used to determine factors associated with the likelihood of a mobile versus an immobile lesion. A 75% partition of the data was used for model training, and 25% was used as a validation cohort. Quantitative model fit statistics were computed using the holdout data, including sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC), along with the corresponding 95% CI. Results: A total of 407 patients in the prospective cohort met inclusion criteria, and 62% were male. The mean ± SD age was 13.7 ± 2.2 years, height 161.8 ± 5.3 cm, and weight 59.2 ± 42.2 kg. Arthroscopic evaluation yielded 235 immobile and 172 mobile lesions. Multivariable analysis determined that the best model to predict lesion mobility included chronologic age ≥14 years ( P < .001), effusion on physical examination ( P < .001), and any loss of range of motion on physical examination ( P = .07), while controlling for male sex ( P = .38) and weight >54.4 kg ( P = .12). In the 25% holdout validation sample (n = 102), a sensitivity of 83%, a specificity of 82%, and an AUC of 0.89 (95% CI, 0.82-0.95) were achieved with these predictive factors. Conclusion: Age, effusion, and loss of motion can predict knee OCD lesion mobility at the time of arthroscopy. Education about lesion mobility can help with surgical planning and patient and family counseling.

Abstract Task Group (TG) 314 of the American Association of Physicists in Medicine (AAPM) was charged to develop guidance for recovering from fault states in radiation therapy, specifically regarding the delivery of photon or electron beams using a linear accelerator (linac) including ancillary systems. The fault conditions addressed may involve software, hardware, or a combination of causes. The report provides detailed recommendations for the proactive steps to be taken before a fault, the actions to be taken at the time of a fault, and the safety steps before returning a linac to clinical service, as well as the activities that device manufacturers and standard organizations can do to prevent and resolve the faults. A user‐maintained log of prior faults; establishment of remote access by the vendor; and user training in emergency gantry, couch, and door motions are all useful proactive steps. At the moment of downtime and after ensuring the safety of the patient, the report stresses the importance of capturing fault information, prompt contact with the service engineer after the initial assessment, and considerations for communicating the estimated duration before the linac is returned to service. The medical physicist has a critical responsibility to assess the impact of the fault on patient care. Before resuming clinical use, the medical physicist must both determine the level of testing required to ensure safe operation of the linac and ensure any partially or totally delivered treatments have been correctly saved for accurate completion of the treatment fraction. The report stresses the roles of the radiation therapist, medical physicist, and service engineer to efficiently and safely address linac downtime. The appendices contain a description of the efforts of several organizations regarding linac safety: Integrating the Healthcare Enterprise—Radiation Oncology, International Standards Organization/International Electrotechnical Commission, Radiation Oncology Safety Stakeholder Initiative, and the AAPM Vendor Relations and Product Usability Subcommittee. Disclaimer: The recommendations of this TG should not be used to establish regulations. These recommendations are guidelines for Qualified Medical Physicists and others to use and appropriately interpret for their institution and clinical setting. Each institution may have site‐specific or state‐mandated needs and requirements which may modify their usage of these recommendations.

Background: We identified a novel, ultra-rare missense variant (p.R534S) in DENND3 as a potential disease-susceptibility variant in a multi-generational pedigree of familial idiopathic ventricular fibrillation (IVF). DENND3 is a guanine nucleotide exchange factor and activator for small GTPase Rab proteins involved in endosome and ion channel membrane trafficking. However, the role of DENND3 in the heart and its potential involvement in cardiac arrhythmias are unknown. Objective: To functionally characterize DENND3-p.R534S and determine its impact on channel trafficking. Methods: Heterologous co-expression studies in TSA201 cells were performed with DENND3-WT or DENND3-p.R534S and ion channels: KCNQ1 (Kv7.1, IKs), KCNH2 (Kv11.1, IKr), SCN5A (Nav1.5, INa), or CACNA1C (Cav1.2, ICa) as well as Rab proteins (Rab4, Rab5, Rab6, Rab7, Rab11, Rab12). Patient-specific DENND3-p.R534S iPSC-derived cardiomyocytes (iPSC-CMs) and isogenic controls (IC) were created. Localization and expression of ion channel and Rab proteins was assessed using immunofluorescence (IF) by super resolution AiryScan microscopy. GTPase-Glo assays measured Rab protein activity. Electrophysiology studies using patch-clamp and FluoVolt were performed on iPSC-CM models. Results: IF imaging showed significant increases in membrane expression of KCNQ1 (11714±157to 21929±378, p<0.05), KCNH2 (11378±160 to 31965±544, p<0.05), , SCN5A (10339±8 to 11225±23, p<0.05), and CACNA1C (11879±83 to 13749±138, p<0.05) in DENND3-p.R534S compared to DENND3-WT expressing TSA201 cells. Rab5 distribution was altered significantly by the DENND3-p.R534S variant, with increased dispersion away from the nucleus (0.23±0.01 vs. 0.17±0.01, p<0.05) and increased proximity to the plasma membrane (0.16±0.02 vs. 0.23±0.01, p<0.05). Additionally, Rab5 activity was enhanced significantly (57% increase) by p.R534S versus WT (p<0.05). iPSC-CMs revealed similar increases in channel membrane accumulation and irregular arrhythmic activity including frequent action potential duration alternans and afterdepolarizations in 78% of p.R534S iPSC-CMs versus none in IC cells (p<0.05). Conclusion: DENND3 is a novel ion channel trafficking protein in the heart. The DENND3-p.R534S variant disrupts cardiac ion channel trafficking. These findings highlight DENND3’s role in cardiac ion channel distribution, cellular function, and potential association with arrhythmogenic risk.

BackgroundMultiparametric MRI may cause overdiagnosis of clinically significant prostate cancer (csPCa) with the Prostate Imaging Reporting and Data System version 2.1 (PI‐RADS v2.1).ObjectivesTo investigate the diagnostic performance of stiffness as a standalone and complementary marker to PI‐RADS v2.1 for diagnosing csPCa.Study TypeProspective.SubjectsOne hundred forty‐seven participants with pathologically confirmed prostate lesions (≥1 cm), including 71 with csPCa.Field Strength/SequenceT1‐weighted fast spin‐echo, T2‐weighted fast spin‐echo, single‐shot echo‐planar diffusion‐weighted imaging, fast 3D gradient‐echo T1‐weighted dynamic contrast‐enhanced imaging, and 3D single‐shot spin‐echo based echo‐planar MR elastography at 3.0 T.AssessmentThe PI‐RADS v2.1 score was assessed by three radiologists independently. Lesion shear stiffness (SS) values at 60 Hz and 90 Hz were measured. A modified PI‐RADS integrating stiffness with PI‐RADS v2.1 was developed. Diagnostic performance for csPCa was compared between stiffness, PI‐RADS v2.1 and the modified PI‐RADS.Statistical TestSpearman's correlation, Fleiss κ and intraclass correlation, Pearson correlation, one‐way analysis of variance, area under the receiver operating characteristic curve (AUC), and the Delong test. Significance level was P < 0.05.ResultsIn the peripheral zone, csPCa (N = 35) had significantly higher SS than non‐csPCa at 60 Hz (3.22 ± 0.66 kPa vs. 2.56 ± 0.56 kPa) and at 90 Hz (5.64 ± 1.30 kPa vs. 4.48 ± 0.84 kPa). PI‐RADS v2.1 showed 100% sensitivity, 58% specificity, and 0.79 AUC for detecting csPCa. SS achieved 97% sensitivity, 52% specificity, and 0.80 AUC at 60 Hz, while SS had 63% sensitivity, 87% specificity, and 0.78 AUC at 90 Hz. The modified PI‐RADS, combing SS at 60 Hz with PI‐RADS v2.1, resulted in a significantly increased AUC (0.86) compared to that of PI‐RADS v2.1, with a sensitivity of 97% and specificity of 75%.Data ConclusionStiffness can help identifying csPCa in the peripheral zone. Combining stiffness with the PI‐RADS v2.1 improved the diagnostic accuracy and specificity for csPCa.Evidence Level1Technical EfficacyStage 2

Abstract Purpose: To determine the relationship between germline pathogenic variants (PV) in cancer predisposition genes and the risk of ductal carcinoma in situ (DCIS). Experimental Design: Germline PV frequencies in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, PALB2, RAD51C, and RAD51D) were compared between DCIS cases and unaffected controls and between DCIS and invasive ductal breast cancer (IDC) cases from a clinical testing cohort (n = 9,887), a population-based cohort (n = 3,876), and the UK Biobank (n = 2,421). The risk of contralateral breast cancer (CBC) for DCIS cases with PV was estimated in the population-based cohort. Results: Germline PV were observed in 6.5% and 4.6% of women with DCIS in the clinical testing and population-based cohorts, respectively. BRCA1, BRCA2, and PALB2 PV frequencies were significantly lower among women with DCIS than those with IDC (clinical cohort: 2.8% vs. 5.7%; population-based cohort: 1.7% vs. 3.7%), whereas the PV frequencies for ATM and CHEK2 were similar. ATM, BRCA1, BRCA2, CHEK2, and PALB2 PV were significantly associated with an increased risk of DCIS (OR &gt; 2.0), but only BRCA2 PV were associated with high risk (OR &gt; 4) in both cohorts. The cumulative incidence of CBC among carriers of PV in high-penetrance genes with DCIS was 23% over 15 years. Conclusions: The enrichment of PV in ATM, BRCA1, BRCA2, CHEK2, and PALB2 among women with DCIS suggests that multigene panel testing may be appropriate for women with DCIS. Elevated risks of CBC in carriers of PV in high-penetrance genes with DCIS confirmed the utility of testing for surgical decision-making.

Neuropathic pain is a debilitating chronic condition that lacks effective treatment. The role of cytokine- and chemokine-mediated neuroinflammation in its pathogenesis has been well documented. Follistatin (FST) is a secreted protein known to antagonize the biological activity of cytokines in the transforming growth factor–β (TGF-β) superfamily. The involvement of FST in neuropathic pain and the underlying mechanism remain largely unknown. Here, we report that FST was up-regulated in A-fiber sensory neurons after spinal nerve ligation (SNL) in mice. Inhibition or deletion of FST alleviated neuropathic pain and reduced the nociceptive neuron hyperexcitability induced by SNL. Conversely, intrathecal or intraplantar injection of recombinant FST, or overexpression of FST in the dorsal root ganglion (DRG) neurons, induced pain hypersensitivity. Furthermore, exogenous FST increased neuronal excitability in nociceptive neurons. The biolayer interferometry (BLI) assay and coimmunoprecipitation (co-IP) demonstrated direct binding of FST to the insulin-like growth factor–1 receptor (IGF1R), and IGF1R inhibition reduced FST-induced activation of extracellular signal–regulated kinase (ERK) and protein kinase B (AKT), as well as neuronal hyperexcitability. Further co-IP analysis revealed that the N-terminal domain of FST exhibits the highest affinity for IGF1R, and blocking this interaction with a peptide derived from FST attenuated Nav1.7-mediated neuronal hyperexcitability and neuropathic pain after SNL. In addition, FST enhanced neuronal excitability in human DRG neurons through IGF1R. Collectively, our findings suggest that FST, released from A-fiber neurons, enhances Nav1.7-mediated hyperexcitability of nociceptive neurons by binding to IGF1R, making it a potential target for neuropathic pain treatment.

Abstract Background: Breast cancer has been associated with monogenic, polygenic, and epidemiologic (clinical, reproductive, and lifestyle) risk factors, but studies evaluating the combined effects of these factors have been limited. Methods: We extended previous work in breast cancer risk modeling, incorporating pathogenic variants (PV) in six breast cancer predisposition genes and a 105-SNP polygenic risk score (PRS), to include an epidemiologic risk score (ERS) in a sample of non-Hispanic White women drawn from prospective cohorts and population-based case–control studies, with 23,518 cases and 22,832 controls, from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium. Results: The model predicts 4.4-fold higher risk of breast cancer for postmenopausal women with no predisposition PV and median PRS, but with the highest versus lowest ERS. Overall, women with CHEK2 PVs had &gt;20% lifetime risk of breast cancer. However, 15.6% of women with CHEK2 PVs and a family history of breast cancer, and 45.1% of women with CHEK2 PVs but without a family history of breast cancer, had low (&lt;20%) predicted lifetime risk and thus were below the threshold for MRI screening. CHEK2 PV carriers at the 10th percentile of the joint distribution of ERS and PRS, without a family history of breast cancer, had a predicted lifetime risk similar to the general population. Conclusions: These results illustrate that an ERS, alone and combined with the PRS, can contribute to clinically relevant risk stratification. Impact: Integrating monogenic, polygenic, and epidemiologic risk factors in breast cancer risk prediction models may inform personalized screening and prevention efforts.

Abstract Background A vast amount of potentially useful information such as description of patient symptoms, family, and social history is recorded as free-text notes in electronic health records (EHRs) but is difficult to reliably extract at scale, limiting their utility in research. This study aims to assess whether an “out of the box” implementation of open-source large language models (LLMs) without any fine-tuning can accurately extract social determinants of health (SDoH) data from free-text clinical notes. Methods We conducted a cross-sectional study using EHR data from the Mass General Brigham (MGB) system, analyzing free-text notes for SDoH information. We selected a random sample of 200 patients and manually labeled nine SDoH aspects. Eight advanced open-source LLMs were evaluated against a baseline pattern-matching model. Two human reviewers provided the manual labels, achieving 93% inter-annotator agreement. LLM performance was assessed using accuracy metrics for overall, mentioned, and non-mentioned SDoH, and macro F1 scores. Results LLMs outperformed the baseline pattern-matching approach, particularly for explicitly mentioned SDoH, achieving up to 40% higher Accuracymentioned. openchat_3.5 was the best-performing model, surpassing the baseline in overall accuracy across all nine SDoH aspects. The refined pipeline with prompt engineering reduced hallucinations and improved accuracy. Conclusions Open-source LLMs are effective and scalable tools for extracting SDoH from unstructured EHRs, surpassing traditional pattern-matching methods. Further refinement and domain-specific training could enhance their utility in clinical research and predictive analytics, improving healthcare outcomes and addressing health disparities.