Citations

Abstract Background To utilize high spatial resolution reconstructions for cardiac imaging at energy‐integrating detector CT (EID)‐CT with comparable noise to similar reconstructions at photon‐counting detector (PCD)‐CT, methods to control EID‐CT image noise are needed. Supervised convolutional neural networks (CNN) have shown promise for denoising, but a challenge remains to efficiently create high‐quality and unbiased estimates of noise without access to dedicated software or proprietary information, such that natural noise texture is retained in CNN‐denoised CT images. Purpose This study aims to develop and test image‐based noise estimation methods that can be used to train a CNN model, and to evaluate denoising performance and noise texture preservation for EID‐CT coronary CT angiography (cCTA) images reconstructed with high‐resolution kernels. Methods U‐net CNN models were trained for denoising. To supervise training, noise‐only images were estimated directly from high‐resolution kernel (Bv59) reconstructed EID‐CT (HR EID‐CT) patient images using two different methods: subtraction of low‐ and high‐strength iterative reconstruction (IR); subtraction of adjacent image slices with the same IR strength. The noise estimates from these methods contain differing noise texture and anatomical information. Networks were trained and validated separately for three data sets: the training data from each of the two noise‐estimation methods, and a 50%–50% partition of training data between the two methods. The trained models were applied to two sets of testing data: CT images of a uniform water phantom to measure noise power spectra (NPS), and an independent cohort of seven patient cCTA HR EID‐CT exams. The denoised patient images were compared to standard resolution EID‐CT reconstructions (Bv40). As a low‐noise reference, patient images acquired on the same day with a PCD‐CT and reconstructed using a similar kernel as HR EID‐CT were used for comparison. Results Models trained with each noise‐image estimation method denoised the HR EID‐CT images by 74%–79% to achieve a comparable noise magnitude to the HR PCD‐CT images. The peak, average, and 10% peak frequencies of the NPS of the input images (6.08, 6.24, and 12.0 cm −1 ) were better approximated by the model trained on adjacent slice subtraction (6.56, 5.87, and 11.5 cm −1 ) than by the model trained on subtraction of low‐ and high‐IR images (4.64, 5.44, and 11.3 cm −1 ). In cCTA images, the IR subtraction model images retained anatomic structures from input images but resulted in undesirable salt‐and‐pepper noise texture and CT number bias. The model trained on adjacent slice subtraction images had more natural texture and no significant bias, but the model sometimes removed small anatomic structures. The model trained on the mixed training dataset preserved both noise texture and anatomy from the model inputs and enabled visualization of small structures seen in PCD‐CT images that were previously unresolved by EID‐CT. Conclusions The noise texture and anatomical accuracy in CT images denoised with an image‐based supervised CNN are greatly influenced by the characteristics and partitioning of training data. With higher‐resolution reconstructions and noise texture‐preserving deep learning denoising, the quality of cCTA images from EID‐CT can be enhanced to enable resolvability of subtle anatomy similar to PCD‐CT.

ABSTRACT Background Functional lumen imaging probe (FLIP) utility is established in treatment‐naïve achalasia but less clear following lower esophageal sphincter (LES) directed therapy. Methods Achalasia patients with LES directed therapy across three tertiary care centers between 2017 and 2024 with post‐treatment FLIP and timed barium esophagram (TBE) were retrospectively identified. Reduced esophagogastric junction (EGJ) opening was defined by distensibility index (DI) < 2 mm 2 /mmHg and diameter < 12 mm. Abnormal emptying on TBE was defined as column height ≥ 5 cm at 5 min and/or retained tablet. Eckardt scores ≤ 3 defined clinical response. Key Results The study included 222 patients (46% peroral endoscopic myotomy, 46% laparoscopic Heller myotomy, 8% pneumatic dilation) with a median of 1.4 years to post‐treatment TBE/FLIP. Abnormal emptying on TBE was associated with a narrower median EGJ diameter (13.2 vs. 14.8 mm, p = 0.008), a greater frequency of EGJ diameter < 12 mm (36% vs. 21%, p = 0.012), and a smaller change in EGJ diameter (+4.6 vs. +8.6 mm, p = 0.002). Abnormal emptying on TBE occurred more frequently in patients with EGJ DI < 2 mm 2 /mmHg (8.5% vs. 2.6%, p = 0.052), but was not associated with median EGJ DI (4.5 vs. 5.1 mm 2 /mmHg, p = 0.29) nor median change in EGJ DI (+2.9 vs. +3.9 mm 2 /mmHg, p = 0.25). Patients with reduced EGJ DI or EGJ diameter more often had abnormal TBE (37% vs. 22%, p = 0.012). Only the change in DI (+3.8 vs. +1.5 mm 2 /mmHg, p = 0.012) and diameter (+8.2 vs. +1.6 mm, p = 0.002) on FLIP was associated with a clinical response based on Eckardt ≤ 3. Conclusions and Inferences FLIP following achalasia therapy generally correlates with TBE, although discrepant findings are not uncommon. In particular, FLIP EGJ‐diameter has a strong association with esophageal emptying on TBE. Both TBE and FLIP have limited association with clinical response based on Eckardt, with change in DI and diameter on FLIP most strongly associated. Consequently, FLIP as part of multimodal assessment appears useful in the longitudinal follow‐up of treated achalasia.

Objectives: Examining the effect of demographics and social vulnerability on diagnosis and management of patients with vestibular and balance disorders. Design: Retrospective review of a database of patients presenting with vestibular symptoms to a multidisciplinary tertiary vestibular clinic between January and October 2021. Main outcomes included odds ratios of final diagnosis, treatment response, time to presentation by demographic variable, insurance status, residence, and social vulnerability factors according to the 2018 Centers for Disease Control Social Vulnerability Index. Results: Five hundred thirty-six patients with definitive vestibular diagnoses and treatment outcome data were included. Mean age at presentation was 60.4 ± 16.5 years. Women (n = 389, 72.6%) outnumbered men (n = 147, 27.4%). Most patients self-identified as White (n = 440, 82.1%) and non-Hispanic (n = 521, 97.2%). Overall, 17.4% of participants belonged to a minority group. Socioeconomic status, household composition, geographic location, and insurance status were associated with patient diagnoses received. Patients from the lowest socioeconomic class were more likely to be diagnosed with Meniere’s disease. In addition, patients with private insurance were more likely to be diagnosed with Meniere disease or vestibular migraine than those with Medicare insurance. Geographic distance greater than 60 miles from the clinic was associated with a higher likelihood to present >90 days since initial symptom onset. Housing and transportation vulnerabilities were associated with decreased treatment response. Conclusions: Diagnostic classification, time to presentation, and treatment outcomes differed according to demographic and social vulnerability factors. There was no single unifying theme among vulnerabilities, but the results of this study offer preliminary data to design future investigations on regional and national levels to understand and mitigate the effects of social vulnerability factors on access to specialty vestibular care and outcomes of treatment.

Abstract Aims Mitral and tricuspid regurgitation (MR and TR) are common in older adults and associated with substantial morbidity and mortality. While transthoracic echocardiography (TTE) is the diagnostic gold standard, access remains limited in many care settings. Artificial intelligence (AI)–based echocardiographic analysis may help address this diagnostic gap. Methods and results We externally validated a deep learning algorithm developed by Aisap.ai using TTE studies from the Mayo Clinic Health System (2013–23). The model analyses echocardiographic images to classify atrioventricular regurgitation severity and was evaluated against cardiologist interpretations. Performance was assessed using binary (normal–mild vs. moderate–severe) and ordinal (normal, mild, moderate, severe) classification schemes. Among 1541 eligible TTEs, the model returned predictions for 578 studies (38%). Performance analysis was limited to these cases. The MR cohort included 280 studies and the TR cohort 298. For MR, the model achieved an area under the receiver operating characteristic curve (AUC) of 0.98 [95% confidence interval (CI): 0.97–0.99], with 91% accuracy, 95% sensitivity, and 89% specificity. For TR, the AUC was 0.96 (95% CI: 0.94–0.98), with 84% accuracy, 91% sensitivity, and 80% specificity. Conclusion In cases where a prediction was generated, the model demonstrated high diagnostic performance in identifying clinically significant atrioventricular regurgitation. These findings support the feasibility of AI-assisted echocardiography in diverse populations, while underscoring the need for technical alignment between model requirements and local acquisition practices to ensure real-world applicability.

Abstract Introduction While randomized clinical trials (RCT) confirmed superiority of Mepitel film (MF) in reducing acute radiation dermatitis (ARD) compared to standard-of-care (SoC), the incremental cost difference has limited its use. A cost-effectiveness analysis (CEA) was conducted from a Canadian healthcare payer’s perspective to guide policy decisions. Methods: A decision model was constructed to perform a CEA for MF compared to SoC (moisturisers) for prevention of grade 2 or higher ARD following adjuvant hypo-fractionated whole-breast radiotherapy (RT) based on a Canadian multicentre RCT. Direct and indirect cost data were collected from two oncology centres in Canada. Quality-of-life (QoL) utility values were derived from mapping Dermatology Life Quality Index (DLQI) scores for patients with grade 2 or higher ARD at week 6 of RT to EQ-5D. A willingness-to-pay (WTF) threshold of CAD 50,000 per quality-adjusted life years (QALY) gained was used. One-way sensitivity analysis was performed to account for uncertainty in decision model assumptions. Results: Base case analysis demonstrated that MF is cost-effective in preventing grade 2 or higher ARD as compared with SoC with an incremental cost-effectiveness ratio (ICER) of CAD 3,366 per QALY gained. When nursing costs were included, MF resulted in an ICER of CAD 2,823 per QALY gained. One-way sensitivity analysis showed that the results were most sensitive to the QoL utility value for ARD. All sensitivity variations remained well below the WTP threshold. Conclusions: MF is a cost-effective intervention for preventing high-grade ARD and should be recommended for patients with breast cancer undergoing adjuvant RT.

ABSTRACTObjectivesThyroglossal duct cyst (TGDC) associated carcinoma is rare, accounting for less than 2% of TGDC cases. The majority of cases are classified as papillary thyroid carcinoma (PTC). Standard treatment for TGDC‐PTC involves a Sistrunk procedure and prophylactic total thyroidectomy (TT). However, the necessity of these extensive surgical interventions remains debated. This report aims to explore whether individualized surgical approaches may reduce morbidity while maintaining favorable oncological outcomes.MethodsRetrospective case series of three patients with TGDC‐PTC.ResultsThe age range at presentation for our patients with TGDC‐PTC was 26 to 50. Case 1 involved a 38‐year‐old patient with a cystic mass near the hyoid bone and submental lymphadenopathy who underwent cyst excision with level Ia lymph node clearance. Case 2 is of a 50‐year‐old patient with a history of TGDC‐PTC who presented with a recurrent neck mass 9 years after the initial surgery and underwent a revision Sistrunk procedure. Case 3 presents a 26‐year‐old patient with a large TGDC and a benign thyroid nodule who underwent a Sistrunk procedure. All three patients had PTC confirmed by final pathology. All had no evidence of recurrent disease at follow‐up evaluations ranging from 1 to 12 years.ConclusionThis case series demonstrates the feasibility and safety of individualized surgical management for TGDC‐PTC. Risk stratification allowed for tailored interventions and avoided overly aggressive approaches. Further studies are needed to establish definitive guidelines for managing TGDC‐PTC, particularly in low‐risk patients.Level of Evidence4.

Abstract Anaplastic large cell lymphoma (ALCL) cases were discussed at the 2023 Society of Hematopathology/European Association for Haematopathology workshop held on November 9-11, 2023, in Houston, Texas. This session focused on the clinical and pathologic spectrum of 3 types of ALCL: anaplastic lymphoma kinase (ALK)-positive, ALK-negative, and breast implant associated (BIA). Cases of primary cutaneous ALCL were excluded because they were included in another session. Although the diagnosis of ALCL is often straightforward, the 42 submitted cases encompassed unusual clinical presentations, morphologic variants, and atypical immunophenotypes, exemplifying potential difficulties and challenges in establishing the diagnosis of ALCL. Distinguishing ALCL from CD30-positive peripheral T-cell lymphoma, not otherwise specified, or classic Hodgkin lymphoma was discussed. In patients with a previous history of mycosis fungoides and other T-cell lymphoma/leukemia, the differential diagnosis of a CD30-positive T-cell lymphoma mimicking ALCL (mycosis fungoides transformation vs de novo ALCL) was also discussed. In patients with suspected BIA-ALCL, it is critical to properly handle the periprosthetic fluid when the disease first presents and the capsule at the time of initial capsulectomy to make a correct diagnosis and pathologic staging because a missed diagnosis may lead to disease progression. Comprehensive immunohistochemical analysis; fluorescence in situ hybridization for DUSP22, TP63, or JAK2 rearrangement; assessment of clonality of the T-cell receptor and immunoglobulin genes; and sequencing for mutations were performed as part of the workup of the submitted cases, particularly on ALK-negative ALCL cases, emphasizing the importance of ancillary testing in establishing the diagnosis.

Overtraining syndrome (OTS) is a significant medical condition observed predominantly in endurance athletes and characterised by a decline in performance and disruptions in multiple physiological functions. Given the increasing popularity of endurance training and the complex nature of OTS diagnosis, there is a compelling need for comprehensive case studies. The case series summarises one professional runner, one competitive runner and one recreational runner who were diagnosed with OTS. Key parameters observed include symptoms, diagnostic journey, recovery initiatives and return-to-sport outcomes. All three athletes showed typical OTS manifestations, including impaired performance and multisystem dysfunction (ie, endocrine, nervous, immune and gastrointestinal systems). Following a mandated cessation from training, active recovery strategies were instituted. Two of the three athletes successfully returned to competition. Specific recovery patterns and potential relapse indicators were also identified. The comprehensive examination of the cases underscores the complex nature of OTS diagnosis, its multifaceted symptoms and the critical importance of structured recovery. The case series elucidates the importance of heightened awareness and early intervention to diagnose and manage OTS. In addition, we propose an anecdotal Return to Running Protocol individualised to the athlete’s response.