Citations

Background/Objectives: Lung cancer is a devastating disease with the highest mortality rate among cancer types. Over 60% of non-small cell lung cancer (NSCLC) patients, accounting for 87% of lung cancer diagnoses, require radiation therapy. Rapid treatment initiation significantly increases the patient’s survival rate and reduces the mortality rate. Accurate tumor segmentation is a critical step in diagnosing and treating NSCLC. Manual segmentation is time- and labor-consuming and causes delays in treatment initiation. Although many lung nodule detection methods, including deep learning-based models, have been proposed. Most of these methods still have a long-standing problem of high false positives (FPs). Methods: Here, we developed an electronic health record (EHR)-guided lung tumor auto-segmentation called EXACT-Net (EHR-enhanced eXACtitude in Tumor segmentation), where the extracted information from EHRs using a pre-trained large language model (LLM) was used to remove the FPs and keep the TP nodules only. Results: The auto-segmentation model was trained on NSCLC patients’ computed tomography (CT), and the pre-trained LLM was used with the zero-shot learning approach. Our approach resulted in a 250% boost in successful nodule detection using the data from ten NSCLC patients treated in our institution. Conclusions: We demonstrated that combining vision-language information in EXACT-Net multi-modal AI framework greatly enhances the performance of vision only models, paving the road to multimodal AI framework for medical image processing.

Endoscopic ultrasound (EUS)-guided tissue sampling includes the techniques of fine needle aspiration (FNA) and fine needle biopsy (FNB), and both procedures have revolutionized specimen collection from the gastrointestinal tract, especially from remote/inaccessible organs. EUS-FNB has replaced FNA as the procedure of choice for tissue acquisition in solid pancreatic lesions (SPLs) across various society guidelines. FNB specimens provide a larger histological tissue core (preserving tissue architecture) with fewer needle passes, and this is extremely relevant in today’s era of precision and personalized molecular medicine. Innovations in needle tip design are constantly under development to maximize diagnostic accuracy by enhancing histological sampling capabilities. But, apart from the basic framework of the needle, various other factors play a role that influence diagnostic outcomes, namely, sampling techniques (fanning, aspiration or suction, and number of passes), collection methods, on-site evaluation (rapid, macroscopic, or visual), and specimen processing. The choice taken depends strongly on the endoscopist’s preference, available resources at the disposal, and procedure objectives. Hence, in this review, we explicate in detail the concepts and available literature at our disposal on the topic of EUS-guided pancreatic tissue sampling to best guide any practicing gastroenterologist/endoscopist in a not-to-ideal set-up, which EUS-guided tissue acquisition technique is the “best” for their case to augment their diagnostic outcomes.

Muscle stem cells (MuSCs) are essential for skeletal muscle regeneration, influenced by a complex interplay of mechanical, biochemical, and molecular cues. Properties of the extracellular matrix (ECM) such as stiffness and alignment guide stem cell fate through mechanosensitive pathways, where forces like shear stress translate into biochemical signals, affecting cell behavior. Aging introduces senescence which disrupts the MuSC niche, leading to reduced regenerative capacity via epigenetic alterations and metabolic shifts. Transplantation further challenges MuSC viability, often resulting in fibrosis driven by dysregulated fibro-adipogenic progenitors (FAPs). Addressing these issues, scaffold designs integrated with pharmacotherapy emulate ECM environments, providing cues that enhance graft functionality and endurance. These scaffolds facilitate the synergy between mechanotransduction and intracellular signaling, optimizing MuSC proliferation and differentiation. Innovations utilizing human pluripotent stem cell-derived myogenic progenitors and exosome-mediated delivery exploit bioactive properties for targeted repair. Additionally, 3D-printed and electrospun scaffolds with adjustable biomechanical traits tackle scalability in treating volumetric muscle loss. Advanced techniques like single-cell RNA sequencing and high-resolution imaging unravel muscle repair mechanisms, offering precise mapping of cellular interactions. Collectively, this interdisciplinary approach fortifies tissue graft durability and MuSC maintenance, propelling therapeutic strategies for muscle injuries and degenerative diseases.

Background Migraine is associated with obesity. These analyses evaluated weight change with atogepant used as a preventive migraine treatment. Methods Five atogepant clinical trials in adults with migraine (one phase 2b/3; four phase 3) were included: Three 12-week, randomized, placebo-controlled trials (episodic migraine: two; chronic migraine: one); one 40-week, open-label extension trial and one 52-week, standard care, randomized, long-term safety trial in episodic migraine. Change from baseline in body weight was measured. Results Mean baseline body mass indexes were 30.0–30.7 kg/m 2 (pooled episodic migraine [United States only]) and 25.0–25.5 kg/m 2 (chronic migraine [East Asia, Europe, and North America]). More participants treated with atogepant 60 mg once-daily compared to placebo experienced ≥7% weight loss at any time in the pooled episodic migraine placebo-controlled trials (4.9% vs. 2.8%), chronic migraine placebo-controlled trial (5.8% vs. 2.0%), and pooled open-label extension and long-term safety trials (24.0% vs.14.7% in standard care [long-term safety only]). In the placebo-controlled trials, weight loss with atogepant 60 mg once-daily was observed at week 2 (pooled episodic migraine: −0.32%; chronic migraine: −0.39%), increasing at week 12 (pooled episodic migraine: −1.02%; chronic migraine: −1.50%); compared to weight gain with placebo at week 12 (pooled episodic migraine: +0.49%; chronic migraine: +0.10%). In the long-term episodic migraine studies, weight loss with atogepant 60 mg once-daily was observed at week 4 (long-term safety: −0.42%; open-label extension: −0.76%), increasing at week 40 (long-term safety: −2.38%; open-label extension: −2.09%). Conclusion Atogepant was associated with modest dose- and duration-dependent weight loss. Trial registration ClinicalTrials.gov identifiers: NCT02848326 (CGP-MD-01); NCT03777059 (3101-301-002); NCT03700320 (long-term safety trial); NCT03939312 (open-label extension trial); NCT03855137 (3101-303-002).

Objective To assess the quality of nasopharyngoscopy video recordings used for velopharyngeal insufficiency (VPI) surgical planning and identify factors that limit evaluation of velopharyngeal closure. Design Prospective observational study. Setting Metropolitan-based hospitals with craniofacial clinics in the United States and Canada. Participants One-hundred and forty-two (142) patients with VPI across 10 hospitals. Assessment(s) Nasopharyngoscopy video recordings used for VPI surgical planning . Main Outcome Measure(s) Ratability of nasopharyngoscopy video recordings, with “ratable” defined as the video (1) visualized the velum, lateral pharyngeal wall, and posterior pharyngeal walls at some point during speech production and (2) contained an oral speech sample at the phrase level or above. Results One-hundred and forty-two (142) nasopharyngoscopy video recordings were obtained from patients undergoing VPI evaluation, of which 59.9% (n=85) were ratable. A multilevel logistic regression model was used to identify factors that influenced the quality of nasopharyngoscopy video recordings. Factors associated with unratable nasopharyngoscopy videos were age ( P =.030), sex ( P =.005*), type of scope camera used ( P =.039), presence of compensatory misarticulations ( P =.008), and a limited speech sample ( P =.040). Conclusions A substantial proportion of nasopharyngoscopy video recordings obtained during VPI evaluation are not sufficient for rating velopharyngeal closure. Lack of ratability could impact the surgery selected to treat VPI. Younger patients, those with limited speech samples, or patients with extensive compensatory articulations may be more successful in completing other VPI imaging techniques, such as videofluoroscopy or magnetic resonance imaging.

We present a case study of neotricuspidization of the aortic valve with neocusp suturing based on templates similar to those used in the Ozaki procedure but adapted for infants. This is an alternative for patients when valve reconstruction is impossible or risky. A good postoperative hemodynamic outcome was obtained, but it is necessary to evaluate this approach on the basis of long-term results.

Abstract Objectives Diagnostic reconciliation is the collaborative process between patients and clinicians to create and reconcile evidence-based, feasible, and desirable care plans. However, the specific components of this process remain unclear. The objective of this study was to develop the first comprehensive framework to elucidate the diagnostic reconciliation process. Methods We followed a multi-step and iterative approach to develop the framework, including a focused systematic review of diagnostic conversations, quantitative evaluation of recordings of real-life clinical visits recordings, and stakeholder engagement (e.g., patients, clinicians, researchers). Results We identified 17 potential components to the process of diagnostic reconciliation through literature review and stakeholder engagement. After review of 56 clinical visits and further stakeholder engagement, we developed a final framework including four categories: 1) understanding the need for a test/referral, 2) logistics of test/referral scheduling, 3) test/referral information, and 4) test/referral results. Conclusions The proposed framework lays the foundation for evaluation and improvement of diagnostic conversations in practice. Clinicians can enhance patient-centered diagnosis by co-creating diagnostic plans of care in practice and using the components described in the novel diagnostic reconciliation framework.