Citations

Cardiac amyloidosis (CA) is an underdiagnosed form of infiltrative cardiomyopathy caused by abnormal amyloid fibrils deposited extracellularly in the myocardium and cardiac structures. There can be high variability in its clinical manifestations, and diagnosing CA requires expertise and often thorough evaluation; as such, the diagnosis of CA can be challenging and is often delayed. The application of artificial intelligence (AI) to different diagnostic modalities is rapidly expanding and transforming cardiovascular medicine. Advanced AI methods such as deep-learning convolutional neural networks (CNNs) may enhance the diagnostic process for CA by identifying patients at higher risk and potentially expediting the diagnosis of CA. In this review, we summarize the current state of AI applications to different diagnostic modalities used for the evaluation of CA, including their diagnostic and prognostic potential, and current challenges and limitations.

Abstract Apilimod dimesylate is a first-in-class phosphoinositide kinase, FYVE-type zinc finger-containing (PIKfyve) inhibitor with a favourable clinical safety profile and has demonstrated activity in preclinical C9orf72 and TDP-43 amyotrophic lateral sclerosis (ALS) models. In this ALS clinical trial, the safety, tolerability, CNS penetrance and modulation of pharmacodynamic target engagement biomarkers were evaluated. This phase 2a, randomized, double-blind, placebo-controlled, biomarker-end-point clinical trial was conducted in four US centres (ClinicalTrials.gov NCT05163886). Participants with C9orf72 repeat expansions were randomly assigned (2:1) to receive twice-daily oral treatment with 125 mg apilimod dimesylate capsules or matching placebo for 12 weeks, followed by a 12-week open-label extension. Safety was measured as the occurrence of treatment-emergent or serious adverse events attributable to the study drug and tolerability at trial completion or treatment over 12 weeks. Changes from baseline in plasma and CSF and concentrations of apilimod dimesylate and its active metabolites and of pharmacodynamic biomarkers of PIKfyve inhibition [soluble glycoprotein nonmetastatic melanoma protein B (sGPNMB) upregulation] and disease-specific CNS target engagement [poly(GP)] were measured. Between 16 December 2021 and 7 July 2022, 15 eligible participants were enrolled. There were no drug-related serious adverse events reported in the trial. Fourteen (93%) participants completed the double-blind period with 99% dose compliance [n = 9 (90%) apilimod dimesylate; n = 5 (100%) placebo]. At Week 12, apilimod dimesylate was measurable in CSF at 1.63 ng/ml [standard deviation (SD): 0.937]. At Week 12, apilimod dimesylate increased plasma sGPNMB by >2.5-fold (P < 0.001), indicating PIKfyve inhibition, and lowered CSF poly(GP) protein levels by 73% (P < 0.001), indicating CNS tissue-level proof of mechanism. Apilimod dimesylate met prespecified key safety and biomarker end-points in this phase 2a trial and demonstrated CNS penetrance and pharmacodynamic target engagement. Apilimod dimesylate was observed to result in the greatest reduction in CSF poly(GP) levels observed to date in C9orf72 clinical trials.

The diagnosis, treatment, and management of gynecologic malignancies benefit from both positron emission tomography/computed tomography (PET/CT) and MRI. PET/CT provides important information on the local extent of disease as well as diffuse metastatic involvement. MRI offers soft tissue delineation and loco-regional disease involvement. The combination of these two technologies is key in diagnosis, treatment planning, and evaluating treatment response in gynecological malignancies. This review aims to assess the performance of PET/MRI in gynecologic cancer patients and outlines the technical challenges and clinical advantages of PET/MR systems when specifically applied to gynecologic malignancies.

Importance Among women diagnosed with primary breast cancer (BC) at or younger than age 40 years, prior data suggest that their risk of a second primary BC (SPBC) is higher than that of women who are older when they develop a first primary BC. Objective To estimate cumulative incidence and characterize risk factors of SPBC among young patients with BC. Design, Setting, and Participants Participants were enrolled in the Young Women’s Breast Cancer Study, a prospective study of 1297 women aged 40 years or younger who were diagnosed with stage 0 to III BC from August 2006 to June 2015. Demographic, genetic testing, treatment, and outcome data were collected by patient surveys and medical record review. A time-to-event analysis was used to account for competing risks when determining cumulative incidence of SPBC, and Fine-Gray subdistribution hazard models were used to evaluate associations between clinical factors and SPBC risk. Data were analyzed from January to May 2023. Main Outcomes and Measures The 5- and 10- year cumulative incidence of SPBC. Results In all, 685 women with stage 0 to III BC (mean [SD] age at primary BC diagnosis, 36 [4] years) who underwent unilateral mastectomy or lumpectomy as the primary surgery for BC were included in the analysis. Over a median (IQR) follow-up of 10.0 (7.4-12.1) years, 17 patients (2.5%) developed an SPBC; 2 of these patients had cancer in the ipsilateral breast after lumpectomy. The median (IQR) time from primary BC diagnosis to SPBC was 4.2 (3.3-5.6) years. Among 577 women who underwent genetic testing, the 10-year risk of SPBC was 2.2% for women who did not carry a pathogenic variant (12 of 544) and 8.9% for carriers of a pathogenic variant (3 of 33). In multivariate analyses, the risk of SPBC was higher among PV carriers vs noncarriers (subdistribution hazard ratio [sHR], 5.27; 95% CI, 1.43-19.43) and women with primary in situ BC vs invasive BC (sHR, 5.61; 95% CI, 1.52-20.70). Conclusions Findings of this cohort study suggest that young BC survivors without a germline pathogenic variant have a low risk of developing a SPBC in the first 10 years after diagnosis. Findings from germline genetic testing may inform treatment decision-making and follow-up care considerations in this population.

Context.— Social media is a powerful tool in pathology education and professional networking that connects pathologists and pathology trainees from around the world. Twitter (X) appears to be the most popular social media platform pathologists use to share pathology-related content and connect with other pathologists. Although there has been some published research on pathology-related activity on Twitter during short time frames, to date there has not been published research examining pathology-related Twitter activity in totality from its earliest days of activity to recently. Objective.— To comprehensively evaluate the use of pathology on Twitter (X) during the last 10 years. Design.— Pathology-related tweets were systematically scraped from Twitter from January 2012 to January 2023 using pathology hashtags as a surrogate measure for all pathology content on Twitter. COVID-related tweets were approximated by tweets containing the term “COVID.” Results.— There were 591 812 unique pathology-related tweets identified during the time period, with #pathology being the most common hashtag used and #PathTwitter becoming more popular since 2020. There has been positive annual growth of pathology Twitter, with peaks in use during major pathology conferences. During the initial phases of the COVID-19 pandemic, a sustained increase in pathology tweets was observed. Conclusions.— Pathology Twitter has grown during the last 10 years and has become increasingly popular for pathology education and networking. With the changing landscape of social media platforms, this study provides an understanding of how pathology medical education and professional networking uses of social media happen and evolve over time.

Abstract Although it is evident that standard-dose whole-brain radiotherapy as consolidation is associated with significant neurotoxicity, the optimal consolidative strategy for primary central nervous system lymphoma (PCNSL) is not defined. We performed a randomized phase 2 clinical trial via the US Alliance cancer cooperative group to compare myeloablative consolidation supported by autologous stem cell transplantation with nonmyeloablative consolidation after induction therapy for PCNSL. To our knowledge, this is the first randomized trial to be initiated that eliminates whole-brain radiotherapy as a consolidative approach in newly diagnosed PCNSL. Patients aged 18 to 75 years were randomly assigned in a 1:1 manner to induction therapy (methotrexate, temozolomide, rituximab, and cytarabine) followed by consolidation with either thiotepa plus carmustine and autologous stem cell rescue vs induction followed by nonmyeloablative, infusional etoposide plus cytarabine. The primary end point was progression-free survival (PFS). A total of 113 patients were randomized, and 108 (54 in each arm) were evaluable. More patients in the nonmyeloablative arm experienced progressive disease or death during induction (28% vs 11%; P = .05). Thirty-six patients received autologous stem cell transplant, and 34 received nonmyeloablative consolidation. The estimated 2-year PFS was higher in the myeloablative vs nonmyeloablative arm (73% vs 51%; P = .02). However, a planned secondary analysis, landmarked at start of the consolidation, revealed that the estimated 2-year PFS in those who completed consolidation therapy was not significantly different between the arms (86% vs 71%; P = .21). Both consolidative strategies yielded encouraging efficacy and similar toxicity profiles. This trial was registered at www.clininicals.gov as #NCT01511562.

Abstract Objectives Myeloproliferative neoplasm, unclassifiable (MPN-U, revised to MPN, not otherwise specified in the fifth edition of the World Health Organization classification) is a heterogeneous category of primary marrow disorders with clinical, morphologic, and/or molecular features that preclude classification as a more specific MPN subtype due to stage at diagnosis, overlapping features between MPN subtypes, or the presence of coexisting disorders. Compared with other MPN subtypes, the contribution of the mutational landscape in MPN-U in conjunction with other clinical and morphologic biomarkers to prognosis has been less well investigated. Methods We performed a multicenter, retrospective study of MPN-U (94 cases) to better define the clinicopathologic features, genetic landscape, and clinical outcomes, including subgroups of early-stage, advanced-stage, and coexisting disorders. The Dynamic International Prognostic Scoring System (DIPSS) plus scoring system was applied to assess its relevance to MPN-U prognosis. Results Multivariate analysis demonstrated bone marrow blast count and DIPSS plus score as statistically significant in predicting overall survival. Univariate analysis identified additional potential poor prognostic markers, including abnormal karyotype and absence of JAK2 mutation. Secondary mutations were frequent in the subset analyzed by next-generation sequencing (26/37 cases, 70.3%) with a borderline association between high molecular risk mutations and overall survival. Conclusions This study, as one of the largest of MPN-U studies incorporating both clinicopathologic and molecular data, moves toward identification of biomarkers that better predict prognosis in this heterogeneous category.