Predictive Value of Deep Learning-derived CT Pectoralis Muscle and Adipose Measurements for Incident Heart Failure: Multi-Ethnic Study of Atherosclerosis.

Purpose: To develop a deep learning algorithm capable of extracting pectoralis muscle and adipose measurements and to longitudinally investigate associations between these measurements and incident heart failure (HF) in participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Materials and Methods: MESA is a prospective study of subclinical cardiovascular disease characteristics and risk factors for progression to clinically overt disease approved by institutional review boards of six participating centers (ClinicalTrials.gov identifier: NCT00005487). All participants with adequate imaging and clinical data from the fifth examination of MESA were included in this study. Hence, in this secondary analysis, manual segmentations of 600 chest CT examinations (between the years 2010 and 2012) were used to train and validate a convolutional neural network, which subsequently extracted pectoralis muscle and adipose (intermuscular adipose tissue (IMAT), perimuscular adipose tissue (PAT), extramyocellular lipids and subcutaneous adipose tissue) area measurements from 3031 CT examinations using individualized thresholds for adipose segmentation. Next, 1781 participants without baseline HF were longitudinally investigated for associations between baseline pectoralis muscle and adipose measurements and incident HF using crude and adjusted Cox proportional hazards models. The full models were adjusted for variables in categories of demographic (age, race, sex, income), clinical/laboratory (including physical activity, BMI, and smoking), CT (coronary artery calcium score), and cardiac MRI (left ventricular ejection fraction and mass (% of predicted)) data. Results: In 1781 participants (median age, 68 (IQR,61, 75) years; 907 [51%] females), 41 incident HF events occurred over a median 6.5-year follow-up. IMAT predicted incident HF in unadjusted (hazard ratio [HR]:1.14; 95% CI: 1.03-1.26) and fully adjusted (HR:1.16, 95% CI: 1.03-1.31) models. PAT also predicted incident HF in crude (HR:1.19; 95% CI: 1.06-1.35) and fully adjusted (HR:1.25; 95% CI: 1.07-1.46) models. Conclusion: The study demonstrates that fast and reliable deep learning-derived pectoralis muscle and adipose measurements are obtainable from conventional chest CT, which may be predictive of incident HF.©RSNA, 2023.

Subchondral bone in knee osteoarthritis: bystander or treatment target?

The subchondral bone is an important structural component of the knee joint relevant for osteoarthritis (OA) incidence and progression once disease is established. Experimental studies have demonstrated that subchondral bone changes are not simply the result of altered biomechanics, i.e., pathologic loading. In fact, subchondral bone alterations have an impact on joint homeostasis leading to articular cartilage loss already early in the disease process. This narrative review aims to summarize the available and emerging imaging techniques used to evaluate knee OA-related subchondral bone changes and their potential role in clinical trials of disease-modifying OA drugs (DMOADs). Radiographic fractal signature analysis has been used to quantify OA-associated changes in subchondral texture and integrity. Cross-sectional modalities such as cone-beam computed tomography (CT), contrast-enhanced cone beam CT, and micro-CT can also provide high-resolution imaging of the subchondral trabecular morphometry. Magnetic resonance imaging (MRI) has been the most commonly used advanced imaging modality to evaluate OA-related subchondral bone changes such as bone marrow lesions and altered trabecular bone texture. Dual-energy X-ray absorptiometry can provide insight into OA-related changes in periarticular subchondral bone mineral density. Positron emission tomography, using physiological biomarkers of subchondral bone regeneration, has provided additional insight into OA pathogenesis. Finally, artificial intelligence algorithms have been developed to automate some of the above subchondral bone measurements. This paper will particularly focus on semiquantitative methods for assessing bone marrow lesions and their utility in identifying subjects at risk of symptomatic and structural OA progression, and evaluating treatment responses in DMOAD clinical trials.

Impact of immune status on the clinical characteristics, treatment outcomes and mortality of pulmonary nocardiosis: a retrospective analysis in a tertiary care hospital from a low to middle-income country.

Nocardiosis is an opportunistic infection that primarily targets the immunosuppressed. We investigate the differences in demographics and characteristics between immunosuppressed and immunocompetent patients with nocardiosis in a tertiary care hospital in Pakistan. Retrospective records were reviewed for patients diagnosed with pulmonary nocardiosis between 2010 and 2020. Immunosuppressed individuals were identified as those with autoimmune diseases, hematologic diseases and malignancies, HIV, immunosuppressant therapy, etc. Data collected included basic demographics, comorbid conditions, medication history, clinical presentation, radiological and microbiological data, and nocardiosis outcomes and complications. A total of 66 patients with nocardiosis were included in this study out of which 48 were immunosuppressed while 18 were immunocompetent. Both groups were compared for a number of variables including patient characteristics, underlying conditions, radiological findings, treatment regimen and outcomes. Immunosuppressed individuals were younger, and had higher rates of diabetes, chronic renal disease, chronic liver disease, higher platelet counts, surgical intervention, and longer hospital stays. Fever, dyspnea, and sputum production were the most common presentations. Nocardia asteroides was found to be the most common species of Nocardia overall. Nocardiosis presents differently in patients with immunosuppressed and immunocompetent patients consistent with previous studies. Nocardiosis should be considered in any patient presenting with treatment-resistant pulmonary or neurological symptoms.

Higher thyroid hormone has a negative association with lower limb lean body mass in euthyroid older adults: Analysis from the Baltimore Longitudinal study of aging.

Background: Hyperthyroidism is associated with lower lean body mass, as a result of catabolic actions of thyroid hormone. Therefore, higher thyroid hormone levels could be a factor in the development of sarcopenia and age associated functional decline. The relationship between thyroid hormone and muscle mass in ambulatory, euthyroid older adults is not known. Method: We used mixed-effects models to estimate the cross-sectional relationships (accounting for inter-person variability) between thyroid axis hormone measures and lower limb composition or sarcopenia at visits in the Baltimore Longitudinal Study of Aging (BLSA) at which DEXA scans were available and both thyrotropin (TSH) and free thyroxine (FT4) were in the reference range. Analyses were adjusted for levothyroxine use, age, race, sex, BMI, smoking, alcohol intake, cholesterol, and systolic blood pressure. Results: 1442 euthyroid participants (median age 68, 50% female, and 69% white) contributed to 5306 visits from 2003 to 2019. FT4 was negatively associated with lower limb lean mass (beta: 88.49; 95% Confidence Interval (CI): 122.78, -54.20; p < 0.001) and positively associated with sarcopenia (OR: 1.11%, 95% CI: 1.01, 1.22) in the whole cohort. Additionally, higher FT4 was associated with lower leg lean mass (beta: 66.79; 95% CI: 102.24, -31.33; p < 0.001) and sarcopenia (OR:1.09%, 95% CI:1.01, 1.18) in older adults, but not in younger adults alone. Conclusion: In euthyroid older adults, higher FT4 is associated with lower leg lean mass and higher odds of sarcopenia. Understanding the relationship between thyroid hormone and sarcopenia is needed to improve clinical decision-making and avoid functional decline from excess thyroid hormone use in older adults.

Computed Tomography: State-of-the-Art Advancements in Musculoskeletal Imaging.

ABSTRACT: Although musculoskeletal magnetic resonance imaging (MRI) plays a dominant role in characterizing abnormalities, novel computed tomography (CT) techniques have found an emerging niche in several scenarios such as trauma, gout, and the characterization of pathologic biomechanical states during motion and weight-bearing. Recent developments and advancements in the field of musculoskeletal CT include 4-dimensional, cone-beam (CB), and dual-energy (DE) CT. Four-dimensional CT has the potential to quantify biomechanical derangements of peripheral joints in different joint positions to diagnose and characterize patellofemoral instability, scapholunate ligamentous injuries, and syndesmotic injuries. Cone-beam CT provides an opportunity to image peripheral joints during weight-bearing, augmenting the diagnosis and characterization of disease processes. Emerging CBCT technologies improved spatial resolution for osseous microstructures in the quantitative analysis of osteoarthritis-related subchondral bone changes, trauma, and fracture healing. Dual-energy CT-based material decomposition visualizes and quantifies monosodium urate crystals in gout, bone marrow edema in traumatic and nontraumatic fractures, and neoplastic disease. Recently, DE techniques have been applied to CBCT, contributing to increased image quality in contrast-enhanced arthrography, bone densitometry, and bone marrow imaging. This review describes 4-dimensional CT, CBCT, and DECT advances, current logistical limitations, and prospects for each technique.