DXA-derived lumbar bone strain index corrected for kyphosis is associated with vertebral fractures and trabecular bone score in acromegaly.

PURPOSE: The bone strain index (BSI) is a marker of bone deformation based on a finite element analysis inferred from dual X-ray absorptiometry (DXA) scans, that has been proposed as a predictor of fractures in osteoporosis (i.e., higher BSI indicates a lower bone's resistance to loads with consequent higher risk of fractures). We aimed to investigate the association between lumbar BSI and vertebral fractures (VFs) in acromegaly. METHODS: Twenty-three patients with acromegaly (13 males, mean age 58 years; three with active disease) were evaluated for morphometric VFs, trabecular bone score (TBS), bone mineral density (BMD) and BSI at lumbar spine, the latter being corrected for the kyphosis as measured by low-dose X-ray imaging system (EOS®-2D/3D). RESULTS: Lumbar BSI was significantly higher in patients with VFs as compared to those without fractures (2.90 ± 1.46 vs. 1.78 ± 0.33, p = 0.041). BSI was inversely associated with TBS (rho -0.44; p = 0.034), without significant associations with BMD (p = 0.151), age (p = 0.500), BMI (p = 0.957), serum IGF-I (p = 0.889), duration of active disease (p = 0.434) and sex (p = 0.563). CONCLUSIONS: Lumbar BSI corrected for kyphosis could be proposed as integrated parameter of spine arthropathy and osteopathy in acromegaly helping the clinicians in identifying patients with skeletal fragility possibly predisposed to VFs.

Volume-of-Interest Aware Deep Neural Networks for Rapid Chest CT-Based COVID-19 Patient Risk Assessment.

Since December 2019, the world has been devastated by the Coronavirus Disease 2019 (COVID-19) pandemic. Emergency Departments have been experiencing situations of urgency where clinical experts, without long experience and mature means in the fight against COVID-19, have to rapidly decide the most proper patient treatment. In this context, we introduce an artificially intelligent tool for effective and efficient Computed Tomography (CT)-based risk assessment to improve treatment and patient care. In this paper, we introduce a data-driven approach built on top of volume-of-interest aware deep neural networks for automatic COVID-19 patient risk assessment (discharged, hospitalized, intensive care unit) based on lung infection quantization through segmentation and, subsequently, CT classification. We tackle the high and varying dimensionality of the CT input by detecting and analyzing only a sub-volume of the CT, the Volume-of-Interest (VoI). Differently from recent strategies that consider infected CT slices without requiring any spatial coherency between them, or use the whole lung volume by applying abrupt and lossy volume down-sampling, we assess only the "most infected volume" composed of slices at its original spatial resolution. To achieve the above, we create, present and publish a new labeled and annotated CT dataset with 626 CT samples from COVID-19 patients. The comparison against such strategies proves the effectiveness of our VoI-based approach. We achieve remarkable performance on patient risk assessment evaluated on balanced data by reaching 88.88%, 89.77%, 94.73% and 88.88% accuracy, sensitivity, specificity and F1-score, respectively.

Vertebral Fractures Associated with Spinal Sagittal Imbalance and Quality of Life in Acromegaly: A Radiographic Study with EOS 2D/3D Technology.

INTRODUCTION: Acromegaly is commonly complicated by arthropathy and skeletal fragility with high risk of vertebral fractures (VFs). OBJECTIVE: This study aimed to assess whether VFs may be associated with sagittal spine deformities, arthropathy, impaired quality of life (QoL), pain, and disability. METHODS: Thirty-eight patients with acromegaly (median age: 55 years, 20 males) and 38 matched control subjects were evaluated by a low-dose sagittal and coronal planes, X-ray imaging system (EOS®-2D/3D) for morphometric VFs, radiological signs of spine arthropathy, and spine deformities (Cobb thoracic index ≥40°, pelvic incidence minus lumbar lordosis ≥10°, pelvic tilt >20°, and sagittal vertical axis ≥4 cm) determining sagittal spine imbalance. Acromegalic patients were also evaluated by questionnaires for QoL (Acromegaly QoL Questionnaire [AcroQoL] and Short Form-36 [SF-36]) and pain and disability (Western Ontario and McMaster University [WOMAC]). RESULTS: Acromegalic patients showed higher prevalence of thoracic hyperkyphosis (i.e., Cobb thoracic index ≥40°; p = 0.04) and pelvic tilt >20° (p = 0.02) than control subjects. VFs were found in 34.2% of acromegalic patients (p = 0.003 vs. control subjects), in relationship with higher prevalence of hyperkyphosis (p = 0.03), pelvic tilt >20° (p = 0.04), sagittal vertical axis ≥4 cm (p = 0.03), and moderate/severe subchondral degeneration (p = 0.01). Moreover, patients with VFs had lower AcroQoL general health (p = 0.007) and SF-36 general health (p = 0.002) scores and higher WOMAC pain (p = 0.003) and global (p = 0.009) scores than patients who did not fracture. CONCLUSIONS: In acromegaly, VFs may be associated with spine deformities and sagittal imbalance, spine arthropathy, impaired QoL, and disability.

Analysis of the Pelvic Functional Orientation in the Sagittal Plane: A Radiographic Study With EOS 2D/3D Technology.

BACKGROUND: We investigated the relationship between pelvic incidence (PI) with anterior pelvic plane angle (APPA), pelvic tilt (PT) angle, and sacral slope (SS) in standing and sitting positions to identify the best parameter expressing the pelvic functional orientation in the sagittal plane. METHODS: We enrolled 109 consecutive patients (M:F = 43:66) eligible for a primary total hip arthroplasty (THA) with an average age of 63.4 years (15-85). EOS 2D/3D radiography was performed in standing and sitting positions before THA to evaluate the functional pelvic orientation. 3D images took into account the patient-specific sagittal balance measuring APPA, PT, SS, and PI. RESULTS: In standing position, functional parameters measured 5° ± 7.1 for APPA, 11° ± 8.3 for PT, 43° ± 8.5 for SS, and 53° ± 10.9 for PI. In sitting position, they were -18° ± 10.4 for APPA, 34° ± 11.8 for PT, 20° ± 12.6 for SS, and 54° ± 10.9 for PI. There was no significant difference between men and women in terms of the functional parameters in both positions. No relationship was found between APPA and PI in both positions. SS correlated with PI in standing (r = 0.66; P < .0001; R2 = 0.44) and sitting (r = 0.51; P < .0001; R2 = 0.26). PT correlated with PI in standing (r = 0.65; P < .0001; R2 = 0.42) and sitting (r = 0.38; P < .0001; R2 = 0.14). CONCLUSION: SS shows the highest correlation with functional pelvic tilt. The study suggests that adjustments in acetabular anteversion during primary THA should be based on SS.