Fat Mass Does Not Increase the Precision Error of Trabecular Bone Score Measurements.

INTRODUCTION: Trabecular bone score (TBS) is an indirect index of trabecular microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry. Previous phantom study showed that an increase in soft tissue thickness does not affect TBS reproducibility. We investigated the effect of increasing body mass index (BMI) and waist circumference on TBS precision error on patients, compared to bone mineral density (BMD). METHODOLOGY: A population of postmenopausal Caucasian women was distributed in 3 different BMI (normal, overweight, and class I obesity), plus 2 further groups based on waist circumference diameter (≤88 cm and >88 cm, respectively). In vivo precision error was calculated on 30 consecutive subjects that were scanned 2 times, with patient repositioning, using the Hologic QDR-Discovery W densitometer. Coefficient of variation, percent least significant change, and reproducibility were calculated according to the International Society for Clinical Densitometry guidelines. RESULTS: Ninety-five women aged 66 ± 10 (mean ± standard deviation) were included. No significant differences were found both for BMD and TBS precision errors, respectively, when comparing BMI groups and waist circumference groups. BMD reproducibility ranged from 95.9% (BMI > 30 kg/m2) to 97.5% (BMI < 25 kg/m2). TBS reproducibility ranged between 95.8% (BMI = 25-29.9 kg/m2, waist circumference > 88 cm) and 96.6% (BMI < 25 kg/m2). With the exception of obese group, a significant difference was found between BMD and TBS reproducibility, being that of TBS slightly lower than BMD. A significant decrease of TBS values was found between normal and obese subjects, as well as between waist circumference groups. CONCLUSIONS: TBS precision error is not affected by BMI and waist circumference differences. TBS reproducibility showed to be slightly lower than that of BMD, but this difference was mitigated in obese patients. A negative association was found between the amount of fat mass and TBS mean values.

The Extension-Thickness-Damage (ETD) score: a pre-operative hip MR arthrography-based classification to predict type of labrum surgery.

INTRODUCTION: Hip magnetic resonance arthrography (MRA) is the pre-operative imaging modality of choice in patients with labral damage, with several classifications of labral tears having been reported based on MRA findings. Nevertheless, none of the available classification systems allows the surgeon to predict before surgery how a labral tear could be treated. Our purpose was to develop a new MRA-based scoring system of labral tears to predict before surgery the treatment option more suitable for labral tears. MATERIALS AND METHODS: Forty-seven patients (29 males and 18 females; mean age: 35.9 ± 12.4) performed hip MRA for suspicious of femoroacetabular impingement and were afterwards subjected to arthroscopic treatment. Two musculoskeletal radiologists reviewed all pre-operative examinations and provided the Extension-Thickness-Damage score for each patient, based on Extension of tear, Thickness of labrum, and type of Damage. Chondral lesions grading was based on the arthroscopic findings according to Konan classification. For statistical purposes, patients were divided into two groups, depending on the type of treatment: labral repair or debridement. Mann-Whitney U, Chi-square, receiver operator curves, and Cohen kappa statistics were used. RESULTS: 35/47 underwent repair, while 12/47 were debrided. In both groups, the median chondral damage was grade III, with no significant differences (p = 0.439). The median Extension-Thickness-Damage score in the repair group (6) was significantly lower (p < 0.001) than that in the debridement group (8). The highest diagnostic performance (area under the curve) of Extension-Thickness-Damage was 0.819. The inter-observer agreement was substantial in the evaluation of Extension (k = 0.626) and Thickness (k = 0.771), and almost perfect for Damage (k = 0.827). Higher scores of Extension and Thickness were more frequently associated with debridement (p < 0.001; p = 0.0016, respectively), with no significant differences on the basis of Damage parameter (p = 0.284). CONCLUSIONS: The MRA-based Extension-Thickness-Damage score could represent a helpful pre-operative tool, expressing the extent of the damage and its reparability before arthroscopy.

Detection and Classification of Bronchiectasis Through Convolutional Neural Networks.

PURPOSE: Bronchiectasis is a chronic disease characterized by an irreversible dilatation of bronchi leading to chronic infection, airway inflammation, and progressive lung damage. Three specific patterns of bronchiectasis are distinguished in clinical practice: cylindrical, varicose, and cystic. The predominance and the extension of the type of bronchiectasis provide important clinical information. However, characterization is often challenging and is subject to high interobserver variability. The aim of this study is to provide an automatic tool for the detection and classification of bronchiectasis through convolutional neural networks. MATERIALS AND METHODS: Two distinct approaches were adopted: (i) direct network performing a multilabel classification of 32×32 regions of interest (ROIs) into 4 classes: healthy, cylindrical, cystic, and varicose and (ii) a 2-network serial approach, where the first network performed a binary classification between normal tissue and bronchiectasis and the second one classified the ROIs containing abnormal bronchi into one of the 3 bronchiectasis typologies. Performances of the networks were compared with other architectures presented in the literature. RESULTS: Computed tomography from healthy individuals (n=9, age=47±6, FEV1%pred=109±17, FVC%pred=116±17) and bronchiectasis patients (n=21, age=59±15, FEV1%pred=74±25, FVC%pred=91±22) were collected. A total of 19,059 manually selected ROIs were used for training and testing. The serial approach provided the best results with an accuracy and F1 score average of 0.84, respectively. Slightly lower performances were observed for the direct network (accuracy=0.81 and F1 score average=0.82). On the test set, cylindrical bronchiectasis was the subtype classified with highest accuracy, while most of the misclassifications were related to the varicose pattern, mainly to the cylindrical class. CONCLUSION: The developed networks accurately detect and classify bronchiectasis disease, allowing to collect quantitative information regarding the radiologic severity and the topographical distribution of bronchiectasis subtype.

Chest X-ray findings in a large cohort of 1117 patients with SARS-CoV-2 infection: a multicenter study during COVID-19 outbreak in Italy.

To describe radiographic key patterns on Chest X-ray (CXR) in patients with SARS-CoV-2 infection, assessing the prevalence of radiographic signs of interstitial pneumonia. To evaluate pattern variation between a baseline and a follow-up CXR. 1117 patients tested positive for SARS-CoV-2 infection were retrospectively enrolled from four centers in Lombardy region. All patients underwent a CXR at presentation. Follow-up CXR was performed when clinically indicated. Two radiologists in each center reviewed images and classified them as suggestive or not for interstitial pneumonia, recording the presence of ground-glass opacity (GGO), reticular pattern or consolidation and their distribution. Pearson's χ2 test for categorical variables and McNemar test (χ2 for paired data) were performed. Patients mean age 63.3 years, 767 were males (65.5%). The main result is the large proportion of positive CXR in COVID-19 patients. Baseline CXR was positive in 940 patients (80.3%), with significant differences in age and sex distribution between patients with positive and negative CXR. 382 patients underwent a follow-up CXR. The most frequent pattern on baseline CXR was the GGO (66.1%), on follow-up was consolidation (53.4%). The most common distributions were peripheral and middle-lower lung zone. We described key-patterns and their distribution on CXR in a large cohort of COVID-19 patients: GGO was the most frequent finding on baseline CXR, while we found an increase in the proportion of lung consolidation on follow-up CXR. CXR proved to be a reliable tool in our cohort obtaining positive results in 80.3% of the baseline cases.

Reporting rotator cuff tears on magnetic resonance arthrography using the Snyder's arthroscopic classification.

AIM: To determine diagnostic performance of magnetic resonance arthrography (MRA) in evaluating rotator cuff tears (RCTs) using Snyder's classification for reporting. METHODS: One hundred and twenty-six patients (64 males, 62 females; median age 55 years) underwent shoulder MRA and arthroscopy, which represented our reference standard. Surgical arthroscopic reports were reviewed and the reported Snyder's classification was recorded. MRA examinations were evaluated by two independent radiologists (14 and 5 years' experience) using Snyder's classification system, blinded to arthroscopy. Agreement between arthroscopy and MRA on partial- and full-thickness tears was calculated, first regardless of their extent. Then, analysis took into account also the extent of the tear. Interobserver agreement was also calculated the quadratically-weighted Cohen kappa statistics. RESULTS: On arthroscopy, 71/126 patients (56%) had a full-thickness RCT. The remaining 55/126 patients (44%) had a partial-thickness RCT. Regardless of tear extent, out of 71 patients with arthroscopically-confirmed full-thickness RCTs, 66 (93%) were correctly scored by both readers. All 55 patients with arthroscopic diagnosis of partial-thickness RCT were correctly assigned as having a partial-thickness RCT at MRA by both readers. Interobserver reproducibility analysis showed total agreement between the two readers in distinguishing partial-thickness from full-thickness RCTs, regardless of tear extent (k = 1.000). With regard to tear extent, in patients in whom a complete tear was correctly diagnosed, correct tear extent was detected in 61/66 cases (92%); in the remaining 5/66 cases (8%), tear extent was underestimated. Agreement was k = 0.955. Interobserver agreement was total (k = 1.000). CONCLUSION: MRA shows high diagnostic accuracy and reproducibility in evaluating RCTs using the Snyder's classification for reporting. Snyder's classification may be adopted for routine reporting of MRA.