Risk identification for the development of large-artery vasospasm after aneurysmatic subarachnoid hemorrhage - a multivariate, risk-, and location-adjusted prediction model.

BACKGROUND: Vasospasm of the large cerebral arteries (CVS) after aneurysmatic subarachnoid hemorrhage (aSAH) reduces cerebral perfusion and causes delayed cerebral ischemia. Although endovascular spasmolysis shows convincing angiographic results, patients often do not improve in outcome. Delayed recognition of CVS contributes substantially to this effect. Therefore, this study aimed to confirm established and to identify unknown risk factors for CVS, which can be used for risk stratification. METHODS: In this monocentric, retrospective cohort study of 853 patients with aSAH, we compared demographics, clinical, and radiographic parameters at the time of aneurysm occlusion between patients who developed CVS and those who did not. Significant cohort differences were included as predictors in a multivariate analysis to address confounding. Logistic regression models were used to determine odds ratios (ORs) for the presence of CVS for each predictor. RESULTS: Of the 853 patients treated with aSAH, 304 (32%) developed CVS. In the univariable analysis, CVS was significantly associated with young age, female sex, aneurysm location, modified Fisher score, Barrow Neurological Institute (BNI) score, and surgical interventions. In the multivariable regression analysis, we identified BNI score (OR 1.33, 95% CI 1.11 to 1.58, p=0.002), decompressive craniectomy (OR 1.93, 95% CI 1.22 to 3.04, p=0.005), and aneurysm clipping (OR 2.22, 95% CI 1.50 to 3.29, p<0.001), as independent risk factors. CONCLUSIONS: Young female patients with high BNI scores who undergo surgical interventions are more likely to develop CVS and should therefore be monitored most intensively after aneurysm occlusion.

Long-term reproducibility of opportunistically assessed vertebral bone mineral density and texture features in routine clinical multi-detector computed tomography using an automated segmentation framework.

Background: To investigate reproducibility of texture features and volumetric bone mineral density (vBMD) extracted from trabecular bone in the thoracolumbar spine in routine clinical multi-detector computed tomography (MDCT) data in a single scanner environment. Methods: Patients who underwent two routine clinical thoraco-abdominal MDCT exams at a single scanner with a time interval of 6 to 26 months (n=203, 131 males; time interval mean, 13 months; median, 12 months) were included in this observational study. Exclusion criteria were metabolic and hematological disorders, bone metastases, use of bone-active medications, and history of osteoporotic vertebral fractures (VFs) or prior diagnosis of osteoporosis. A convolutional neural network (CNN)-based framework was used for automated spine labeling and segmentation (T5-L5), asynchronous Hounsfield unit (HU)-to-BMD calibration, and correction for the intravenous contrast medium phase. Vertebral vBMD and six texture features [varianceglobal, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP)] were extracted for mid- (T5-T8) and lower thoracic (T9-T12), and lumbar vertebrae (L1-L5), respectively. Relative annual changes were calculated in texture features and vBMD for each vertebral level and sorted by sex, and changes were checked for statistical significance (P<0.05) using paired t-tests. Root mean square coefficient of variation (RMSCV) and root mean square error (RMSE) were calculated as measures of variability. Results: SRE, LRE, RLN, and RP exhibited substantial reproducibility with RMSCV-values below 2%, for both sexes and at all spine levels, while vBMD was less reproducible (RMSCV =11.9-16.2%). Entropy showed highest variability (RMSCV =4.34-7.69%) due to statistically significant increases [range, mean ± standard deviation: (4.40±5.78)% to (8.36±8.66)%, P<0.001]. RMSCV of varianceglobal ranged from 1.60% to 3.03%. Conclusions: Opportunistic assessment of texture features in a single scanner environment using the presented CNN-based framework yields substantial reproducibility, outperforming vBMD reproducibility. Lowest scan-rescan variability was found for higher-order texture features. Further studies are warranted to determine, whether microarchitectural changes to the trabecular bone may be assessed through texture features.

Cost-effectiveness of opportunistic QCT-based osteoporosis screening for the prediction of incident vertebral fractures.

Objectives: Opportunistic quantitative computed tomography (oQCT) derived from non-dedicated routine CT has demonstrated high accuracy in diagnosing osteoporosis and predicting incident vertebral fractures (VFs). We aimed to investigate the cost-effectiveness of oQCT screening compared to dual-energy X-ray absorptiometry (DXA) as the standard of care for osteoporosis screening. Methods: Three screening strategies ("no osteoporosis screening", "oQCT screening", and "DXA screening") after routine CT were simulated in a state-transition model for hypothetical cohorts of 1,000 patients (women and men aged 65 years) over a follow-up period of 5 years (base case). The primary outcomes were the cumulative costs and the quality-adjusted life years (QALYs) estimated from a U.S. health care perspective for the year 2022. Cost-effectiveness was assessed based on a willingness-to-pay (WTP) threshold of $70,249 per QALY. The secondary outcome was the number of prevented VFs. Deterministic and probabilistic sensitivity analyses were conducted to test the models' robustness. Results: Compared to DXA screening, oQCT screening increased QALYs in both sexes (additional 2.40 per 1,000 women and 1.44 per 1,000 men) and resulted in total costs of $3,199,016 and $950,359 vs. $3,262,934 and $933,077 for women and men, respectively. As a secondary outcome, oQCT screening prevented 2.6 and 2.0 additional VFs per 1,000 women and men, respectively. In the probabilistic sensitivity analysis, oQCT screening remained cost-effective in 88.3% (women) and 90.0% (men) of iterations. Conclusion: oQCT screening is a cost-effective ancillary approach for osteoporosis screening and has the potential to prevent a substantial number of VFs if considered in daily clinical practice.

Diagnosis of joint invasion in patients with malignant bone tumors: value and reproducibility of direct and indirect signs on MR imaging.

OBJECTIVES: To evaluate the performance and reproducibility of MR imaging features in the diagnosis of joint invasion (JI) by malignant bone tumors. METHODS: MR images of patients with and without JI (n = 24 each), who underwent surgical resection at our institution, were read by three radiologists. Direct (intrasynovial tumor tissue (ITT), intraarticular destruction of cartilage/bone, invasion of capsular/ligamentous insertions) and indirect (tumor size, signal alterations of epiphyseal/transarticular bone (bone marrow replacement/edema-like), synovial contrast enhancement, joint effusion) signs of JI were assessed. Odds ratios, sensitivity, specificity, PPV, NPV, and reproducibilities (Cohen's and Fleiss' κ) were calculated for each feature. Moreover, the diagnostic performance of combinations of direct features was assessed. RESULTS: Forty-eight patients (28.7 ± 21.4 years, 26 men) were evaluated. All readers reliably assessed the presence of JI (sensitivity = 92-100 %; specificity = 88-100%, respectively). Best predictors for JI were direct visualization of ITT (OR = 186-229, p < 0.001) and destruction of intraarticular bone (69-324, p < 0.001). Direct visualization of ITT was also highly reliable in assessing JI (sensitivity, specificity, PPV, NPV = 92-100 %), with excellent reproducibility (κ = 0.83). Epiphyseal bone marrow replacement and synovial contrast enhancement were the most sensitive indirect signs, but lacked specificity (29-54%). By combining direct signs with high specificity, sensitivity was increased (96 %) and specificity (100 %) was maintained. CONCLUSION: JI by malignant bone tumors can reliably be assessed on preoperative MR images with high sensitivity, specificity, and reproducibility. Particularly direct visualization of ITT, destruction of intraarticular bone, and a combination of highly specific direct signs were valuable, while indirect signs were less predictive and specific. KEY POINTS: • Direct visualization of intrasynovial tumor was the single most sensitive and specific (92-100%) MR imaging sign of joint invasion. • Indirect signs of joint invasion, such as joint effusion or synovial enhancement, were less sensitive and specific compared to direct signs. • A combination of the most specific direct signs of joint invasion showed best results with perfect specificity and PPV (both 100%) and excellent sensitivity and NPV (both 96 %).

Lung nodule detection in chest X-rays using synthetic ground-truth data comparing CNN-based diagnosis to human performance.

We present a method to generate synthetic thorax radiographs with realistic nodules from CT scans, and a perfect ground truth knowledge. We evaluated the detection performance of nine radiologists and two convolutional neural networks in a reader study. Nodules were artificially inserted into the lung of a CT volume and synthetic radiographs were obtained by forward-projecting the volume. Hence, our framework allowed for a detailed evaluation of CAD systems' and radiologists' performance due to the availability of accurate ground-truth labels for nodules from synthetic data. Radiographs for network training (U-Net and RetinaNet) were generated from 855 CT scans of a public dataset. For the reader study, 201 radiographs were generated from 21 nodule-free CT scans with altering nodule positions, sizes and nodule counts of inserted nodules. Average true positive detections by nine radiologists were 248.8 nodules, 51.7 false positive predicted nodules and 121.2 false negative predicted nodules. The best performing CAD system achieved 268 true positives, 66 false positives and 102 false negatives. Corresponding weighted alternative free response operating characteristic figure-of-merits (wAFROC FOM) for the radiologists range from 0.54 to 0.87 compared to a value of 0.81 (CI 0.75-0.87) for the best performing CNN. The CNN did not perform significantly better against the combined average of the 9 readers (p = 0.49). Paramediastinal nodules accounted for most false positive and false negative detections by readers, which can be explained by the presence of more tissue in this area.

Opioid users show worse baseline knee osteoarthritis and faster progression of degenerative changes: a retrospective case-control study based on data from the Osteoarthritis Initiative (OAI).

BACKGROUND: Opioids are frequently prescribed for pain control in knee osteoarthritis patients, despite recommendations by current guidelines. Previous studies have investigated the chondrotoxicity of different opioid subtypes. However, the impact opioids may have on progression of osteoarthritis in vivo remains unknown. The aim of this study was thus to describe the associations between opioid use and knee structural changes and clinical outcomes, over 4 years. METHODS: Participants with baseline opioid use (n=181) and who continued use for ≥1 year between baseline and 4-year follow-up (n=79) were included from the Osteoarthritis Initiative cohort and frequency matched with non-users (controls) (1:2). Whole-Organ Magnetic Resonance Imaging Scores (WORMS) were obtained, including a total summation score (WORMS total, range 0-96) and subscores for cartilage (0-36), menisci (0-24), and bone marrow abnormalities and subchondral cyst-like lesions (0-18, respectively). Knee Injury Osteoarthritis Outcomes score (KOOS) symptoms, quality of life (QOL), and pain were also obtained at baseline and follow-up (range 0-100; lower scores indicate worse outcomes). Using linear regression models, associations between baseline and longitudinal findings were investigated. As pain may modify observations, a sensitivity analysis was performed for longitudinal findings. All analyses were adjusted for sex, BMI, age, race, and Kellgren-Lawrence grade. RESULTS: Opioid users had greater structural degeneration at baseline (WORMS total: Coef. [95% CI], P; 7.1 [5.5, 8.8], <0.001) and a greater increase over 4 years (4.7 [2.9, 6.5], <0.001), compared to controls. Cartilage and meniscus scores increased greater in opioid users, compared to controls (P≤0.001), and findings withstood the adjustment for baseline pain (P≤0.002). All baseline KOOS scores were lower in opioid users compared to controls (P<0.001). QOL loss was greater, when adjusted for baseline KOOS pain (QOL -6.9 [-11.6, -2.1], 0.005). CONCLUSIONS: Opioid users had worse baseline knee structural degeneration and faster progression. Opioid use was also associated with worse symptoms, pain, and QOL. Furthermore, QOL loss was greater in opioid users compared to controls, when adjusted for baseline KOOS pain, indicating that opioids may not be suited to prevent subjective disease progression in KOA patients.

Diagnostic value of fluoroscopy-guided hip aspiration for periprosthetic joint infection.

PURPOSE: To assess the value of preoperative joint aspiration in detecting periprosthetic joint infection (PJI) in patients undergoing revision hip arthroplasty and to compare these with the clinical findings, serum markers, and intraoperative findings. MATERIALS AND METHODS: Fluoroscopically guided hip aspirations in patients with pain after hip arthroplasty were retrospectively reviewed from January 2014 to December 2018. All hips underwent subsequent revision hip arthroplasty. Antibiotics were discontinued at least 2 weeks before the aspiration. The 2018 Musculoskeletal Infection Society (MSIS) criteria served as a standard of reference for PJI. Clinical, serum, synovial, and intraoperative parameters were recorded in all patients. Correlations between all parameters with PJI diagnosis were analyzed using linear and logistic regression models with ROC analysis. RESULTS: In 202 hips that included 91 septic hips, hip aspiration (AUC = 0.78) and intraoperative (0.80) parameters performed better than serum-based tests (0.64) and clinical parameters (0.68) in detecting PJI. Using MSIS criteria as a standard of reference, hip aspiration had a sensitivity of 64.0% and an accuracy of 78.5% for cultures and a sensitivity of 74.2% and an accuracy of 82.1% for synovial polymorphonuclear neutrophils% (PMN%). Results substantially improved sensitivity after excluding patients that were treated with antibiotics, particularly culture results. CONCLUSIONS: Preoperative hip aspiration showed good diagnostic performance in diagnosing PJI compared with MSIS criteria as a standard of reference. But a negative result from aspirate could not rule out PJI. Based on our findings, hip aspiration is an essential test for treatment planning in patients with pain after hip arthroplasty.

Joint-adjacent Adipose Tissue by MRI is Associated With Prevalence and Progression of Knee Degenerative Changes: Data from the Osteoarthritis Initiative.

BACKGROUND: Adipose tissue has recently gained interest as an independent imaging biomarker for osteoarthritis. PURPOSE: To explore 1) cross-sectional associations between local subcutaneous fat (SCF) thickness at the knee and the extent of degenerative changes in overweight and obese individuals and 2) associations between local fat distribution and progression of osteoarthritis over 4 years. STUDY TYPE: Retrospective cohort study. POPULATION: 338 obese and overweight participants from the Osteoarthritis Initiative cohort without radiographic evidence of osteoarthritis. FIELD STRENGTH: 3T: 3D-FLASH-WE; 3D-DESS-WE; T1w-SE; MSME. ASSESSMENT: Baseline SCF thickness was measured in standardized locations medial, lateral and anterior to the knee and the average joint-adjacent SCF (ajSCF) was calculated. Right thigh SCF cross-sectional area was assessed. Quantitative cartilage T2 relaxation times and semi-quantitative whole organ MRI scores (WORMS) were obtained at baseline and 4-year follow-up. WORMSsum was calculated as sum of cartilage, bone marrow edema, subchondral cyst, and meniscal scores. STATISTICAL TESTS: Associations of SCF measures with baseline, and 4-year change in T2 and WORMS were analyzed using regression models. SCF measurements were standardized using the equation ValueParticipant-MeanCohortStandard deviation . Analyses were adjusted for age, sex, physical activity, and BMI. RESULTS: Cross-sectionally, significant associations between lateral SCF, lateral compartment WORMS and T2 were found ( ΔWORMSsum1SDchange in lateralSCF , [95% CI]: 0.53, [0.12-0.95], P < 0.05; ΔT2 : 0.50, [0.02-0.98], P < 0.05). Moreover, greater lateral SCF was associated with faster progression of lateral WORMSsum gradings (OR = 1.50, [1.05-2.15], P < 0.05). No significant positive associations were found for thigh SCF and WORMSsum (P = 0.44) or T2 measurements (medial: P = 0.15, lateral: 0.39, patellar: P = 0.75). DATA CONCLUSION: Joint-adjacent SCF thickness was associated with imaging parameters of knee osteoarthritis, both cross-sectionally and longitudinally, while thigh SCF was not, suggesting a spatial association of SCF and knee osteoarthritis. Based on these findings, joint-adjacent SCF may play a role in the development and progression of knee osteoarthritis. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 5.

Obese and overweight individuals have greater knee synovial inflammation and associated structural and cartilage compositional degeneration: data from the osteoarthritis initiative.

OBJECTIVE: This work aims to study (i) the relationship between body mass index (BMI) and knee synovial inflammation using non-contrast-enhanced MRI and (ii) the association of synovial inflammation versus degenerative abnormalities and pain. MATERIALS AND METHODS: Subjects with risk for and mild to moderate radiographic osteoarthritis were selected from the Osteoarthritis Initiative. Subjects were grouped into three BMI categories with 87 subjects per group: normal weight (BMI, 20-24.9 kg/m2), overweight (BMI, 25-29.9 kg/m2), and obese (BMI, ≥ 30 kg/m2), frequency matched for age, sex, race, Kellgren-Lawrence grade, and history of knee surgery and injury. Semi-quantitative synovial inflammation imaging biomarkers were obtained including effusion-synovitis, size and intensity of infrapatellar fat pad signal abnormality, and synovial proliferation score. Cartilage composition was measured using T2 relaxation time and structural abnormalities using the whole-organ magnetic resonance imaging score (WORMS). The Western Ontario and McMasters (WOMAC) Osteoarthritis Index was used for pain assessment. Intra- and inter-reader reproducibility was assessed by kappa values. RESULTS: Overweight and obese groups had higher prevalence and severity of all synovial inflammatory markers (p ≤ 0.03). Positive associations were found between synovial inflammation imaging biomarkers and average T2 values, WORMS maximum scores and total WOMAC pain scores (p < 0.05). Intra- and inter-reader kappa values for imaging biomarkers were high (0.76-1.00 and 0.60-0.94, respectively). CONCLUSION: Being overweight or obese was significantly associated with a greater prevalence and severity of synovial inflammation imaging biomarkers. Substantial reproducibility and high correlation with knee structural, cartilage compositional degeneration, and WOMAC pain scores validate the synovial inflammation biomarkers used in this study.

A robust convolutional neural network for lung nodule detection in the presence of foreign bodies.

Lung cancer is a major cause of death worldwide. As early detection can improve outcome, regular screening is of great interest, especially for certain risk groups. Besides low-dose computed tomography, chest X-ray is a potential option for screening. Convolutional network (CNN) based computer aided diagnosis systems have proven their ability of identifying nodules in radiographies and thus may assist radiologists in clinical practice. Based on segmented pulmonary nodules, we trained a CNN based one-stage detector (RetinaNet) with 257 annotated radiographs and 154 additional radiographs from a public dataset. We compared the performance of the convolutional network with the performance of two radiologists by conducting a reader study with 75 cases. Furthermore, the potential use for screening on patient level and the impact of foreign bodies with respect to false-positive detections was investigated. For nodule location detection, the architecture achieved a performance of 43 true-positives, 26 false-positives and 22 false-negatives. In comparison, performance of the two readers was 42 ± 2 true-positives, 28 ± 0 false-positives and 23 ± 2 false-negatives. For the screening task, we retrieved a ROC AUC value of 0.87 for the reader study test set. We found the trained RetinaNet architecture to be only slightly prone to foreign bodies in terms of misclassifications: out of 59 additional radiographs containing foreign bodies, false-positives in two radiographs were falsely detected due to foreign bodies.

CTPA with a conventional CT at 100 kVp vs. a spectral-detector CT at 120 kVp: Comparison of radiation exposure, diagnostic performance and image quality.

PURPOSE: To compare CT pulmonary angiographies (CTPAs) as well as phantom scans obtained at 100 kVp with a conventional CT (C-CT) to virtual monochromatic images (VMI) obtained with a spectral detector CT (SD-CT) at equivalent dose levels as well as to compare the radiation exposure of both systems. MATERIAL AND METHODS: In total, 2110 patients with suspected pulmonary embolism (PE) were examined with both systems. For each system (C-CT and SD-CT), imaging data of 30 patients with the same mean CT dose index (4.85 mGy) was used for the reader study. C-CT was performed with 100 kVp and SD-CT was performed with 120 kVp; for SD-CT, virtual monochromatic images (VMI) with 40, 60 and 70 keV were calculated. All datasets were evaluated by three blinded radiologists regarding image quality, diagnostic confidence and diagnostic performance (sensitivity, specificity). Contrast-to-noise ratio (CNR) for different iodine concentrations was evaluated in a phantom study. RESULTS: CNR was significantly higher with VMI at 40 keV compared to all other datasets. Subjective image quality as well as sensitivity and specificity showed the highest values with VMI at 60 keV and 70 keV. Hereby, a significant difference to 100 kVp (C-CT) was found for image quality. The highest sensitivity was found using VMI at 60 keV with a sensitivity of more than 97 % for all localizations of PE. For diagnostic confidence and subjective contrast, highest values were found with VMI at 40 keV. CONCLUSION: Higher levels of diagnostic performance and image quality were achieved for CPTAs with SD-CT compared to C-CT given similar dose levels. In the clinical setting SD-CT may be the modality of choice as additional spectral information can be obtained.

Bone mineral density measurements derived from dual-layer spectral CT enable opportunistic screening for osteoporosis.

OBJECTIVE: To investigate the in vivo applicability of non-contrast-enhanced hydroxyapatite (HA)-specific bone mineral density (BMD) measurements based on dual-layer CT (DLCT). METHODS: A spine phantom containing three artificial vertebral bodies with known HA densities was measured to obtain spectral data using DLCT and quantitative CT (QCT), simulating different patient positions and grades of obesity. BMD was calculated from virtual monoenergetic images at 50 and 200 keV. HA-specific BMD values of 174 vertebrae in 33 patients (66 ± 18 years; 33% women) were determined in non-contrast routine DLCT and compared with corresponding QCT-based BMD values. RESULTS: Examining the phantom, HA-specific BMD measurements were on a par with QCT measurements. In vivo measurements revealed strong correlations between DLCT and QCT (r = 0.987 [95% confidence interval, 0.963-1.000]; p < 0.001) and substantial agreement in a Bland-Altman plot. CONCLUSION: DLCT-based HA-specific BMD measurements were comparable with QCT measurements in in vivo analyses. This suggests that opportunistic DLCT-based BMD measurements are an alternative to QCT, without requiring phantoms and specific protocols. KEY POINTS: • DLCT-based hydroxyapatite-specific BMD measurements show a substantial agreement with QCT-based BMD measurements in vivo. • DLCT-based hydroxyapatite-specific measurements are on a par with QCT in spine phantom measurements. • Opportunistic DLCT-based BMD measurements may be a feasible alternative for QCT, without requiring dedicated examination protocols or a phantom.