Sex differences and age-related changes in vertebral body volume and volumetric bone mineral density at the thoracolumbar spine using opportunistic QCT

ObjectivesTo quantitatively investigate the age- and sex-related longitudinal changes in trabecular volumetric bone mineral density (vBMD) and vertebral body volume at the thoracolumbar spine in adults.MethodsWe retrospectively included 168 adults (mean age 58.7 ± 9.8 years, 51 women) who received ≥7 MDCT scans over a period of ≥6.5 years (mean follow-up 9.0 ± 2.1 years) for clinical reasons. Level-wise vBMD and vertebral body volume were extracted from 22720 thoracolumbar vertebrae using a convolutional neural network (CNN)-based framework with asynchronous calibration and correction of the contrast media phase. Human readers conducted semiquantitative assessment of fracture status and bony degenerations.ResultsIn the 40-60 years age group, women had a significantly higher trabecular vBMD than men at all thoracolumbar levels (p<0.05 to p<0.001). Conversely, men, on average, had larger vertebrae with lower vBMD. This sex difference in vBMD did not persist in the 60-80 years age group. While the lumbar (T12-L5) vBMD slopes in women only showed a non-significant trend of accelerated decline with age, vertebrae T1-11 displayed a distinct pattern, with women demonstrating a significantly accelerated decline compared to men (p<0.01 to p<0.0001). Between baseline and last follow-up examinations, the vertebral body volume slightly increased in women (T1-12: 1.1 ± 1.0 cm3; L1-5: 1.0 ± 1.4 cm3) and men (T1-12: 1.2 ± 1.3 cm3; L1-5: 1.5 ± 1.6 cm3). After excluding vertebrae with bony degenerations, the residual increase was only small in women (T1-12: 0.6 ± 0.6 cm3; L1-5: 0.7 ± 0.7 cm3) and men (T1-12: 0.7 ± 0.6 cm3; L1-5: 1.2 ± 0.8 cm3). In non-degenerated vertebrae, the mean change in volume was <5% of the respective vertebral body volumes.ConclusionSex differences in thoracolumbar vBMD were apparent before menopause, and disappeared after menopause, likely attributable to an accelerated and more profound vBMD decline in women at the thoracic spine. In patients without advanced spine degeneration, the overall volumetric changes in the vertebral body appeared subtle

Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans.

OBJECTIVES To investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models. METHODS This single-center retrospective study included patients who underwent two thoraco-abdominal CT scans during clinical routine with an average inter-scan interval of 21.7 ± 13.1 months (range 5-52 months). Automatic spine segmentation and vBMD extraction was performed by a convolutional neural network framework (anduin.bonescreen.de). Mean vBMD was calculated for levels T5-8, T9-12, and L1-5. VFs were identified by an expert in spine imaging. Odds ratios (ORs) for prevalent and incident VFs were calculated for vBMD (per standard deviation decrease) at each level, for baseline VF prevalence (yes/no), and for baseline VF count (n) using logistic regression models, adjusted for age and sex. Models were compared using Akaike's and Bayesian information criteria (AIC & BIC). RESULTS 420 patients (mean age, 63 years ± 9, 276 males) were included in this study. 40 (25 female) had prevalent and 24 (13 female) had incident VFs. Individuals with lower vBMD at any spine level had higher odds for VFs (L1-5, prevalent VF: OR,95%-CI,p: 2.2, 1.4-3.5,p=0.001; incident VF: 3.5, 1.8-6.9,p<0.001). In contrast, VF status (2.15, 0.72-6.43,p=0.170) and count (1.38, 0.89-2.12,p=0.147) performed worse in incident VF prediction. Information criteria revealed best fit for vBMD-based models (AIC vBMD=165.2; VF status=181.0; count=180.7). CONCLUSIONS VF prediction based on automatically extracted vBMD from routine clinical MDCT outperforms prediction models based on VF status and count. These findings underline the importance of opportunistic quantitative osteoporosis screening in clinical routine MDCT data

Proposed diagnostic volumetric bone mineral density thresholds for osteoporosis and osteopenia at the cervicothoracic spine in correlation to the lumbar spine

Objectives: To determine the correlation between cervicothoracic and lumbar volumetric bone mineral density (vBMD) in an average cohort of adults and to identify specific diagnostic thresholds for the cervicothoracic spine on the individual subject level. Methods: In this HIPPA–compliant study, we retrospectively included 260 patients (59.7 ± 18.3 years, 105 women), who received a contrast-enhanced or non-contrast-enhanced CT scan. vBMD was extracted using an automated pipeline (https://anduin.bonescreen.de). The association of vBMD between each vertebra spanning C2–T12 and the averaged values at the lumbar spine (L1–L3) was analyzed before and after semiquantitative assessment of fracture status and degeneration, and respective vertebra-specific cut-off values for osteoporosis were calculated using linear regression. Results: In both women and men, trabecular vBMD decreased with age in the cervical, thoracic, and lumbar regions. vBMD values of cervicothoracic vertebrae showed strong correlations with lumbar vertebrae (L1–L3), with a median Pearson value of r = 0.87 (range: r$_{C2}$ = 0.76 to r$_{T12}$ = 0.96). The correlation coefficients were significantly lower (p < 0.0001) without excluding fractured and degenerated vertebrae, median r = 0.82 (range: r$_{C2}$ = 0.69 to r$_{T12}$ = 0.93). Respective cut-off values for osteoporosis peaked at C4 (209.2 mg/ml) and decreased to 83.8 mg/ml at T12. Conclusion: Our data show a high correlation between clinically used mean L1–L3 values and vBMD values elsewhere in the spine, independent of age. The proposed cut-off values for the cervicothoracic spine therefore may allow the determination of low bone mass even in clinical cases where only parts of the spine are imaged. Key Points: vBMD of all cervicothoracic vertebrae showed strong correlation with lumbar vertebrae (L1–L3), with a median Pearson’s correlation coefficient of r = 0.87 (range: r$_{C2}$ = 0.76 to r$_{T12}$ = 0.96). The correlation coefficients were significantly lower (p < 0.0001) without excluding fractured and moderate to severely degenerated vertebrae, median r = 0.82 (range: r$_{C2}$ = 0.69 to r$_{T12}$ = 0.93). We postulate that trabecular vBMD < 200 mg/ml for the cervical spine and < 100 mg/ml for the thoracic spine are strong indicators of osteoporosis, similar to < 80 mg/ml at the lumbar spine

Automated Opportunistic Osteoporosis Screening in Routine Computed Tomography of the Spine: Comparison With Dedicated Quantitative CT

Opportunistic osteoporosis screening in nondedicated routine computed tomography (CT) is of increasing importance. The purpose of this study was to compare lumbar volumetric bone mineral density (vBMD) assessed by a convolutional neural network (CNN)-based framework in routine CT to vBMD from dedicated quantitative CT (QCT), and to evaluate the ability of vBMD and surrogate measurements of Hounsfield units (HU) to distinguish between patients with and without osteoporotic vertebral fractures (VFs). A total of 144 patients (median age: 70.7 years, 93 females) with clinical routine CT (eight different CT scanners, 120 kVp or 140 kVp, with and without intravenous contrast medium) and dedicated QCT acquired within ≤30 days were included. Vertebral measurements included (i) vBMD from the CNN-based approach including automated vertebral body labeling, segmentation, and correction of the contrast media phase for routine CT data (vBMD_OPP), (ii) vBMD from dedicated QCT (vBMD_QCT), and (iii) noncalibrated HU from vertebral bodies of routine CT data as previously proposed for immanent opportunistic osteoporosis screening based on CT attenuation. The intraclass correlation coefficient (ICC) for vBMD_QCT versus vBMD_OPP indicated better agreement (ICC = 0.913) than the ICC for vBMD_QCT versus noncalibrated HU (ICC = 0.704). Bland-Altman analysis showed data points from 137 patients (95.1%) within the limits of agreement (LOA) of -23.2 to 25.0 mg/cm3 for vBMD_QCT versus vBMD_OPP. Osteoporosis (vBMD <80 mg/cm3 ) was detected in 89 patients (vBMD_QCT) and 88 patients (vBMD_OPP), whereas no patient crossed the diagnostic thresholds from normal vBMD to osteoporosis or vice versa. In a subcohort of 88 patients (thoracolumbar spine covered by imaging for VF reading), 69 patients showed one or more prevalent VFs, and the performance for discrimination between patients with and without VFs was best for vBMD_OPP (area under the curve [AUC] = 0.862; 95% confidence interval [CI], 0.771-0.953). In conclusion, automated opportunistic osteoporosis screening in routine CT of various scanner setups is feasible and may demonstrate high diagnostic accuracy for prevalent VFs. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR)

Shifting up a gear with iDNA: From mammal detection events to standardised surveys

Invertebrate-derived DNA (iDNA), in combination with high throughput sequencing, has been proposed as a cost-efficient and powerful tool to survey vertebrate species. Previous studies, however, have only provided evidence that vertebrates can be detected using iDNA, but have not taken the next step of placing these detection events within a statistical framework that allows for robust biodiversity assessments. Here, we compare concurrent iDNA and camera-trap surveys. Leeches were repeatedly collected in close vicinity to 64 camera-trap stations in Sabah, Malaysian Borneo. We analyse iDNA-derived mammalian detection events in a modern occupancy model that accounts for imperfect detection and compare the results with those from occupancy models parameterised with camera-trap-derived detection events. We also combine leech-iDNA and camera-trap data in a single occupancy model. We found consistent estimates of occupancy probabilities produced by our camera-trap and leech datasets. This indicates that the metabarcoding of leech-iDNA method provides reasonable estimates of occupancy and may be a suitable method for studying and monitoring mammal species in tropical rainforests. However, we also show that a more extensive collection of leeches would be needed to assess mammal biodiversity with a robustness similar to that of camera traps. As certain taxa were only detected in leeches, we see great potential in complementing camera-trap studies with the iDNA approach, as long as the collection of leeches follows a robust and standardised sampling scheme. Synthesis and applications. Here, we describe an approach to analyse detection records of mammals derived from leech samples using an occupancy framework that accounts for leech-specific factors influencing the detection probability. We further combined camera trap and leech data, which lead to increased confidence in occupancy estimates. Our approach is not restricted to the processing of leech samples, but can be used for the analysis of other invertebrate DNA and environmental DNA data. Our study is the first step to shift the application of invertebrate DNA studies from opportunistic ad-hoc collections to the systematic surveys required for long-term management of wildlife populations

Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans

ObjectivesTo investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models.MethodsThis single-center retrospective study included patients who underwent two thoraco-abdominal CT scans during clinical routine with an average inter-scan interval of 21.7 ± 13.1 months (range 5–52 months). Automatic spine segmentation and vBMD extraction was performed by a convolutional neural network framework (anduin.bonescreen.de). Mean vBMD was calculated for levels T5-8, T9-12, and L1-5. VFs were identified by an expert in spine imaging. Odds ratios (ORs) for prevalent and incident VFs were calculated for vBMD (per standard deviation decrease) at each level, for baseline VF prevalence (yes/no), and for baseline VF count (n) using logistic regression models, adjusted for age and sex. Models were compared using Akaike’s and Bayesian information criteria (AIC &amp; BIC).Results420 patients (mean age, 63 years ± 9, 276 males) were included in this study. 40 (25 female) had prevalent and 24 (13 female) had incident VFs. Individuals with lower vBMD at any spine level had higher odds for VFs (L1-5, prevalent VF: OR,95%-CI,p: 2.2, 1.4–3.5,p=0.001; incident VF: 3.5, 1.8–6.9,p&lt;0.001). In contrast, VF status (2.15, 0.72–6.43,p=0.170) and count (1.38, 0.89–2.12,p=0.147) performed worse in incident VF prediction. Information criteria revealed best fit for vBMD-based models (AIC vBMD=165.2; VF status=181.0; count=180.7).ConclusionsVF prediction based on automatically extracted vBMD from routine clinical MDCT outperforms prediction models based on VF status and count. These findings underline the importance of opportunistic quantitative osteoporosis screening in clinical routine MDCT data

Exposure to repetitive head impacts is associated with corpus callosum microstructure and plasma total tau in former professional American football players

BACKGROUND: Exposure to repetitive head impacts (RHI) is associated with an increased risk of later-life neurobehavioral dysregulation and neurodegenerative disease. The underlying pathomechanisms are largely unknown. PURPOSE: To investigate whether RHI exposure is associated with later-life corpus callosum (CC) microstructure and whether CC microstructure is associated with plasma total tau and neuropsychological/neuropsychiatric functioning. STUDY TYPE: Retrospective cohort study. POPULATION: Seventy-five former professional American football players (age 55.2 ± 8.0 years) with cognitive, behavioral, and mood symptoms. FIELD STRENGTH/SEQUENCE: Diffusion-weighted echo-planar MRI at 3 T. ASSESSMENT: Subjects underwent diffusion MRI, venous puncture, neuropsychological testing, and completed self-report measures of neurobehavioral dysregulation. RHI exposure was assessed using the Cumulative Head Impact Index (CHII). Diffusion MRI measures of CC microstructure (i.e., free-water corrected fractional anisotropy (FA), trace, radial diffusivity (RD), and axial diffusivity (AD)) were extracted from seven segments of the CC (CC1-7), using a tractography clustering algorithm. Neuropsychological tests were selected: Trail Making Test Part A (TMT-A) and Part B (TMT-B), Controlled Oral Word Association Test (COWAT), Stroop Interference Test, and the Behavioral Regulation Index (BRI) from the Behavior Rating Inventory of Executive Function, Adult version (BRIEF-A). STATISTICAL TESTS: Diffusion MRI metrics were tested for associations with RHI exposure, plasma total tau, neuropsychological performance, and neurobehavioral dysregulation using generalized linear models for repeated measures. RESULTS: RHI exposure was associated with increased AD of CC1 (correlation coefficient (r) = 0.32, P < 0.05) and with increased plasma total tau (r = 0.34, P < 0.05). AD of the anterior CC1 was associated with increased plasma total tau (CC1: r = 0.30, P < 0.05; CC2: r = 0.29, P < 0.05). Higher trace, AD, and RD of CC1 were associated with better performance (P < 0.05) in TMT-A (trace, r = 0.33; AD, r = 0.31; and RD, r = 0.28) and TMT-B (trace, r = 0.31; RD, r = 0.34). Higher FA and AD of CC2 were associated with better performance (P < 0.05) in TMT-A (FA, r = 0.36; AD, r = 0.28), TMT-B (FA, r = 0.36; AD, r = 0.27), COWAT (FA, r = 0.36; AD, r = 0.32), and BRI (AD, r = 0.29). DATA CONCLUSION: These results suggest an association among RHI exposure, CC microstructure, plasma total tau, and clinical functioning in former professional American football players. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 1

Advanced MR techniques for preoperative glioma characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2