Dark-field X-ray imaging for the assessment of osteoporosis in human lumbar spine specimens

Background: Dark-field imaging is a novel imaging modality that allows for the assessment of material interfaces by exploiting the wave character of x-ray. While it has been extensively studied in chest imaging, only little is known about the modality for imaging other tissues. Therefore, the purpose of this study was to evaluate whether a clinical X-ray dark-field scanner prototype allows for the assessment of osteoporosis.Materials and methods: In this prospective study we examined human cadaveric lumbar spine specimens (vertebral segments L2 to L4). We used a clinical prototype for dark-field radiography that yields both attenuation and dark-field images. All specimens were scanned in lateral orientation in vertical and horizontal position. All specimens were additionally imaged with CT as reference. Bone mineral density (BMD) values were derived from asynchronously calibrated quantitative CT measurements. Correlations between attenuation signal, dark-field signal and BMD were assessed using Spearman’s rank correlation coefficients. The capability of the dark-field signal for the detection of osteoporosis/osteopenia was evaluated with receiver operating characteristics (ROC) curve analysis.Results: A total of 58 vertebrae from 20 human cadaveric spine specimens (mean age, 73 years ±13 [standard deviation]; 11 women) were studied. The dark-field signal was positively correlated with the BMD, both in vertical (r = 0.56, p < .001) and horizontal position (r = 0.43, p < .001). Also, the dark-field signal ratio was positively correlated with BMD (r = 0.30, p = .02). No correlation was found between the signal ratio of attenuation signal and BMD (r = 0.14, p = .29). For the differentiation between specimens with and without osteoporosis/osteopenia, the area under the ROC curve (AUC) was 0.80 for the dark-field signal in vertical position.Conclusion: Dark-field imaging allows for the differentiation between spine specimens with and without osteoporosis/osteopenia and may therefore be a potential biomarker for bone stability

SNR analysis of contrast-enhanced MR imaging for early detection of rheumatoid arthritis.

OBJECTIVE:To investigate whether signal to noise (SNR) analysis of contrast-enhanced MRI gives additional benefit for early disease detection by Magnetic Resonance Imaging (MRI) of experimental rheumatoid arthritis (RA) in a small animal model. METHODS:We applied contrast-enhanced MRI at 7T in DBA mice with or without collagen-induced arthritis (CIA). Clinical score, OMERACT RAMRIS analysis and analysis of signal to noise ratios (SNR) of regions of interest in RA bearing mice, methotrexate/methylprednisolone acetate treated RA and control animals were compared with respect to benefit for early diagnosis. RESULTS:While treated RA and control animals did not show signs of RA activity in any of the above-mentioned scoring methods at any time point analyzed, RA animals revealed characteristic signs of RA in RAMRIS at the same time point when RA was detected clinically through scoring of the paws. The MR-based SNR analysis detected signs of synovitis, the earliest indication of RA, not only in late clinical stages, but also at an early stage when little or no clinical signs of RA were present in CIA animals and RAMRIS did not allow a distinct early detection. CONCLUSION:SNR analysis of contrast-enhanced MR imaging provides additional benefit for early arthritis detection in CIA mice

Additional MRI for initial M-staging in pancreatic cancer: a cost-effectiveness analysis

Objective!#!Pancreatic cancer is portrayed to become the second leading cause of cancer-related death within the next years. Potentially complicating surgical resection emphasizes the importance of an accurate TNM classification. In particular, the failure to detect features for non-resectability has profound consequences on patient outcomes and economic costs due to incorrect indication for resection. In the detection of liver metastases, contrast-enhanced MRI showed high sensitivity and specificity; however, the cost-effectiveness compared to the standard of care imaging remains unclear. The aim of this study was to analyze whether additional MRI of the liver is a cost-effective approach compared to routinely acquired contrast-enhanced computed tomography (CE-CT) in the initial staging of pancreatic cancer.!##!Methods!#!A decision model based on Markov simulation was developed to estimate the quality-adjusted life-years (QALYs) and lifetime costs of the diagnostic modalities. Model input parameters were assessed based on evidence from recent literature. The willingness-to-pay (WTP) was set to 100,000/QALY. To evaluate model uncertainty, deterministic and probabilistic sensitivity analyses were performed.!##!Results!#!In the base-case analysis, the model yielded a total cost of 185,597 and an effectiveness of 2.347 QALYs for CE-MR/CT and $187,601 and 2.337 QALYs for CE-CT respectively. With a net monetary benefit (NMB) of$49,133, CE-MR/CT is shown to be dominant over CE-CT with a NMB of $46,117. Deterministic and probabilistic survival analysis showed model robustness for varying input parameters.!##!Conclusion!#!Based on our results, combined CE-MR/CT can be regarded as a cost-effective imaging strategy for the staging of pancreatic cancer.!##!Key points!#!• Additional MRI of the liver for initial staging of pancreatic cancer results in lower total costs and higher effectiveness. • The economic model showed high robustness for varying input parameters

Calcium scoring using virtual non-contrast images from a dual-layer spectral detector CT: comparison to true non-contrast data and evaluation of proportionality factor in a large patient collective

Objective!#!Determination of coronary artery calcium scoring (CACS) in non-contrast computed tomography (CT) images has been shown to be an important prognostic factor in coronary artery disease (CAD). The objective of this study was to evaluate the accuracy of CACS from virtual non-contrast (VNC) imaging generated from spectral data in comparison to standard (true) non-contrast (TNC) imaging in a representative patient cohort with clinically approved software.!##!Methods!#!One hundred three patients referred to coronary CTA with suspicion of CAD were investigated on a dual-layer spectral detector CT (SDCT) scanner. CACS was calculated from both TNC and VNC images by software certified for medical use. Patients with a CACS of 0 were excluded from analysis.!##!Results!#!The mean age of the study population was 61 ± 11 years with 48 male patients (67%). Inter-quartile range of clinical CACS was 22-282. Correlation of measured CACS from true- and VNC images was high (0.95); p < 0.001. The slope was 3.83, indicating an underestimation of VNC CACS compared to TNC CACS by that factor. Visual analysis of the Bland-Altman plot of CACS showed good accordance with both methods after correction of VNC CACS by the abovementioned factor.!##!Conclusions!#!In clinical diagnostics of CAD, the determination of CACS is feasible using VNC images generated from spectral data obtained on a dual-layer spectral detector CT. When multiplied by a correction factor, results were in good agreement with the standard technique. This could enable radiation dose reductions by obviating the need for native scans typically used for CACS.!##!Key points!#!• Calcium scoring is feasible from contrast-enhanced CT images using a dual-layer spectral detector CT scanner. • When multiplied by a correction factor, calcium scoring from virtual non-contrast images shows good agreement with the standard technique. • Omitting native scans for calcium scoring could enable radiation dose reduction

Soft tissue masses: distribution of entities and rate of malignancy in small lesions

Background!#!Small soft tissue masses are often falsely assumed to be benign and resected with failure to achieve tumor-free margins. Therefore, this study retrospectively investigated the distribution of histopathologic diagnosis to be encountered in small soft tissue tumors (≤ 5 cm) in a large series of a tertiary referral center.!##!Methods!#!Patients with a soft tissue mass (STM) with a maximum diameter of 5 cm presenting at our institution over a period of 10 years, who had undergone preoperative Magnetic resonance imaging and consequent biopsy or/and surgical resection, were included in this study. A final histopathological diagnosis was available in all cases. The maximum tumor diameter was determined on MR images by one radiologist. Moreover, tumor localization (head/neck, trunk, upper extremity, lower extremity, hand, foot) and depth (superficial / deep to fascia) were assessed.!##!Results!#!In total, histopathologic results and MR images of 1753 patients were reviewed. Eight hundred seventy patients (49.63%) showed a STM ≤ 5 cm and were therefore included in this study (46.79 +/- 18.08 years, 464 women). Mean maximum diameter of the assessed STMs was 2.88 cm. Of 870 analyzed lesions ≤ 5 cm, 170 (19.54%) were classified as superficial and 700 (80.46%) as deep. The malignancy rate of all lesions ≤ 5 cm was at 22.41% (superficial: 23.53% / deep: 22.14%). The malignancy rate dropped to 16.49% (20.79% / 15.32%) when assessing lesions ≤ 3 cm (p = 0.007) and to 15.0% (18.18% / 13.79%) when assessing lesions ≤ 2 cm (p = 0.006). Overall, lipoma was the most common benign lesion of superficial STMs (29.41%) and tenosynovial giant cell tumor was the most common benign lesion of deep STMs (23.29%). Undifferentiated pleomorphic sarcoma was the most common malignant diagnosis among both, superficial (5.29%) and deep (3.57%) STMs.!##!Conclusions!#!The rate of malignancy decreased significantly with tumor size in both, superficial and deep STMs. The distribution of entities was different between superficial and deep STMs, yet there was no significant difference found in the malignancy rate

Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning

Abstract Background A deep learning (DL) model that automatically detects cardiac pathologies on cardiac MRI may help streamline the diagnostic workflow. To develop a DL model to detect cardiac pathologies on cardiac MRI T1-mapping and late gadolinium phase sensitive inversion recovery (PSIR) sequences were used. Methods Subjects in this study were either diagnosed with cardiac pathology (n = 137) including acute and chronic myocardial infarction, myocarditis, dilated cardiomyopathy, and hypertrophic cardiomyopathy or classified as normal (n = 63). Cardiac MR imaging included T1-mapping and PSIR sequences. Subjects were split 65/15/20% for training, validation, and hold-out testing. The DL models were based on an ImageNet pretrained DenseNet-161 and implemented using PyTorch and fastai. Data augmentation with random rotation and mixup was applied. Categorical cross entropy was used as the loss function with a cyclic learning rate (1e-3). DL models for both sequences were developed separately using similar training parameters. The final model was chosen based on its performance on the validation set. Gradient-weighted class activation maps (Grad-CAMs) visualized the decision-making process of the DL model. Results The DL model achieved a sensitivity, specificity, and accuracy of 100%, 38%, and 88% on PSIR images and 78%, 54%, and 70% on T1-mapping images. Grad-CAMs demonstrated that the DL model focused its attention on myocardium and cardiac pathology when evaluating MR images. Conclusions The developed DL models were able to reliably detect cardiac pathologies on cardiac MR images. The diagnostic performance of T1 mapping alone is particularly of note since it does not require a contrast agent and can be acquired quickly

MR-based proton density fat fraction (PDFF) of the vertebral bone marrow differentiates between patients with and without osteoporotic vertebral fractures

The bone marrow proton density fat fraction (PDFF) assessed with MRI enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures. Therefore, PDFF may be a potentially useful biomarker for bone fragility assessment.!##!Introduction!#!To evaluate whether magnetic resonance imaging (MRI)-based proton density fat fraction (PDFF) of vertebral bone marrow can differentiate between osteoporotic/osteopenic patients with and without vertebral fractures.!##!Methods!#!Of the 52 study patients, 32 presented with vertebral fractures of the lumbar spine (66.4 ± 14.4 years, 62.5% women; acute low-energy osteoporotic/osteopenic vertebral fractures, N = 25; acute high-energy traumatic vertebral fractures, N = 7). These patients were frequency matched for age and sex to patients without vertebral fractures (N = 20, 69.3 ± 10.1 years, 70.0% women). Trabecular bone mineral density (BMD) values were derived from quantitative computed tomography. Chemical shift encoding-based water-fat MRI of the lumbar spine was performed, and PDFF maps were calculated. Associations between fracture status and PDFF were assessed using multivariable linear regression models.!##!Results!#!Over all patients, mean PDFF and trabecular BMD correlated significantly (r =  - 0.51, P < 0.001). In the osteoporotic/osteopenic group, those patients with osteoporotic/osteopenic fractures had a significantly higher PDFF than those without osteoporotic fractures after adjusting for age, sex, weight, height, and trabecular BMD (adjusted mean difference [95% confidence interval], 20.8% [10.4%, 30.7%]; P < 0.001), although trabecular BMD values showed no significant difference between the subgroups (P = 0.63). For the differentiation of patients with and without vertebral fractures in the osteoporotic/osteopenic subgroup using mean PDFF, an area under the receiver operating characteristic (ROC) curve (AUC) of 0.88 (P = 0.006) was assessed. When evaluating all patients with vertebral fractures, those with high-energy traumatic fractures had a significantly lower PDFF than those with low-energy osteoporotic/osteopenic vertebral fractures (P < 0.001).!##!Conclusion!#!MR-based PDFF enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures, suggesting the use of PDFF as a potential biomarker for bone fragility

18F FDG PET/MRI with hepatocyte-specific contrast agent for M staging of rectal cancer: a primary economic evaluation

Purpose!#!Rectal cancer is one of the most frequent causes of cancer-related morbidity and mortality in the world. Correct identification of the TNM state in primary staging of rectal cancer has critical implications on patient management. Initial evaluations revealed a high sensitivity and specificity for whole-body PET/MRI in the detection of metastases allowing for metastasis-directed therapy regimens. Nevertheless, its cost-effectiveness compared with that of standard-of-care imaging (SCI) using pelvic MRI + chest and abdominopelvic CT is yet to be investigated. Therefore, the aim of this study was to analyze the cost-effectiveness of whole-body !##!Methods!#!For estimation of quality-adjusted life years (QALYs) and lifetime costs of diagnostic modalities, a decision model including whole-body !##!Results!#!In the base-case scenario, the strategy whole-body !##!Conclusion!#!Based on the results of the analysis, use of whole-bod

Detection of Bone Marrow Edema in Patients with Osteoid Osteoma Using Three-Material Decomposition with Dual-Layer Spectral CT

The aim of this study is to assess whether perifocal bone marrow edema (BME) in patients with osteoid osteoma (OO) can be accurately detected on dual-layer spectral CT (DLCT) with three-material decomposition. To that end, 18 patients with OO (25.33 ± 12.44 years; 7 females) were pairwise-matched with 18 patients (26.72 ± 9.65 years; 9 females) admitted for suspected pathologies other than OO in the same anatomic location but negative imaging findings. All patients were examined with DLCT and MRI. DLCT data was decomposed into hydroxyapatite and water- and fat-equivalent volume fraction maps. Two radiologists assessed DLCT-based volume fraction maps for the presence of perifocal BME, using a Likert scale (1 = no edema; 2 = likely no edema; 3 = likely edema; 4 = edema). Accuracy, sensitivity, and specificity for the detection of BME on DLCT were analyzed using MR findings as standard of reference. For the detection of BME in patients with OO, DLCT showed a sensitivity of 0.92, a specificity of 0.94, and an accuracy of 0.92 for both radiologists. Interreader agreement for the assessment of BME with DLCT was substantial (weighted κ = 0.78; 95% CI, 0.59, 0.94). DLCT with material-specific volume fraction maps allowed accurate detection of BME in patients with OO. This may spare patients additional examinations and facilitate the diagnosis of OO

CT-like images based on T1 spoiled gradient-echo and ultra-short echo time MRI sequences for the assessment of vertebral fractures and degenerative bone changes of the spine

Objectives!#!To evaluate the performance of 3D T1w spoiled gradient-echo (T1SGRE) and ultra-short echo time (UTE) MRI sequences for the detection and assessment of vertebral fractures and degenerative bone changes compared with conventional CT.!##!Methods!#!Fractures (n = 44) and degenerative changes (n = 60 spinal segments) were evaluated in 30 patients (65 ± 14 years, 18 women) on CT and 3-T MRI, including CT-like images derived from T1SGRE and UTE. Two radiologists evaluated morphological features on both modalities: Genant and AO/Magerl classifications, anterior/posterior vertebral height, fracture age; disc height, neuroforaminal diameter, grades of spondylolisthesis, osteophytes, sclerosis, and facet joint degeneration. Diagnostic accuracy and agreement between MRI and CT and between radiologists were assessed using crosstabs, weighted κ, and intraclass correlation coefficients. Image quality was graded on a Likert scale.!##!Results!#!For fracture detection, sensitivity, specificity, and accuracy were 0.95, 0.98, and 0.97 for T1SGRE and 0.91, 0.96, and 0.95 for UTE. Agreement between T1SGRE and CT was substantial to excellent (e.g., Genant: κ, 0.92 [95% confidence interval, 0.83-1.00]; AO/Magerl: κ, 0.90 [0.76-1.00]; osteophytes: κ, 0.91 [0.82-1.00]; sclerosis: κ, 0.68 [0.48-0.88]; spondylolisthesis: ICCs, 0.99 [0.99-1.00]). Agreement between UTE and CT was lower, ranging from moderate (e.g., sclerosis: κ, 0.43 [0.26-0.60]) to excellent (spondylolisthesis: ICC, 0.99 [0.99-1.00]). Inter-reader agreement was substantial to excellent (0.52-1.00), respectively, for all parameters. Median image quality of T1SGRE was rated significantly higher than that of UTE (p < 0.001).!##!Conclusions!#!Morphologic assessment of bone pathologies of the spine using MRI was feasible and comparable to CT, with T1SGRE being more robust than UTE.!##!Key points!#!• Vertebral fractures and degenerative bone changes can be assessed on CT-like MR images, with 3D T1w spoiled gradient-echo-based images showing a high diagnostic accuracy and agreement with CT. • This could enable MRI to precisely assess bone morphology, and 3D T1SGRE MRI sequences may substitute additional spinal CT examinations in the future. • Image quality and robustness of T1SGRE sequences are higher than those of UTE MRI for the assessment of bone structures