Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics.

OBJECTIVES: Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation. MATERIALS AND METHODS: The consensus was achieved by a multi-stage process. Stage 1 comprised a definition screening, a retrospective analysis with semantic mapping of terms found in 22 workflow definitions, and the compilation of an initial baseline definition. Stages 2 and 3 consisted of a Delphi process with over 45 experts hailing from sites participating in the German Research Foundation (DFG) Priority Program 2177. Stage 2 aimed to achieve a broad consensus for a definition proposal, while stage 3 identified the importance of translational challenges. RESULTS: Workflow definitions from 22 publications (published 2012-2020) were analyzed. Sixty-nine definition terms were extracted, mapped, and semantic ambiguities (e.g., homonymous and synonymous terms) were identified and resolved. The consensus definition was developed via a Delphi process. The final definition comprising seven phases and 37 aspects reached a high overall consensus (> 89% of experts "agree" or "strongly agree"). Two aspects reached no strong consensus. In addition, the Delphi process identified and characterized from the participating experts' perspective the ten most important challenges in radiomics workflows. CONCLUSION: To overcome semantic inconsistencies between existing definitions and offer a well-defined, broad, referenceable terminology, a consensus workflow definition for radiomics-based setups and a terms mapping to existing literature was compiled. Moreover, the most relevant challenges towards clinical application were characterized. CRITICAL RELEVANCE STATEMENT: Lack of standardization represents one major obstacle to successful clinical translation of radiomics. Here, we report a consensus workflow definition on different aspects of radiomics studies and highlight important challenges to advance the clinical adoption of radiomics. KEY POINTS: Published radiomics workflow terminologies are inconsistent, hindering standardization and translation. A consensus radiomics workflow definition proposal with high agreement was developed. Publicly available result resources for further exploitation by the scientific community.

First experiences with machine learning predictions of accelerated declining eGFR slope of living kidney donors 3 years after donation.

BACKGROUND: Living kidney donors are screened pre-donation to estimate the risk of end-stage kidney disease (ESKD). We evaluate Machine Learning (ML) to predict the progression of kidney function deterioration over time using the estimated GFR (eGFR) slope as the target variable. METHODS: We included 238 living kidney donors who underwent donor nephrectomy. We divided the dataset based on the eGFR slope in the third follow-up year, resulting in 185 donors with an average eGFR slope and 53 donors with an accelerated declining eGFR-slope. We trained three Machine Learning-models (Random Forest [RF], Extreme Gradient Boosting [XG], Support Vector Machine [SVM]) and Logistic Regression (LR) for predictions. Predefined data subsets served for training to explore whether parameters of an ESKD risk score alone suffice or additional clinical and time-zero biopsy parameters enhance predictions. Machine learning-driven feature selection identified the best predictive parameters. RESULTS: None of the four models classified the eGFR slope with an AUC greater than 0.6 or an F1 score surpassing 0.41 despite training on different data subsets. Following machine learning-driven feature selection and subsequent retraining on these selected features, random forest and extreme gradient boosting outperformed other models, achieving an AUC of 0.66 and an F1 score of 0.44. After feature selection, two predictive donor attributes consistently appeared in all models: smoking-related features and glomerulitis of the Banff Lesion Score. CONCLUSIONS: Training machine learning-models with distinct predefined data subsets yielded unsatisfactory results. However, the efficacy of random forest and extreme gradient boosting improved when trained exclusively with machine learning-driven selected features, suggesting that the quality, rather than the quantity, of features is crucial for machine learning-model performance. This study offers insights into the application of emerging machine learning-techniques for the screening of living kidney donors.

Robustness of radiomic features in healthy abdominal parenchyma of patients with repeated examinations on dual-layer dual-energy CT.

OBJECTIVES: Robustness of radiomic features in physiological tissue is an important prerequisite for quantitative analysis of tumor biology and response assessment. In contrast to previous studies which focused on different tumors with mostly short scan-re-scan intervals, this study aimed to evaluate the robustness of radiomic features in cancer-free patients and over a clinically encountered inter-scan interval. MATERIALS AND METHODS: Patients without visible tumor burden who underwent at least two portal-venous phase dual energy CT examinations of the abdomen between May 2016 and January 2020 were included, while macroscopic tumor burden was excluded based upon follow-up imaging for all patients (≥3 months). Further, patients were excluded if no follow-up imaging was available, or if the CT protocol showed deviations between repeated examinations. Circular regions of interest were placed and proofread by two board-certified radiologists (4 years and 5 years experience) within the liver (segments 3 and 6), the psoas muscle (left and right), the pancreatic head, and the spleen to obtain radiomic features from normal-appearing organ parenchyma using PyRadiomics. Radiomic feature robustness was tested using the concordance correlation coefficient with a threshold of 0.75 considered indicative for deeming a feature robust. RESULTS: In total, 160 patients with 480 repeated abdominal CT examinations (range: 2-4 per patient) were retrospectively included in this single-center, IRB-approved study. Considering all organs and feature categories, only 4.58 % (25/546) of all features were robust with the highest rate being found in the first order feature category (20.37 %, 22/108). Other feature categories (grey level co-occurrence matrix, grey level dependence matrix, grey level run length matrix, grey level size zone matrix, and neighborhood gray-tone difference matrix) yielded an overall low percentage of robust features (range: 0.00 %-1.19 %). A subgroup analysis revealed the reconstructed field of view and the X-ray tube current as determinants of feature robustness (significant differences in subgroups for all organs, p < 0.001) as well as the size of the region of interest (no significant difference for the pancreatic head with p = 0.135, significant difference with p < 0.001 for all other organs). CONCLUSION: Radiomic feature robustness obtained from cancer-free subjects with repeated examinations using a consistent protocol and CT scanner was limited, with first order features yielding the highest proportion of robust features.

The worldwide COVID-19 pandemic caused a decline in sonographic examinations - is this a continuing trend?

PURPOSE: Due to the increasing number of COVID-19 infections since spring 2020 the patient care workflow underwent changes in Germany. To minimize face-to-face exposure and reduce infection risk, non-time-critical elective medical procedures were postponed. Since ultrasound examinations include non-time-critical elective examinations and often can be substituted by other imaging modalities not requiring direct patient contact, the number of examinations has declined significantly. The aim of this study is to quantify the baseline number of ultrasound examinations in the years before, during, and in the early post-pandemic period of the COVID-19 pandemic (since January 2015 to September 2023), and to measure the number of examinations at different German university hospitals. MATERIALS AND METHODS: The number of examinations was assessed based on a web-based database at all participating clinics at the indicated time points. RESULTS: N = 288 562 sonographic examinations from four sites were included in the present investigation. From January 2020 to June 2020, a significantly lower number of examinations of n = 591.21 vs. 698.43 (p = 0.01) per month and included center was performed. Also, excluding the initial pandemic period until June 2020, significantly fewer ultrasound examinations were performed compared to pre-pandemic years 648.1 vs. 698.4 (p < 0.05), per month and included center, while here differences between the individual centers were observed. In the late phase of the pandemic (n = 681.96) and in the post-pandemic phase (as defined by the WHO criteria from May 2023; n = 739.95), the number of sonographic examinations returned to pre-pandemic levels. CONCLUSION: The decline in the number of sonographic examinations caused by the COVID-19 pandemic was initially largely intentional and can be illustrated quantitatively. After an initial abrupt decline in sonographic examinations, the pre-pandemic levels could not be reached for a long time, which could be due to restructuring of patient care and follow-up treatment. In the post-pandemic phase, the pre-pandemic level has been achieved again. The reasons for a prolonged reduction in ultrasound examinations are discussed in this article. KEY POINTS: · During the pandemic, significantly fewer ultrasound examinations were performed in the included centers.. · The number of examinations could not be reach the pre-pandemic level for a long time, which could be due to restructuring of patient care and follow-up treatment.. · Identifying causes for sonographic exam reduction is crucial in pandemic preparedness to uphold healthcare quality and continuity for all patients.. · The prolonged decline in sonographic examinations during the pandemic does not represent a lasting trend, as evidenced by the return to pre-pandemic levels..

Dual-energy CT revisited: a focused review of clinical use cases.

BACKGROUND: Dual-energy CT (DECT) has been available for more than 15 years and has undergone continuous technical development and refinement. Recently, the first photon-counting CT scanner became clinically available and has the potential to further expand the possibilities of spectral imaging. Numerous studies on DECT have been published since its creation, highlighting the clinical applications of the various reconstructions enabled by DECT. METHODS: The aim of this focused review is to succinctly summarize basic principles and available technical concepts of DECT and to discuss established applications relevant to the daily clinical routine. RESULTS/CONCLUSION: DECT is instrumental for a broad variety of clinical use cases. While some DECT applications can enhance day-to-day clinical practice, others are still subject to broad-scale validation and should therefore be handled with restraint in the clinical routine. KEY POINTS: · Virtual monoenergetic images, virtual unenhanced images, and iodine maps are the most well-investigated and relevant dual-energy CT reconstructions for clinical application.. · Low-keV virtual monoenergetic images (VMIs) yield superior image and iodine contrast, which can be leveraged for improved vessel assessment and lesion conspicuity, or to reduce contrast media or radiation dose. VMIs at intermediate energies can serve as a replacement for conventional grey-scale images. VMIs at high keV enable efficient artifact reduction, which can be further optimized in combination with dedicated metal artifact reduction algorithms.. · Iodine maps and virtual unenhanced images can improve lesion detection in oncologic imaging and enable lesion assessment in monophasic CT examinations, which may allow a reduction of correlative and follow-up imaging..

Therapy of Locally Advanced and Oligometastatic Pancreatic Adenocarcinoma.

Pancreatic adenocarcinoma is a lethal disease, and surgical resection remains the only curative treatment option. Unfortunately, upon primary diagnosis, only 15-20% of all patients with pancreatic ductal adenocarcinoma (PDAC) have localized disease that is eligible for operation. The remainder of patients either have borderline resectable or locally advanced disease or present with distant metastasis. In this review, we present a comprehensive overview regarding the current strategies and future directions in the multimodal therapy of locally advanced and oligometastasized pancreatic adenocarcinoma and discuss the benefit of surgery following neoadjuvant therapy in these patients.

Deep-Learning-Based Image Denoising in Imaging of Urolithiasis: Assessment of Image Quality and Comparison to State-of-the-Art Iterative Reconstructions.

This study aimed to compare the image quality and diagnostic accuracy of deep-learning-based image denoising reconstructions (DLIDs) to established iterative reconstructed algorithms in low-dose computed tomography (LDCT) of patients with suspected urolithiasis. LDCTs (CTDIvol, 2 mGy) of 76 patients (age: 40.3 ± 5.2 years, M/W: 51/25) with suspected urolithiasis were retrospectively included. Filtered-back projection (FBP), hybrid iterative and model-based iterative reconstruction (HIR/MBIR, respectively) were reconstructed. FBP images were processed using a Food and Drug Administration (FDA)-approved DLID. ROIs were placed in renal parenchyma, fat, muscle and urinary bladder. Signal- and contrast-to-noise ratios (SNR/CNR, respectively) were calculated. Two radiologists evaluated image quality on five-point Likert scales and urinary stones. The results showed a progressive decrease in image noise from FBP, HIR and DLID to MBIR with significant differences between each method (p < 0.05). SNR and CNR were comparable between MBIR and DLID, while it was significantly lower in HIR followed by FBP (e.g., SNR: 1.5 ± 0.3; 1.4 ± 0.4; 1.0 ± 0.3; 0.7 ± 0.2, p < 0.05). Subjective analysis confirmed best image quality in MBIR, followed by DLID and HIR, both being superior to FBP (p < 0.05). Diagnostic accuracy for urinary stone detection was best using MBIR (0.94), lowest using FBP (0.84) and comparable between DLID (0.90) and HIR (0.90). Stone size measurements were consistent between all reconstructions and showed excellent correlation (r2 = 0.958-0.975). In conclusion, MBIR yielded the highest image quality and diagnostic accuracy, with DLID producing better results than HIR and FBP in image quality and matching HIR in diagnostic precision.

A combined experimental and finite element analysis of the human elbow under loads of daily living.

Elbow trauma is often accompanied by a loss of independence in daily self-care activities, negatively affecting patients' quality of life. Finite element models can help gaining profound knowledge about native human joint mechanics, which is crucial to adequately restore joint functionality after severe injuries. Therefore, a finite element model of the elbow is required that includes both the radio-capitellar and ulno-trochlear joint and is subjected to loads realistic for activities of daily living. Since no such model has been published, we aim to fill this gap. For comparison, 8 intact cadaveric elbows were subjected to loads of up to 1000 N, after they were placed in an extended position. At each load step, the displacement of the proximal humerus relative to the distal base plate was measured with optical tracking markers and the joint pressure was measured with a pressure mapping sensor. Analogously, eight finite element models were created based on subject-specific CT scans of the corresponding elbow specimens. The CT scans were registered to the positions of tantalum beads in the experiment. The optically measured displacements were applied as boundary conditions. We demonstrated that the workflow can predict the experimental contact pressure distribution with a moderate correlation, the experimental peak pressures in the correct joints and the experimental stiffness with moderate to excellent correlation. The predictions of peak pressure magnitude, contact area and load share on the radius require improvement by precise representation of the cartilage geometry and soft tissues in the model, and proper initial contact in the experiment.

Cost-effectiveness of WEB Embolization, Coiling and Stent-assisted Coiling for the Treatment of Unruptured Intracranial Aneurysms.

PURPOSE: Information about the cost-effectiveness of a certain treatment is relevant for decision-making and healthcare providers. This study compares the cost-effectiveness of the novel Woven Endobridge (WEB) for intracranial aneurysm treatment with conventional coiling and stent-assisted coiling (SAC) from the perspective of the German Statutory Health Insurance. METHODS: A patient-level simulation was constructed to simulate 55-year-old patients with an unruptured middle cerebral artery aneurysm (size: 3-11 mm) considering WEB treatment, coiling or SAC in terms of morbidity, angiographic outcome, retreatment, procedural and rehabilitation costs and rupture rates. Incremental cost-effectiveness ratios (ICERs) were calculated as costs per quality-adjusted life years (QALYs) and costs per year with neurologic morbidity avoided. Uncertainty was explored with deterministic and probabilistic sensitivity analyses. The majority of data were obtained from prospective multi-center studies and meta-analyses of non-randomized studies. RESULTS: In the base case, lifetime QALYs were 13.24 for the WEB, 12.92 for SAC and 12.68 for coiling. Lifetime costs were 20,440 € for the WEB, 23,167 € for SAC, and 8200 € for coiling. Compared to coiling, the ICER for the WEB was 21,826 €/QALY, while SAC was absolutely dominated by WEB. Probabilistic sensitivity analysis revealed that at a willingness-to-pay of ≥ 30,000 €/QALY, WEB was the preferred treatment. Deterministic sampling showed that the discount rate, material costs and retreatment rates had the largest impact on the ICERs. CONCLUSION: The novel WEB showed at least comparable cost-effectiveness to SAC for treatment of broad-based unruptured aneurysms. Considering all three modalities, coiling had the least costs; however this modality is often not appropriate for the treatment of wide-necked aneurysms.

Morphological Studies to Identify the Nasopalatine and Inferior Alveolar Nerve Using a Special Head and Neck MRI Coil.

OBJECTIVES: Procedures in oral and maxillofacial surgery bear a high risk of nerve damage. Three-dimensional imaging techniques can optimize surgical planning and help to spare nerves. The aim of this study was to investigate the diagnostic value of a 1.5 T magnetic resonance imaging (MRI) scanner with a dedicated dental signal amplification coil for the assessment of nerves in the oral cavity as compared with cone beam computed tomography (CBCT). METHODS: Based on 6 predefined criteria, the assessability of the inferior alveolar and nasopalatine nerves in CBCT and MRI with a dedicated 4-channel dental coil were compared in 24 patients. RESULTS: Compared with CBCT, MRI with the dental coil showed significantly better evaluability of the inferior alveolar nerve in the sagittal and axial plane and the nasopalatine nerve in the axial plane. In the sagittal plane; however, the assessability of the nasopalatine nerve was significantly better in CBCT as compared with MRI. Yet, pertaining to overall assessability, no significant differences between modalities were found. CONCLUSIONS: In this pilot study, it can be reported that 1.5- T MRI with a dedicated dental coil is at least equivalent, if not superior, to CBCT in imaging nerve structures of the stomatognathic system. CLINICAL RELEVANCE: Preoperative, 3-dimensional images are known to simplify and refine the planning and execution of operations in maxillofacial surgery. In contrast to computed tomography and CBCT, MRI does not cause radiation exposure while enabling visualization of all relevant hard and soft tissues and, therefore, holds an advantage over well-established techniques.

Virtual versus true non-contrast images of the brain from spectral detector CT: comparison of attenuation values and image quality.

BACKGROUND: Prior studies focused on utilization of dual-energy computed tomography (DECT) to better detect intracranial pathology and to reduce artifacts. It is still unclear whether virtual non-contrast (VNC) images of DECT can replace true non-contrast (TNC) images. PURPOSE: To compare attenuation values and image quality of VNC images to TNC images of the brain, obtained using spectral detector CT (SDCT). MATERIAL AND METHODS: We retrospectively evaluated patients that underwent head CT with and without contrast material, on a SDCT scanner at our institution (n = 33). The attenuation values of different brain structures were obtained from TNC images, the conventional images of the post-contrast exams (n = 16) or the CT angiography (CTA) (n = 17), and the derived VNC images. In total, 591 regions of interest were obtained, including white and gray matter. Two neuroradiologists independently evaluated the image quality of the VNC and TNC images, using a 5-point Likert scale. RESULTS: The mean difference between the attenuation values on the VNC versus the TNC images was <4 HU for almost all the structures. The difference reached statistical significance (P < 0.05) for the deep gray structures but not for the white matter. The image quality score of the TNC images was 5 in all the patients (excellent gray-white matter differentiation). The scores of the VNC images differed between post-contrast and CTA examinations, with means of 4.9 ± 0.3 (excellent) and 3.2 ± 0.4 (fair), respectively (P < 0.001). CONCLUSION: Our results show minor differences between attenuation values of different brain structures on VNC versus TNC images of SDCT.

Artificial Intelligence in Ophthalmology - Status Quo and Future Perspectives.

Artificial intelligence (AI) is an emerging technology in healthcare and holds the potential to disrupt many arms in medical care. In particular, disciplines using medical imaging modalities, including e.g. radiology but ophthalmology as well, are already confronted with a wide variety of AI implications. In ophthalmologic research, AI has demonstrated promising results limited to specific diseases and imaging tools, respectively. Yet, implementation of AI in clinical routine is not widely spread due to availability, heterogeneity in imaging techniques and AI methods. In order to describe the status quo, this narrational review provides a brief introduction to AI ("what the ophthalmologist needs to know"), followed by an overview of different AI-based applications in ophthalmology and a discussion on future challenges.Abbreviations: Age-related macular degeneration, AMD; Artificial intelligence, AI; Anterior segment OCT, AS-OCT; Coronary artery calcium score, CACS; Convolutional neural network, CNN; Deep convolutional neural network, DCNN; Diabetic retinopathy, DR; Machine learning, ML; Optical coherence tomography, OCT; Retinopathy of prematurity, ROP; Support vector machine, SVM; Thyroid-associated ophthalmopathy, TAO.

MRI correlates of motoneuron loss in SMA.

BACKGROUND: Magnetic resonance imaging (MRI) is currently explored as supplemental tool to monitor disease progression and treatment response in various neuromuscular disorders. We here assessed the utility of a multi-parametric magnetic resonance imaging (MRI) protocol including quantitative water T2 mapping, Dixon-based proton density fat fraction (PDFF) estimation and diffusion tensor imaging (DTI) to detect loss of spinal motor neurons and subsequent muscle damage in adult SMA patients. METHODS: Sixteen SMA patients and 13 age-matched controls were enrolled in this prospective, longitudinal study. All participants underwent MRI imaging including measurements of Dixon-based PDFF and DTI of the sciatic nerve. SMA patients furthermore underwent measurements of muscle water T2 (T2w) of the biceps femoris muscle (BFM) and quadriceps femoris muscle (QFM). Ten participants returned for a second scan six months later. MRI parameter were correlated with clinical data. All patients were on nusinersen treatment. RESULTS: There were significantly higher intramuscular fat fractions in the BFM and QFM of SMA patients compared to healthy controls at baseline and after 6 months. Furthermore, T2 values significantly correlated positively with intramuscular fat fractions. The Hammersmith functional motor scale significantly correlated with the QFM's intramuscular fat fractions. DTI scans of the sciatic nerve were not significantly different between the two groups. CONCLUSION: This study demonstrates that, water T2 mapping and Dixon-based PDFF estimation may distinguish between adult SMA patients and controls, due to massive intramuscular fat accumulation in SMA. More extensive long-term studies are warranted to further evaluate these two modalities as surrogate markers in SMA patients during treatment.

Virtual non-contrast reconstructions improve differentiation between vascular enhancement and calcifications in stereotactic planning CT scans of cystic intracranial tumors.

PURPOSE: To assess the diagnostic value of spectral-detector CT (SDCT) derived virtual non-contrast images (VNC) for differentiation between vascular enhancement and wall calcifications of cystic intracranial tumors in contrast-enhanced stereotactic planning examinations. METHOD: 48 patients with cystic intracranial tumors who underwent stereotactic SDCT examinations between 02/2017 and 02/2020 were retrospectively included. In each patient, two separate hyperattenuating structures along the cyst wall were defined as either enhancement or calcification, respectively, using reference MRI examinations. Quantitative analysis was performed ROI-based in conventional images (CI) and VNC. In the subjective analysis, two radiologists diagnosed the predefined peri-cystic structures in binary decisions as either enhancement or calcification using CI and the combination of CI and VNC, and rated diagnostic confidence, image noise and removal of iodine in VNC. Moreover, a potential diagnostic benefit of VNC was indicated. RESULTS: Attenuation in CI was higher as compared to VNC across all assessed ROI (all p < 0.01). In VNC, CNR between calcification and white matter was significantly higher as compared to CNR between vascular enhancement and white matter (2.6 vs 1.3, p < 0.01), while there was no significant difference in CI. In the qualitative assessment, diagnostic accuracy was significantly higher using both VNC and CI compared to using CI alone. Raters reported less image noise in VNC as compared to CI. An additional diagnostic benefit of VNC was indicated in 84.4 % of all cases. CONCLUSIONS: SDCT-derived VNC images facilitate differentiation between peri-cystic contrast enhancement in blood vessels and calcifications in stereotactic planning scans of cystic intracranial tumors.

Clinical Low Dose Photon Counting CT for the Detection of Urolithiasis: Evaluation of Image Quality and Radiation Dose.

The purpose of this study was the evaluation of image quality and radiation dose parameters of the novel photon counting CT (PCCT, Naeotom Alpha, Siemens Healthineers) using low-dose scan protocols for the detection of urolithiasis. Standard CT scans were used as a reference (S40, Somatom Sensation 40, Siemens Healthineers). Sixty-three patients, who underwent CT scans between August and December 2021, were retrospectively enrolled. Thirty-one patients were examined with the PCCT and 32 patients were examined with the S40. Radiation dose parameters, as well as quantitative and qualitative image parameters, were analyzed. The presence of urolithiasis, image quality, and diagnostic certainty were rated on a 5-point-scale by 3 blinded readers. Both patient groups (PCCT and S40) did not differ significantly in terms of body mass index. Radiation dose was significantly lower for examinations with the PCCT compared to the S40 (2.4 ± 1.0 mSv vs. 3.4 ± 1.0 mSv; p < 0.001). The SNR was significantly better on images acquired with the PCCT (13.3 ± 3.3 vs. 8.2 ± 1.9; p < 0.001). The image quality of the PCCT was rated significantly better (4.3 ± 0.7 vs. 2.8 ± 0.6; p < 0.001). The detection rate of kidney or ureter calculi was excellent with both CT scanners (PCCT 97.8% and S40 99%, p = 0.611). In high contrast imaging, such as the depiction of stones of the kidney and the ureter, PCCT allows a significant reduction of radiation dose, while maintaining excellent diagnostic confidence and image quality. Given this image quality with our current protocol, further adjustments towards ultra-low-dose CT scans appear feasible.

Two-dimensional CT measurements enable assessment of body composition on head and neck CT.

OBJECTIVES: The aim of this study was to evaluate whether simple 2D measurements in axial slices of head and neck CT examinations correlate with generally established measurements of body composition in abdominal CT at the height of the third lumbar vertebra and thus allow for an estimation of muscle and fat masses. METHODS: One hundred twenty-two patients who underwent concurrent CT of the head and neck and the abdomen between July 2016 and July 2020 were retrospectively included. For a subset of 30 patients, additional bioelectrical impedance analysis (BIA) was available. Areas of paraspinal muscles at the height of the third (C3) and fifth cervical vertebrae (C5) as well as the total cross-sectional area at the height of C3 and at the submandibular level were correlated with the results of abdominal measurements and BIA. Furthermore, intra- and interreader variabilities of all measurements were assessed. RESULTS: Regarding adipose tissue, good correlations were found between the total cross-sectional area of the patient's body at the submandibular level and at the height of C3 between both abdominal measurements and BIA results (r = 0.8-0.92; all p < 0.001). Regarding muscle, the total paraspinal muscle area at the height of C3 and C5 showed strong correlations with abdominal measurements and moderate to strong correlations with BIA results (r = 0.44-0.80; all p < 0.001), with the muscle area on C5 yielding slightly higher correlations. CONCLUSIONS: Body composition information can be obtained with comparable reliability from head and neck CT using simple biplanar measurements as from abdominal CT. KEY POINTS: • The total paraspinal muscle area at the height of C3 and C5 correlates strongly with abdominal muscle mass. • The total cross-sectional area at the submandibular level and at the height of C3 shows good correlations with abdominal fat mass. • The described measurements facilitate a rapid, opportunistic assessment of relevant body composition parameters.

Spectral Detector CT-Derived Pulmonary Perfusion Maps and Pulmonary Parenchyma Characteristics for the Semiautomated Classification of Pulmonary Hypertension.

Objectives: To evaluate the usefulness of spectral detector CT (SDCT)-derived pulmonary perfusion maps and pulmonary parenchyma characteristics for the semiautomated classification of pulmonary hypertension (PH). Methods: A total of 162 consecutive patients with right heart catheter (RHC)-proven PH of different aetiologies as defined by the current ESC/ERS guidelines who underwent CT pulmonary angiography (CTPA) on SDCT and 20 patients with an invasive rule-out of PH were included in this retrospective study. Semiautomatic lung segmentation into normal and malperfused areas based on iodine density (ID) as well as automatic, virtual non-contrast-based emphysema quantification were performed. Corresponding volumes, histogram features and the ID SkewnessPerfDef-Emphysema-Index (δ-index) accounting for the ratio of ID distribution in malperfused lung areas and the proportion of emphysematous lung parenchyma were computed and compared between groups. Results: Patients with PH showed a significantly greater extent of malperfused lung areas as well as stronger and more homogenous perfusion defects. In group 3 and 4 patients, ID skewness revealed a significantly more homogenous ID distribution in perfusion defects than in all other subgroups. The δ-index allowed for further subclassification of subgroups 3 and 4 (p < 0.001), identifying patients with chronic thromboembolic PH (CTEPH, subgroup 4) with high accuracy (AUC: 0.92, 95%-CI, 0.85-0.99). Conclusion: Abnormal pulmonary perfusion in PH can be detected and quantified by semiautomated SDCT-based pulmonary perfusion maps. ID skewness in malperfused lung areas, and the δ-index allow for a classification of PH subgroups, identifying groups 3 and 4 patients with high accuracy, independent of reader expertise.

Dual-Energy CT, Virtual Non-Calcium Bone Marrow Imaging of the Spine: An AI-Assisted, Volumetric Evaluation of a Reference Cohort with 500 CT Scans.

Virtual non-calcium (VNCa) images from dual-energy computed tomography (DECT) have shown high potential to diagnose bone marrow disease of the spine, which is frequently disguised by dense trabecular bone on conventional CT. In this study, we aimed to define reference values for VNCa bone marrow images of the spine in a large-scale cohort of healthy individuals. DECT was performed after resection of a malignant skin tumor without evidence of metastatic disease. Image analysis was fully automated and did not require specific user interaction. The thoracolumbar spine was segmented by a pretrained convolutional neuronal network. Volumetric VNCa data of the spine's bone marrow space were processed using the maximum, medium, and low calcium suppression indices. Histograms of VNCa attenuation were created for each exam and suppression setting. We included 500 exams of 168 individuals (88 female, patient age 61.0 ± 15.9). A total of 8298 vertebrae were segmented. The attenuation histograms' overlap of two consecutive exams, as a measure for intraindividual consistency, yielded a median of 0.93 (IQR: 0.88-0.96). As our main result, we provide the age- and sex-specific bone marrow attenuation profiles of a large-scale cohort of individuals with healthy trabecular bone structure as a reference for future studies. We conclude that artificial-intelligence-supported, fully automated volumetric assessment is an intraindividually robust method to image the spine's bone marrow using VNCa data from DECT.

Feasibility of artificial intelligence-supported assessment of bone marrow infiltration using dual-energy computed tomography in patients with evidence of monoclonal protein - a retrospective observational study.

OBJECTIVES: To demonstrate the feasibility of an automated, non-invasive approach to estimate bone marrow (BM) infiltration of multiple myeloma (MM) by dual-energy computed tomography (DECT) after virtual non-calcium (VNCa) post-processing. METHODS: Individuals with MM and monoclonal gammopathy of unknown significance (MGUS) with concurrent DECT and BM biopsy between May 2018 and July 2020 were included in this retrospective observational study. Two pathologists and three radiologists reported BM infiltration and presence of osteolytic bone lesions, respectively. Bone mineral density (BMD) was quantified CT-based by a CE-certified software. Automated spine segmentation was implemented by a pre-trained convolutional neural network. The non-fatty portion of BM was defined as voxels > 0 HU in VNCa. For statistical assessment, multivariate regression and receiver operating characteristic (ROC) were conducted. RESULTS: Thirty-five patients (mean age 65 ± 12 years; 18 female) were evaluated. The non-fatty portion of BM significantly predicted BM infiltration after adjusting for the covariable BMD (p = 0.007, r = 0.46). A non-fatty portion of BM > 0.93% could anticipate osteolytic lesions and the clinical diagnosis of MM with an area under the ROC curve of 0.70 [0.49-0.90] and 0.71 [0.54-0.89], respectively. Our approach identified MM-patients without osteolytic lesions on conventional CT with a sensitivity and specificity of 0.63 and 0.71, respectively. CONCLUSIONS: Automated, AI-supported attenuation assessment of the spine in DECT VNCa is feasible to predict BM infiltration in MM. Further, the proposed method might allow for pre-selecting patients with higher pre-test probability of osteolytic bone lesions and support the clinical diagnosis of MM without pathognomonic lesions on conventional CT. KEY POINTS: • The retrospective study provides an automated approach for quantification of the non-fatty portion of bone marrow, based on AI-supported spine segmentation and virtual non-calcium dual-energy CT data. • An increasing non-fatty portion of bone marrow is associated with a higher infiltration determined by invasive biopsy after adjusting for bone mineral density as a control variable (p = 0.007, r = 0.46). • The non-fatty portion of bone marrow might support the clinical diagnosis of multiple myeloma when conventional CT images are negative (sensitivity 0.63, specificity 0.71).

Value of spectral detector computed tomography to differentiate infected from noninfected thoracoabominal fluid collections.

PURPOSE: To investigate the diagnostic value of spectral detector CT (SDCT)-derived virtual non-contrast (VNC), virtual monoenergetic images (VMI) and iodine overlays (IO) for distinguishing infected from noninfected fluid collections (FC) in the chest or abdomen. METHOD: This retrospective study included 58 patients with venous phase SDCT with 77 FC. For all included FC, microbiological analysis of aspirated fluid served as reference. For quantitative analysis, wall thickness was measured, and (ROI)-based analysis performed within the fluid, the FC's wall (if any) and the aorta. Two radiologists qualitatively evaluated visibility of wall enhancement, diagnostic confidence regarding infection of fluid collection, confidence of CT-guided drainage catheter placement and visibility of anatomical landmarks in conventional images (CI) and VNC, VMI40keV, IO. RESULTS: Wall thickness significantly differed between infected (n = 46) and noninfected (n = 31) FC (3.5 ± 1.8 mm vs. 1.4 ± 1.8 mm, AUC = 0.81; p < 0.05). Fluid attenuation and wall enhancement was significantly higher in infected as compared to noninfected FC in all reconstructions (p < 0.05, respectively). Highest AUC regarding A) attenuation in fluid was yielded in CI and VMI70,80keV (0.75); B) wall enhancement in CI (0.88) followed by iodine concentration (0.86). Contrast-to-noise ratio of wall vs. fluid was highest in VMI40keV (p < 0.05). All assessed qualitative parameters received significantly higher ratings when using spectral reconstructions vs. CI (p for all <0.05), except for visibility of wall enhancement. CONCLUSION: Spectral reconstructions improve the assessment of infected from noninfected thoracoabdominal fluid collections and depiction of wall enhancement. Diagnostic performance of the quantitative measurements in spectral reconstructions were comparable with measurements in conventional images.