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Tuberculosis is an endemic emergency that is prevalent in developing countries, particularly in sub-Saharan Black Africa, including Congo-Brazzaville. In addition to the pulmonary, ganglionic, and bone forms, there are other poorly documented locations. In the Congo, among these is cutaneous tuberculosis which is exceptional. A 9-year-old boy and two adult patients had persistent lesions of the left hip and thigh wounds, chest wall, and hypogastric wound with no healing for more than four months, respectively. Among these patients, one case of tuberculous contact was noted. Histopathological examination revealed a Koester follicle, suggesting a tuberculous skin fistula. A fistulectomy was performed, coupled with a quadruple antituberculous therapy combining rifampicin, isoniazid, ethambutol, and pyrazinamide for two months, relayed by a dual therapy consisting of isoniazid and ethambutol for 6 to 8 months. The evolution was favorable in all cases with healing of the lesions after 3 to 6 weeks. The existence of inexhaustible fistulas and the absence of scarring of a wound should make one suspect, among other things, cutaneous tuberculosis. The product of fistulectomy makes it possible to establish the histological diagnosis of cutaneous tuberculosis.

Objective: Our study objective was to explore the additional value of dual-energy CT (DECT) material decomposition for squamous cell carcinoma of the head and neck (SCCHN) survival prognostication., Methods: A group of 50 SCCHN patients (male, 37; female, 13; mean age, 63.6 ± 10.82 years) with baseline head and neck DECT between September 2014 and August 2020 were retrospectively included. Primary tumors were segmented, radiomics features were extracted, and DECT material decomposition was performed. We used independent train and validation datasets with cross-validation and 100 independent iterations to identify prognostic signatures applying elastic net (EN) and random survival forest (RSF). Features were ranked and intercorrelated according to their prognostic importance. We benchmarked the models against clinical parameters. Intraclass correlation coefficients were used to analyze the interreader variation., Results: The exclusively radiomics-trained models achieved similar ( P = 0.947) prognostic performance of area under the curve (AUC) = 0.784 (95% confidence interval [CI], 0.775-0.812) (EN) and AUC = 0.785 (95% CI, 0.759-0.812) (RSF). The additional application of DECT material decomposition did not improve the model's performance (EN, P = 0.594; RSF, P = 0.198). In the clinical benchmark, the top averaged AUC value of 0.643 (95% CI, 0.611-0.675) was inferior to the quantitative imaging-biomarker models ( P < 0.001). A combined imaging and clinical model did not improve the imaging-based models ( P > 0.101). Shape features revealed high prognostic importance., Conclusions: Radiomics AI applications may be used for SCCHN survival prognostication, but the spectral information of DECT material decomposition did not improve the model's performance in our preliminary investigation., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: The radiologists' workload is increasing, and computational imaging techniques may have the potential to identify visually unequivocal lesions, so that the radiologist can focus on equivocal and critical cases. The purpose of this study was to assess radiomics versus dual-energy CT (DECT) material decomposition to objectively distinguish visually unequivocal abdominal lymphoma and benign lymph nodes., Methods: Retrospectively, 72 patients [m, 47; age, 63.5 (27-87) years] with nodal lymphoma (n = 27) or benign abdominal lymph nodes (n = 45) who had contrast-enhanced abdominal DECT between 06/2015 and 07/2019 were included. Three lymph nodes per patient were manually segmented to extract radiomics features and DECT material decomposition values. We used intra-class correlation analysis, Pearson correlation and LASSO to stratify a robust and non-redundant feature subset. Independent train and test data were applied on a pool of four machine learning models. Performance and permutation-based feature importance was assessed to increase the interpretability and allow for comparison of the models. Top performing models were compared by the DeLong test., Results: About 38% (19/50) and 36% (8/22) of the train and test set patients had abdominal lymphoma. Clearer entity clusters were seen in t-SNE plots using a combination of DECT and radiomics features compared to DECT features only. Top model performances of AUC = 0.763 (CI = 0.435-0.923) were achieved for the DECT cohort and AUC = 1.000 (CI = 1.000-1.000) for the radiomics feature cohort to stratify visually unequivocal lymphomatous lymph nodes. The performance of the radiomics model was significantly (p = 0.011, DeLong) superior to the DECT model., Conclusions: Radiomics may have the potential to objectively stratify visually unequivocal nodal lymphoma versus benign lymph nodes. Radiomics seems superior to spectral DECT material decomposition in this use case. Therefore, artificial intelligence methodologies may not be restricted to centers with DECT equipment., (© 2023. The Author(s).)

Background: Treatment plans for squamous cell carcinoma of the head and neck (SCCHN) are individually decided in tumor board meetings but some treatment decision-steps lack objective prognostic estimates. Our purpose was to explore the potential of radiomics for SCCHN therapy-specific survival prognostication and to increase the models' interpretability by ranking the features based on their predictive importance., Methods: We included 157 SCCHN patients (male, 119; female, 38; mean age, 64.39 ± 10.71 years) with baseline head and neck CT between 09/2014 and 08/2020 in this retrospective study. Patients were stratified according to their treatment. Using independent training and test datasets with cross-validation and 100 iterations, we identified, ranked and inter-correlated prognostic signatures using elastic net (EN) and random survival forest (RSF). We benchmarked the models against clinical parameters. Inter-reader variation was analyzed using intraclass-correlation coefficients (ICC)., Results: EN and RSF achieved top prognostication performances of AUC = 0.795 (95% CI 0.767-0.822) and AUC = 0.811 (95% CI 0.782-0.839). RSF prognostication slightly outperformed the EN for the complete (ΔAUC 0.035, p = 0.002) and radiochemotherapy (ΔAUC 0.092, p < 0.001) cohort. RSF was superior to most clinical benchmarking (p ≤ 0.006). The inter-reader correlation was moderate or high for all features classes (ICC ≥ 0.77 (± 0.19)). Shape features had the highest prognostic importance, followed by texture features., Conclusions: EN and RSF built on radiomics features may be used for survival prognostication. The prognostically leading features may vary between treatment subgroups. This warrants further validation to potentially aid clinical treatment decision making in the future., (© 2023. The Author(s).)

We aimed to identify hepatocellular carcinoma (HCC) patients who will respond to repetitive transarterial chemoembolization (TACE) to improve the treatment algorithm. Retrospectively, 61 patients (mean age, 65.3 years ± 10.0 [SD]; 49 men) with 94 HCC mRECIST target-lesions who had three consecutive TACE between 01/2012 and 01/2020 were included. Robust and non-redundant radiomics features were extracted from the 24 h post-embolization CT. Five different clinical TACE-scores were assessed. Seven different feature selection methods and machine learning models were used. Radiomics, clinical and combined models were built to predict response to TACE on a lesion-wise and patient-wise level as well as its impact on overall-survival prognostication. 29 target-lesions of 19 patients were evaluated in the test set. Response rates were 37.9% (11/29) on the lesion-level and 42.1% (8/19) on the patient-level. Radiomics top lesion-wise response prognostications was AUC 0.55-0.67. Clinical scores revealed top AUCs of 0.65-0.69. The best working model combined the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical score mHAP&#95;II&#95;score&#95;group with AUC = 0.70, accuracy = 0.72. We transferred this model on a patient-level to achieve AUC = 0.62, CI = 0.41-0.83. The two radiomics-clinical features revealed overall-survival prognostication of C-index = 0.67. In conclusion, a random forest model using the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical mHAP-II-score-group seems promising for TACE response prognostication., (© 2023. The Author(s).)

Artificial intelligence is rapidly expanding in all technological fields. The medical field, and especially diagnostic imaging, has been showing the highest developmental potential. Artificial intelligence aims at human intelligence simulation through the management of complex problems. This review describes the technical background of artificial intelligence, machine learning, and deep learning. The first section illustrates the general potential of artificial intelligence applications in the context of request management, data acquisition, image reconstruction, archiving, and communication systems. In the second section, the prospective of dedicated tools for segmentation, lesion detection, automatic diagnosis, and classification of musculoskeletal disorders is discussed., (© 2022 Wiley Periodicals LLC.)

The Minnesota Multiphasic Personality Inventory (MMPI) family of instruments have long been used in child custody and parental fitness evaluation (PFE) contexts, spanning from the original MMPI to the recently released MMPI-3. In addition to updating the English-language normative sample and expanding content coverage, the MMPI-3 was released with a U.S. Spanish-language normative sample. The present study sought to examine the psychometric properties of the Spanish-language MMPI-3, specifically in a PFE context. The sample consisted of individuals who were evaluated for parental fitness at a multisite private practice in Puerto Rico. A combined gender comparison group sample with equal number of men and women ( n = 238) produced mean T scores that were within half a standard deviation of the Spanish-language normative sample on all scales. Scores on the Symptom Validity Scale were meaningfully higher among women ( n = 247) relative to the normative sample, and the mean juvenile conduct problems score among men ( n = 119) was meaningfully higher than that of the normative sample. Reliability estimates were generally adequate, with some reflecting low internal consistency; however, low standard errors of measurement indicated that low alpha estimates were a function of range restriction rather than measurement imprecision. Limitations, including the need for the accumulation of validity evidence, are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Purpose: To investigate the diagnostic performance of noise-optimized virtual monoenergetic images (VMI+) in dual-energy CT (DECT) of portal vein thrombosis (PVT) compared to standard reconstructions. Method: This retrospective, single-center study included 107 patients (68 men; mean age, 60.1 ± 10.7 years) with malignant or cirrhotic liver disease and suspected PVT who had undergone contrast-enhanced portal-phase DECT of the abdomen. Linearly blended (M&#95;0.6) and virtual monoenergetic images were calculated using both standard VMI and noise-optimized VMI+ algorithms in 20 keV increments from 40 to 100 keV. Quantitative measurements were performed in the portal vein for objective contrast-to-noise ratio (CNR) calculation. The image series showing the greatest CNR were further assessed for subjective image quality and diagnostic accuracy of PVT detection by two blinded radiologists. Results: PVT was present in 38 subjects. VMI+ reconstructions at 40 keV revealed the best objective image quality (CNR, 9.6 ± 4.3) compared to all other image reconstructions (p < 0.01). In the standard VMI series, CNR peaked at 60 keV (CNR, 4.7 ± 2.1). Qualitative image parameters showed the highest image quality rating scores for the 60 keV VMI+ series (median, 4) (p ≤ 0.03). The greatest diagnostic accuracy for the diagnosis of PVT was found for the 40 keV VMI+ series (sensitivity, 96%; specificity, 96%) compared to M&#95;0.6 images (sensitivity, 87%; specificity, 92%), 60 keV VMI (sensitivity, 87%; specificity, 97%), and 60 keV VMI+ reconstructions (sensitivity, 92%; specificity, 97%) (p ≤ 0.01). Conclusions: Low-keV VMI+ reconstructions resulted in significantly improved diagnostic performance for the detection of PVT compared to other DECT reconstruction algorithms.

Purpose: To assess the influence of intravenously injected contrast agent on bone mineral density (BMD) assessment in dual-source dual-energy CT., Methods: This retrospective study included 1,031 patients (mean age, 53 ± 7 years; 519 women) who had undergone third-generation dual-source dual-energy CT in context of tumor staging between January 2019 and December 2019. Dedicated postprocessing software based on material decomposition was used for phantomless volumetric BMD assessment of trabecular bone of the lumbar spine. Volumetric trabecular BMD values derived from unenhanced and contrast-enhanced portal venous phase were compared by calculating correlation and agreement analyses using Pearson product-moment correlation, linear regression, and Bland-Altman plots., Results: Mean BMD values were 115.53 ± 37.23 and 116.10 ± 37.78 mg/cm 3 in unenhanced and contrast-enhanced dual-energy CT series, respectively. Values from contrast-enhanced portal venous phase differed not significantly from those of the unenhanced phase (p = 0.44) and showed high correlation (r = 0.971 [95% CI, 0.969-0.973]) with excellent agreement in Bland-Altman plots. Mean difference of the two phases was 0.61 mg/cm 3 (95% limits of agreement, -17.14 and 18.36 mg/cm 3 )., Conclusion: Portal venous phase dual-source dual-energy CT allows for accurate opportunistic BMD assessment of trabecular bone of the lumbar spine compared to unenhanced imaging. Therefore, dual-source CT may provide greater flexibility regarding BMD assessment in clinical routine and reduce radiation exposure by avoiding additional osteodensitometry examinations, as contrast-enhanced CT scans in context of tumor staging are increasingly performed in dual-energy mode., (Copyright © 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Purpose: To assess and correlate pulmonary involvement and outcome of SARS-CoV-2 pneumonia with the degree of coronary plaque burden based on the CAC-DRS classification (Coronary Artery Calcium Data and Reporting System)., Methods: This retrospective study included 142 patients with confirmed SARS-CoV-2 pneumonia (58 ± 16 years; 57 women) who underwent non-contrast CT between January 2020 and August 2021 and were followed up for 129 ± 72 days. One experienced blinded radiologist analyzed CT series for the presence and extent of calcified plaque burden according to the visual and quantitative HU-based CAC-DRS Score. Pulmonary involvement was automatically evaluated with a dedicated software prototype by another two experienced radiologists and expressed as Opacity Score., Results: CAC-DRS Scores derived from visual and quantitative image evaluation correlated well with the Opacity Score (r=0.81, 95% CI 0.76-0.86, and r=0.83, 95% CI 0.77-0.89, respectively; p<0.0001) with higher correlation in severe than in mild stage SARS-CoV-2 pneumonia (p<0.0001). Combined, CAC-DRS and Opacity Scores revealed great potential to discriminate fatal outcomes from a mild course of disease (AUC 0.938, 95% CI 0.89-0.97), and the need for intensive care treatment (AUC 0.801, 95% CI 0.77-0.83). Visual and quantitative CAC-DRS Scores provided independent prognostic information on all-cause mortality (p=0.0016 and p<0.0001, respectively), both in univariate and multivariate analysis., Conclusions: Coronary plaque burden is strongly correlated to pulmonary involvement, adverse outcome, and death due to respiratory failure in patients with SARS-CoV-2 pneumonia, offering great potential to identify individuals at high risk., (Copyright © 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Objectives: To assess the impact of noise-optimised virtual monoenergetic imaging (VMI+) on image quality and diagnostic evaluation in abdominal dual-energy CT scans with impaired portal-venous contrast., Methods: We screened 11,746 patients who underwent portal-venous abdominal dual-energy CT for cancer staging between 08/2014 and 11/2019 and identified those with poor portal-venous contrast.Standard linearly-blended image series and VMI+ image series at 40, 50, and 60 keV were reconstructed. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of abdominal organs and vascular structures were calculated. Image noise, image contrast and overall image quality were rated by three radiologists using 5-point Likert scale., Results: 452 of 11,746 (4%) exams were poorly opacified. We excluded 190 cases due to incomplete datasets or multiple exams of the same patient with a final study group of 262. Highest CNR values in all abdominal organs (liver, 6.4 ± 3.0; kidney, 17.4 ± 7.5; spleen, 8.0 ± 3.5) and vascular structures (aorta, 16.0 ± 7.3; intrahepatic vein, 11.3 ± 4.7; portal vein, 15.5 ± 6.7) were measured at 40 keV VMI+ with significantly superior values compared to all other series. In subjective analysis, highest image contrast was seen at 40 keV VMI+ (4.8 ± 0.4), whereas overall image quality peaked at 50 keV VMI+ (4.2 ± 0.5) with significantly superior results compared to all other series ( p < 0.001)., Conclusions: Image reconstruction using VMI+ algorithm at 50 keV significantly improves image contrast and image quality of originally poorly opacified abdominal CT scans and reduces the number of non-diagnostic scans., Advances in Knowledge: We validated the impact of VMI+ reconstructions in poorly attenuated DECT studies of the abdomen in a big data cohort., (© 2022 The Authors. Published by the British Institute of Radiology.)

Objectives: To evaluate the predictive value of volumetric bone mineral density (BMD) assessment of the lumbar spine derived from phantomless dual-energy CT (DECT)-based volumetric material decomposition as an indicator for the 2-year occurrence risk of osteoporosis-associated fractures., Methods: L1 of 92 patients (46 men, 46 women; mean age, 64 years, range, 19-103 years) who had undergone third-generation dual-source DECT between 01/2016 and 12/2018 was retrospectively analyzed. For phantomless BMD assessment, dedicated DECT postprocessing software using material decomposition was applied. Digital files of all patients were sighted for 2 years following DECT to obtain the incidence of osteoporotic fractures. Receiver operating characteristic (ROC) analysis was used to calculate cut-off values and logistic regression models were used to determine associations of BMD, sex, and age with the occurrence of osteoporotic fractures., Results: A DECT-derived BMD cut-off of 93.70 mg/cm 3 yielded 85.45% sensitivity and 89.19% specificity for the prediction to sustain one or more osteoporosis-associated fractures within 2 years after BMD measurement. DECT-derived BMD was significantly associated with the occurrence of new fractures (odds ratio of 0.8710, 95% CI, 0.091-0.9375, p < .001), indicating a protective effect of increased DECT-derived BMD values. Overall AUC was 0.9373 (CI, 0.867-0.977, p < .001) for the differentiation of patients who sustained osteoporosis-associated fractures within 2 years of BMD assessment., Conclusions: Retrospective DECT-based volumetric BMD assessment can accurately predict the 2-year risk to sustain an osteoporosis-associated fracture in at-risk patients without requiring a calibration phantom. Lower DECT-based BMD values are strongly associated with an increased risk to sustain fragility fractures., Key Points: •Dual-energy CT-derived assessment of bone mineral density can identify patients at risk to sustain osteoporosis-associated fractures with a sensitivity of 85.45% and a specificity of 89.19%. •The DECT-derived BMD threshold for identification of at-risk patients lies above the American College of Radiology (ACR) QCT guidelines for the identification of osteoporosis (93.70 mg/cm 3 vs 80 mg/cm 3 )., (© 2021. The Author(s).)

Objectives: To investigate the diagnostic accuracy of color-coded contrast-enhanced dual-energy CT virtual noncalcium (VNCa) reconstructions for the assessment of lumbar disk herniation compared to unenhanced VNCa imaging., Methods: A total of 91 patients were retrospectively evaluated (65 years ± 16; 43 women) who had undergone third-generation dual-source dual-energy CT and 3.0-T MRI within an examination interval up to 3 weeks between November 2019 and December 2020. Eight weeks after assessing unenhanced color-coded VNCa reconstructions for the presence and degree of lumbar disk herniation, corresponding contrast-enhanced portal venous phase color-coded VNCa reconstructions were independently analyzed by the same five radiologists. MRI series were additionally analyzed by one highly experienced musculoskeletal radiologist and served as reference standard., Results: MRI depicted 210 herniated lumbar disks in 91 patients. VNCa reconstructions derived from contrast-enhanced CT scans showed similar high overall sensitivity (93% vs 95%), specificity (94% vs 95%), and accuracy (94% vs 95%) for the assessment of lumbar disk herniation compared to unenhanced VNCa images (all p > .05). Interrater agreement in VNCa imaging was excellent for both, unenhanced and contrast-enhanced CT (κ = 0.84 vs κ = 0.86; p > .05). Moreover, ratings for diagnostic confidence, image quality, and noise differed not significantly between unenhanced and contrast-enhanced VNCa series (all p > .05)., Conclusions: Color-coded VNCa reconstructions derived from contrast-enhanced dual-energy CT yield similar diagnostic accuracy for the depiction of lumbar disk herniation compared to unenhanced VNCa imaging and therefore may improve opportunistic retrospective lumbar disk herniation assessment, particularly in case of staging CT examinations., Key Points: • Color-coded dual-source dual-energy CT virtual noncalcium (VNCa) reconstructions derived from portal venous phase yield similar high diagnostic accuracy for the assessment of lumbar disk herniation compared to unenhanced VNCa CT series (94% vs 95%) with MRI serving as a standard of reference. • Diagnostic confidence, image quality, and noise levels differ not significantly between unenhanced and contrast-enhanced portal venous phase VNCa dual-energy CT series. • Dual-source dual-energy CT might have the potential to improve opportunistic retrospective lumbar disk herniation assessment in CT examinations performed for other indications through reconstruction of VNCa images., (© 2021. The Author(s).)

Background: High-resolution computed tomography (HRCT) is essential in narrowing the possible differential diagnoses of diffuse and interstitial lung diseases., Purpose: To investigate the value of a novel computer-based decision support system (CDSS) for facilitating diagnosis of diffuse lung diseases at HRCT., Material and Methods: A CDSS was developed that includes about 100 different illustrations of the most common HRCT signs and patterns and describes the corresponding pathologies in detail. The logical set-up of the software facilitates a structured evaluation. By selecting one or more CT patterns, the program generates a ranked list of the most likely differential diagnoses. Three independent and blinded radiology residents initially evaluated 40 cases with different lung diseases alone; after at least 12 weeks, observers re-evaluated all cases using the CDSS., Results: In 40 patients, a total of 113 HRCT patterns were evaluated. The percentage of correctly classified patterns was higher with CDSS (96.8%) compared to assessment without CDSS (90.3%; P  < 0.01). Moreover, the percentage of correct diagnosis (81.7% vs. 64.2%) and differential diagnoses (89.2% vs. 38.3%) were superior with CDSS compared to evaluation without CDSS (both P  < 0.01)., Conclusion: Addition of a CDSS using a structured approach providing explanations of typical HRCT patterns and graphical illustrations significantly improved the performance of trainees in characterizing and correctly identifying diffuse lung diseases.

Objectives: To compare dual-energy CT (DECT) and MRI for assessing presence and extent of traumatic bone marrow edema (BME) and fracture line depiction in acute vertebral fractures., Methods: Eighty-eight consecutive patients who underwent dual-source DECT and 3-T MRI of the spine were retrospectively analyzed. Five radiologists assessed all vertebrae for presence and extent of BME and for identification of acute fracture lines on MRI and, after 12 weeks, on DECT series. Additionally, image quality, image noise, and diagnostic confidence for overall diagnosis of acute vertebral fracture were assessed. Quantitative analysis of CT numbers was performed by a sixth radiologist. Two radiologists analyzed MRI and grayscale DECT series to define the reference standard., Results: For assessing BME presence and extent, DECT showed high sensitivity (89% and 84%, respectively) and specificity (98% in both), and similarly high diagnostic confidence compared to MRI (2.30 vs. 2.32; range 0-3) for the detection of BME (p = .72). For evaluating acute fracture lines, MRI achieved high specificity (95%), moderate sensitivity (76%), and a significantly lower diagnostic confidence compared to DECT (2.42 vs. 2.62, range 0-3) (p < .001). A cutoff value of - 0.43 HU provided a sensitivity of 89% and a specificity of 90% for diagnosing BME, with an overall AUC of 0.96., Conclusions: DECT and MRI provide high diagnostic confidence and image quality for assessing acute vertebral fractures. While DECT achieved high overall diagnostic accuracy in the analysis of BME presence and extent, MRI provided moderate sensitivity and lower confidence for evaluating fracture lines., Key Points: • In the setting of spinal trauma, dual-energy CT (DECT) is highly accurate in the evaluation of acute vertebral fractures and bone marrow edema presence and extent. • MRI provides moderate sensitivity and lower diagnostic confidence for the depiction of acute fracture lines, when compared to DECT, which might result in potentially inaccurate and underestimated severity assessment of injuries in certain cases when no fracture lines are visible on MRI. • DECT may represent a valid imaging alternative to MRI in specific settings of acute spinal trauma and in follow-up examinations, especially in elderly or unstable patients and in cases of subtle or complex orientated fracture lines., (© 2021. The Author(s).)

Objectives: To determine the diagnostic accuracy of dual-energy CT (DECT) virtual noncalcium (VNCa) reconstructions for assessing thoracic disk herniation compared to standard grayscale CT., Methods: In this retrospective study, 87 patients (1131 intervertebral disks; mean age, 66 years; 47 women) who underwent third-generation dual-source DECT and 3.0-T MRI within 3 weeks between November 2016 and April 2020 were included. Five blinded radiologists analyzed standard DECT and color-coded VNCa images after a time interval of 8 weeks for the presence and degree of thoracic disk herniation and spinal nerve root impingement. Consensus reading of independently evaluated MRI series served as the reference standard, assessed by two separate experienced readers. Additionally, image ratings were carried out by using 5-point Likert scales., Results: MRI revealed a total of 133 herniated thoracic disks. Color-coded VNCa images yielded higher overall sensitivity (624/665 [94%; 95% CI, 0.89-0.96] vs 485/665 [73%; 95% CI, 0.67-0.80]), specificity (4775/4990 [96%; 95% CI, 0.90-0.98] vs 4066/4990 [82%; 95% CI, 0.79-0.84]), and accuracy (5399/5655 [96%; 95% CI, 0.93-0.98] vs 4551/5655 [81%; 95% CI, 0.74-0.86]) for the assessment of thoracic disk herniation compared to standard CT (all p < .001). Interrater agreement was excellent for VNCa and fair for standard CT (ϰ = 0.82 vs 0.37; p < .001). In addition, VNCa imaging achieved higher scores regarding diagnostic confidence, image quality, and noise compared to standard CT (all p < .001)., Conclusions: Color-coded VNCa imaging yielded substantially higher diagnostic accuracy and confidence for assessing thoracic disk herniation compared to standard CT., Key Points: • Color-coded VNCa reconstructions derived from third-generation dual-source dual-energy CT yielded significantly higher diagnostic accuracy for the assessment of thoracic disk herniation and spinal nerve root impingement compared to standard grayscale CT. • VNCa imaging provided higher diagnostic confidence and image quality at lower noise levels compared to standard grayscale CT. • Color-coded VNCa images may potentially serve as a viable imaging alternative to MRI under circumstances where MRI is unavailable or contraindicated., (© 2021. The Author(s).)

Background: Serum protein electrophoresis is one of the core investigations for screening for monoclonal proteins. Among the available capillary systems, the Helena V8 system has been evaluated in a limited number of studies., Methods: In total, 310 sera samples were assessed on the Helena V8 system and compared with the Sebia Capillarys instrument. Abnormalities suggestive of monoclonal proteins were confirmed by immunofixation. Imprecision studies and reference intervals were determined., Results: The imprecision of the Helena V8 was inferior or equal to 5.8%. The mean bias of Helena V8 vs Sebia Capillarys was about -0.9 g/L for albumin; -0.2 g/L for alpha-1; 1.1 g/L for alpha-2; -0.2 g/L for beta; 0.3 g/L for gamma; -0.5 g/L for monoclonal protein in beta; and 0.3 g/L for monoclonal protein in gamma. Among the 56 samples with monoclonal proteins confirmed by immunofixation, all were seen on both methods, with only 1 discordant result at a cutoff of 5.0 g/L. Reference intervals were statistically different between the 2 analyzers, except for the beta fraction., Conclusions: Our evaluation confirms the good analytical performance of the Helena V8 analyzer as a suitable alternative to the Sebia Capillarys instrument., (© American Association for Clinical Chemistry 2021. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Dual-source dual-energy computed tomography (DECT) offers the potential for opportunistic osteoporosis screening by enabling phantomless bone mineral density (BMD) quantification. This study sought to assess the accuracy and precision of volumetric BMD measurement using dual-source DECT in comparison to quantitative CT (QCT)., Methods: A validated spine phantom consisting of three lumbar vertebra equivalents with 50 (L1), 100 (L2), and 200 mg/cm 3 (L3) calcium hydroxyapatite (HA) concentrations was scanned employing third-generation dual-source DECT and QCT. While BMD assessment based on QCT required an additional standardised bone density calibration phantom, the DECT technique operated by using a dedicated postprocessing software based on material decomposition without requiring calibration phantoms. Accuracy and precision of both modalities were compared by calculating measurement errors. In addition, correlation and agreement analyses were performed using Pearson correlation, linear regression, and Bland-Altman plots., Results: DECT-derived BMD values differed significantly from those obtained by QCT (p < 0.001) and were found to be closer to true HA concentrations. Relative measurement errors were significantly smaller for DECT in comparison to QCT (L1, 0.94% versus 9.68%; L2, 0.28% versus 5.74%; L3, 0.24% versus 3.67%, respectively). DECT demonstrated better BMD measurement repeatability compared to QCT (coefficient of variance < 4.29% for DECT, < 6.74% for QCT). Both methods correlated well to each other (r = 0.9993; 95% confidence interval 0.9984-0.9997; p < 0.001) and revealed substantial agreement in Bland-Altman plots., Conclusions: Phantomless dual-source DECT-based BMD assessment of lumbar vertebra equivalents using material decomposition showed higher diagnostic accuracy compared to QCT., (© 2021. The Author(s).)

Background: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans., Methods: One hundred patients (median age, 69 years; range, 19-94 years) who received CT scans of the thoracolumbar spine and blood-testing for hemoglobin and hematocrit levels ± 24 h between 08/2018 and 11/2019 were retrospectively included. Intraaortic blood was segmented using a spherical volume of interest of 1 cm diameter with consecutive radiomic analysis applying PyRadiomics software. Feature selection was performed applying analysis of correlation and collinearity. The final feature set was obtained to differentiate moderate-to-severe anemia. Random forest machine learning was applied and predictive performance was assessed. A decision-tree was obtained to propose a cut-off value of CT Hounsfield units (HU)., Results: High correlation with hemoglobin and hematocrit levels was shown for first-order radiomic features (p < 0.001 to p = 0.032). The top 3 features showed high correlation to hemoglobin values (p) and minimal collinearity (r) to the top ranked feature Median (p < 0.001), Energy (p = 0.002, r = 0.387), Minimum (p = 0.032, r = 0.437). Median (p < 0.001) and Minimum (p = 0.003) differed in moderate-to-severe anemia compared to non-anemic state. Median yielded superiority to the combination of Median and Minimum (p(AUC) = 0.015, p(precision) = 0.017, p(accuracy) = 0.612) in the predictive performance employing random forest analysis. A Median HU value ≤ 36.5 indicated moderate-to-severe anemia (accuracy = 0.90, precision = 0.80)., Conclusions: First-order radiomic features correlate with hemoglobin levels and may be feasible for the prediction of moderate-to-severe anemia. High dimensional radiomic features did not aid augmenting the data in our exemplary use case of intraluminal blood component assessment. Trial registration Retrospectively registered., (© 2021. The Author(s).)

Objectives: To investigate the diagnostic accuracy of color-coded dual-energy CT virtual non-calcium (VNCa) reconstructions for the assessment of bone marrow edema (BME) of the scaphoid in patients with acute wrist trauma., Methods: Our retrospective study included data from 141 patients (67 women, 74 men; mean age 43 years, range 19-80 years) with acute wrist trauma who had undergone third-generation dual-source dual-energy CT and 3-T MRI within 7 days. Eight weeks after assessment of conventional grayscale dual-energy CT scans for the presence of fractures, corresponding color-coded VNCa reconstructions were independently analyzed by the same six radiologists for the presence of BME. CT numbers on VNCa reconstructions were evaluated by a seventh radiologist. Consensus reading of MRI series by two additional radiologists served as the reference standard., Results: MRI depicted 103 scaphoideal zones with BME in 76 patients. On qualitative analysis, VNCa images yielded high overall sensitivity (580/618 [94%]), specificity (1880/1920 [98%]), and accuracy (2460/2538 [97%]) for assessing BME as compared with MRI as reference standard. The interobserver agreement was excellent (κ = 0.98). CT numbers derived from VNCa images were significantly different in zones with and without edema (p < 0.001). A cutoff value of - 46 Hounsfield units provided a sensitivity of 91% and specificity of 97% for differentiating edematous scaphoid lesions. Receiver operating characteristic curve analysis revealed an overall area under the curve of 0.98., Conclusions: Qualitative and quantitative analyses showed excellent diagnostic accuracy of color-coded VNCa reconstructions for assessing traumatic BME of the scaphoid compared to MRI., Key Points: • Color-coded virtual non-calcium (VNCa) reconstructions yield excellent diagnostic accuracy in assessing bone marrow edema of the scaphoid. • VNCa imaging enables detection of non-displaced fractures that are occult on standard grayscale CT. • Diagnostic confidence is comparable between VNCa imaging and MRI.

Rationale and Objectives: To evaluate the impact of noise-optimized virtual monoenergetic imaging (VMI) on lesion demarcation and measuring accuracy of hypoattenuating liver metastases in patients with fatty liver disease compared to standard reconstructions., Materials and Methods: Twenty-eight patients (mean age 62.2 ± 7.7 years) with fatty liver disease and hypoattenuating liver metastases who underwent unenhanced and contrast-enhanced portal-venous dual-energy CT (DECT) were enrolled. Standard linearly blended and VMI series were reconstructed in 10-keV intervals. Lesion-to-parenchyma contrast-to-noise ratio (CNR) was calculated and the best VMI series was further investigated in a subjective evaluation of overall image quality and lesion demarcation. Size measurements were performed independently by measuring all hypodense lesions (n = 58) twice in a predefined sequence. Inter- and intra-rater agreement was assessed using intra-class correlation coefficient (ICC) statistics., Results: The calculated CNR was greatest at 40-keV VMI (4.3 ± 2.6), significantly higher compared to standard reconstructions (2.9 ± 1.9; p < 0.001). Subjective ratings for overall image quality showed no significant difference between the 2 reconstruction techniques (both medians 4; p = 0.147), while lesion margin demarcation was found to be superior for 40-keV VMI (median 5; p ≤ 0.001). Inter- (ICC, 0.98 for 40-keV VMI; ICC, 0.93 for standard reconstruction) and intra-rater (ICC, 0.99 for 40-keV VMI; ICC, 0.94 for standard image series) analysis showed an excellent agreement for lesion measurements in both reconstruction techniques., Conclusion: Noise-optimized VMI reconstructions significantly improve contrast and lesion demarcation of hypoattenuating liver metastases in patients with the fatty liver disease compared to standard reconstruction., (Copyright © 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Objectives: To compare radiation dose and image quality of single-energy (SECT) and dual-energy (DECT) head and neck CT examinations performed with second- and third-generation dual-source CT (DSCT) in matched patient cohorts., Methods: 200 patients (mean age 55.1 ± 16.9 years) who underwent venous phase head and neck CT with a vendor-preset protocol were retrospectively divided into four equal groups ( n = 50) matched by gender and BMI: second (Group A, SECT, 100-kV; Group B, DECT, 80/Sn140-kV), and third-generation DSCT (Group C, SECT, 100-kV; Group D, DECT, 90/Sn150-kV). Assessment of radiation dose was performed for an average scan length of 27 cm. Contrast-to-noise ratio measurements and dose-independent figure-of-merit calculations of the submandibular gland, thyroid, internal jugular vein, and common carotid artery were analyzed quantitatively. Qualitative image parameters were evaluated regarding overall image quality, artifacts and reader confidence using 5-point Likert scales., Results: Effective radiation dose (ED) was not significantly different between SECT and DECT acquisition for each scanner generation ( p = 0.10). Significantly lower effective radiation dose ( p < 0.01) values were observed for third-generation DSCT groups C (1.1 ± 0.2 mSv) and D (1.0 ± 0.3 mSv) compared to second-generation DSCT groups A (1.8 ± 0.1 mSv) and B (1.6 ± 0.2 mSv). Figure-of-merit/contrast-to-noise ratio analysis revealed superior results for third-generation DECT Group D compared to all other groups. Qualitative image parameters showed non-significant differences between all groups ( p > 0.06)., Conclusion: Contrast-enhanced head and neck DECT can be performed with second- and third-generation DSCT systems without radiation penalty or impaired image quality compared with SECT, while third-generation DSCT is the most dose efficient acquisition method., Advances in Knowledge: Differences in radiation dose between SECT and DECT of the dose-vulnerable head and neck region using DSCT systems have not been evaluated so far. Therefore, this study directly compares radiation dose and image quality of standard SECT and DECT protocols of second- and third-generation DSCT platforms.

Objectives: To evaluate the performance of radiomic features extracted from high-resolution computed tomography (HRCT) for the differentiation between cholesteatoma and middle ear inflammation (MEI), and to investigate the impact of post-reconstruction harmonization and data resampling., Methods: One hundred patients were included in this retrospective dual-center study: 48 with histology-proven cholesteatoma (center A: 23; center B: 25) and 52 with MEI (A: 27; B: 25). Radiomic features (co-occurrence and run-length matrix, absolute gradient, autoregressive model, Haar wavelet transform) were extracted from manually defined 2D-ROIs. The ten best features for lesion differentiation were selected using probability of error and average correlation coefficients. A multi-layer perceptron feed-forward artificial neural network (MLP-ANN) was used for radiomics-based classification, with histopathology serving as the reference standard (70% of cases for training, 30% for validation). The analysis was performed five times each on (a) unmodified data and on data that were (b) resampled to the same matrix size, and (c) corrected for acquisition protocol differences using ComBat harmonization., Results: Using unmodified data, the MLP-ANN classification yielded an overall median area under the receiver operating characteristic curve (AUC) of 0.78 (0.72-0.84). Using original data from center A and resampled data from center B, an overall median AUC of 0.88 (0.82-0.99) was yielded, while using ComBat harmonized data, an overall median AUC of 0.89 (0.79-0.92) was revealed., Conclusion: Radiomic features extracted from HRCT differentiate between cholesteatoma and MEI. When using multi-centric data obtained with differences in CT acquisition parameters, data resampling and ComBat post-reconstruction harmonization clearly improve radiomics-based lesion classification., Key Points: • Unenhanced high-resolution CT coupled with radiomics analysis may be useful for the differentiation between cholesteatoma and middle ear inflammation. • Pooling of data extracted from inhomogeneous CT datasets does not appear meaningful without further post-processing. • When using multi-centric CT data obtained with differences in acquisition parameters, post-reconstruction harmonization and data resampling clearly improve radiomics-based soft-tissue differentiation.

Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.

Objectives: The aim of this study was to investigative the diagnostic accuracy of colored dual-energy computed tomography (CT) virtual noncalcium (VNCa) series for analyzing cervical disk herniation compared with standard gray-scale CT images, with magnetic resonance imaging (MRI) serving as standard of reference., Materials and Methods: Data from 57 patients who underwent noncontrast dual-source CT and 3.0-Tesla (T) MRI within 2 weeks between January 2017 and December 2018 were retrospectively analyzed. Five radiologists analyzed standard gray-scale dual-energy CT scans for the presence and degree of cervical disk herniation and spinal nerve root impingement. Readers reassessed scans after 8 weeks using colored VNCa series. Two experienced radiologists set the reference standard in consensus MRI reading sessions. Primary indices of diagnostic accuracy for both CT approaches were sensitivity and specificity, which were compared by application of the McNemar test., Results: A total of 57 patients (mean age, 64 ± 11 years; 30 women) were evaluated (337 intervertebral disks). Magnetic resonance imaging indicated a total of 103 cervical disk herniations. The VNCa reconstructions had higher overall sensitivity compared with gray-scale CT (487/515 [95%; 95% confidence interval (CI), 91%-98%] vs 392/515 [76%; 95% CI, 70%-83%]), as well as higher specificity (1107/1170 [95%; 95% CI, 90%-99%] vs 906/1170 [77%; 95% CI, 72%-82%]) for assessing cervical disk herniation (all P < 0.001). The VNCa reconstructions had higher diagnostic accuracy for analyzing spinal nerve root impingement in comparison with gray-scale CT (sensitivity, 195/230 [85%; 95% CI, 79%-90%] vs 115/230 [50%; 95% CI, 40%-59%]; specificity, 1430/1455 [98%; 95% CI, 94%-100%] vs 1325/1455 [91%; 95% CI, 88%-98%]; accuracy, 1625/1685 [96%; 95% CI, 93%-99%] vs 1440/1685 [86%; 95% CI, 82%-90%]; all P < 0.001)., Conclusions: Color-coded VNCa series improved the diagnostic accuracy for assessing cervical disk herniation and spinal nerve root impingement compared with standard gray-scale CT., Competing Interests: Conflicts of interest and sources of funding: C.B. received speaking fees from Siemens Healthineers. I.Y. received a speaking fee from Siemens Healthineers. J.L.W. received speaking fees from Siemens Healthcare and GE Healthcare and is an employee of Siemens Healthineers. M.H.A. received speaking fees from Siemens Healthineers and Bracco. The other authors have no potential conflict of interest to disclose., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: To investigate whether minimum intensity projection (MinIP) reconstructions enable more accurate depiction of pulmonary ground-glass opacity (GGO) compared to standard transverse sections and multiplanar reformat (MPR) series in patients with suspected coronavirus disease 2019 (COVID-19)., Method: In this multinational study, chest CT scans of 185 patients were retrospectively analyzed. Diagnostic accuracy, diagnostic confidence, image quality regarding the assessment of GGO, as well as subjective time-efficiency of MinIP and standard MPR series were analyzed based on the assessment of six radiologists. In addition, the suitability for COVID-19 evaluation, image quality regarding GGO and subjective time-efficiency in clinical routine was assessed by five clinicians., Results: The reference standard revealed a total of 149 CT scans with pulmonary GGO. MinIP reconstructions yielded significantly higher sensitivity (99.9 % vs 95.6 %), specificity (95.8 % vs 86.1 %) and accuracy (99.1 % vs 93.8 %) for assessing of GGO compared with standard MPR series. MinIP reconstructions achieved significantly higher ratings by radiologists concerning diagnostic confidence (medians, 5.00 vs 4.00), image quality (medians, 4.00 vs 4.00), contrast between GGO and unaffected lung parenchyma (medians, 5.00 vs 4.00) as well as subjective time-efficiency (medians, 5.00 vs 4.00) compared with MPR-series (all P < .001). Clinicians preferred MinIP reconstructions for COVID-19 assessment (medians, 5.00 vs 3.00), image quality regarding GGO (medians, 5.00 vs 3.00) and subjective time-efficiency in clinical routine (medians, 5.00 vs 3.00)., Conclusions: MinIP reconstructions improve the assessment of COVID-19 in chest CT compared to standard images and may be suitable for routine application., (Copyright © 2020 Elsevier B.V. All rights reserved.)