Background/Objectives: A ratio of subcutaneous adipose tissue to muscle mass may be more informative than defining low subcutaneous adipose tissue and muscle mass separately. The objective of this study was to determine which ultrasound measurement points in the upper and lower extremities predict the subcutaneous adipose tissue (SAT)-to-muscle ratio as measured by gold-standard computed tomography (CT) at the third lumbar vertebra (L3) level. Methods: Two hundred hospitalised patients (41% female; median (Q1-Q3) age: 61.3 (51.0-70.1) years) who underwent an abdominal CT scan for any clinical reason within 48 h prior to extremity ultrasound were included in this prospective observational study conducted from 2017 to 2019. Ultrasound measurements of subcutaneous adipose tissue and muscle thickness were obtained at three measuring points on the thigh and two on the upper arm. On the CT scan at the L3 level, subcutaneous (SAT) and visceral adipose tissue and skeletal muscle area were measured. A linear LASSO (Least Absolute Shrinkage and Selection Operator) model was used to identify which ultrasound sites best predicted the CT L3 SAT-to-muscle ratio. Results: Height, weight, sex, SAT-to-muscle ratio at four ultrasound measuring points and abdominal circumference predicted the CT SAT-to-muscle ratio in the LASSO model (R2 = 0.70; cross-validated R2 = 0.63; p values are not reported in LASSO regression and R2 is used instead). The upper-arm anterolateral ultrasound site most strongly influenced the CT SAT-to-muscle ratio (estimate × standard deviation of predictor: 0.24). Conclusions: The CT SAT-to-muscle ratio at the L3 level can be predicted non-invasively using bedside ultrasound, particularly at the anterolateral measuring point of the upper arm. Bedside ultrasound assessment of the ratio of subcutaneous adipose tissue to muscle on the anterolateral upper arm provides a within-patient comparison of body compartments.

To conduct an intrapatient comparison of ultra-low-dose computed tomography (ULDCT) and standard-of-care-dose CT (SDCT) of the chest in terms of the diagnostic accuracy of ULDCT and intrareader agreement in patients with post-COVID conditions. We prospectively included 153 consecutive patients with post-COVID-19 conditions. All participants received an SDCT and an additional ULDCT scan of the chest. SDCTs were performed with standard imaging parameters and ULDCTs at a fixed tube voltage of 100 kVp (with tin filtration), 50 ref. mAs (dose modulation active), and iterative reconstruction algorithm level 5 of 5. All CT scans were separately evaluated by four radiologists for the presence of lung changes and their consistency with post-COVID lung abnormalities. Radiation dose parameters and the sensitivity, specificity, and accuracy of ULDCT were calculated. Of the 153 included patients (mean age 47.4 ± 15.3 years; 48.4

9561 Background: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of metastatic melanoma with objective response rates of 40-58%. However, reliable biomarkers to predict treatment response are lacking. Tumor tissue methylation profiles were recently proposed to have predictive value in various solid organ tumor entities. Methods: Patients with metastatic melanoma, American Joint Committee on Cancer (AJCC; 8 th Edition) stage IV, receiving first-line ICI-based therapy, were retrospectively identified and formalin-fixed paraffin-embedded tumor tissue samples (FFPE) prior to ICI therapy were retrieved. We analyzed DNA methylation profiles of > 850.000 CpG sites in tumor specimens by Infinium MethylationEPIC microarrays. DNA methylation profiles were then correlated with radiological response (iRECIST). Results: 71 patients with metastatic melanoma (44 (62.0%) male, 27 (38.0%) female) were investigated; median progression free survival (PFS) was 8.5 months (range: 0 – 104.1 months) and median overall survival (OS) was 30.6 months (range: 0 – 104.1 months), respectively. 29 (40.8%) patients achieved an objective response to ICIs. Microarray analyses revealed a methylation signature including mainly hypomethylation, corresponding to the response to ICIs. Based on the 500 mostly differentially methylated genes, a total of 3 clusters were identified with the majority of responders being in cluster 2 (12/12) and 3 (12/22). The predictive performance of the methylation signature was high with 80% sensitivity, 81% specificity, and an AUC of 0.853. Conclusions: Our findings suggest that tumor DNA methylation profiling may be useful to predict response to ICIs in patients with metastatic melanoma.

Background: Metal artifacts caused by hip arthroplasty stems limit the diagnostic value of computed tomography (CT) in the evaluation of periprosthetic fractures or implant loosening. The aim of this ex vivo study was to evaluate the influence of different scan parameters and metal artifact algorithms on image quality in the presence of hip stems. Methods: Nine femoral stems, 6 uncemented and 3 cemented, that had been implanted in subjects during their lifetimes were exarticulated and investigated after death and anatomical body donation. Twelve CT protocols consisting of single-energy (SE) and single-source consecutive dual-energy (DE) scans with and without an iterative metal artifact reduction algorithm (iMAR; Siemens Healthineers) and/or monoenergetic reconstructions were compared. Streak and blooming artifacts as well as subjective image quality were evaluated for each protocol. Results: Metal artifact reduction with iMAR significantly reduced the streak artifacts in all investigated protocols (p = 0.001 to 0.01). The best subjective image quality was observed for the SE protocol with a tin filter and iMAR. The least streak artifacts were observed for monoenergetic reconstructions of 110, 160, and 190 keV with iMAR (standard deviation of the Hounsfield units: 151.1, 143.7, 144.4) as well as the SE protocol with a tin filter and iMAR (163.5). The smallest virtual growth was seen for the SE with a tin filter and without iMAR (4.40 mm) and the monoenergetic reconstruction of 190 keV without iMAR (4.67 mm). Conclusions: This study strongly suggests that metal artifact reduction algorithms (e.g., iMAR) should be used in clinical practice for imaging of the bone-implant interface of prostheses with either an uncemented or cemented femoral stem. Among the iMAR protocols, the SE protocol with 140 kV and a tin filter produced the best subjective image quality. Furthermore, this protocol and DE monoenergetic reconstructions of 160 and 190 keV with iMAR achieved the lowest levels of streak and blooming artifacts. Level of Evidence: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

The collection of the Narrenturm in Vienna houses and maintains more than 50,000 objects including approximately 1200 teratological specimens; making it one of the biggest collections of specimens from human origin in Europe. The existence of this magnificent collection-representing an important resource for dysmorphology research, mostly awaiting contemporary diagnoses-is not widely known in the scientific community. Here, we show that the Narrenturm harbors a wealth of specimens with (exceptionally) rare congenital anomalies. These museums can be seen as physical repositories of human malformation, covering hundreds of years of dedicated collecting and preserving, thereby creating unique settings that can be used to expand our knowledge of developmental conditions that have to be preserved for future generations of scientists.

Background:Ultra-low-dose CT (ULDCT) examinations of the chest at only twice the radiation dose of a chest X-ray (CXR) now offer a valuable imaging alternative to CXR. This trial prospectively compares ULDCT and CXR for the detection rate of diagnoses and their clinical relevance in a low-prevalence cohort of non-traumatic emergency department patients. Methods:In this prospective crossover cohort trial, 294 non-traumatic emergency department patients with a clinically indicated CXR were included between May 2nd and November 26th of 2019 (www.clinicaltrials.gov: NCT03922516). All participants received both CXR and ULDCT, and were randomized into two arms with inverse reporting order. The detection rate of CXR was calculated from 'arm CXR' (n = 147; CXR first), and of ULDCT from 'arm ULDCT' (n = 147; ULDCT first). Additional information reported by the second exam in each arm was documented. From all available clinical and imaging data, expert radiologists and emergency physicians built a compound reference standard, including radiologically undetectable diagnoses, and assigned each finding to one of five clinical relevance categories for the respective patient. Findings:Detection rates for main diagnoses by CXR and ULDCT (mean effective dose: 0.22 mSv) were 9.1% (CI [5.2, 15.5]; 11/121) and 20.1% (CI [14.2, 27.7]; 27/134; P = 0.016), respectively. As an additional imaging modality, ULDCT added 9.1% (CI [5.2, 15.5]; 11/121) of main diagnoses to prior CXRs, whereas CXRs did not add a single main diagnosis (0/134; P < 0.001). Notably, ULDCT also offered higher detection rates than CXR for all other clinical relevance categories, including findings clinically irrelevant for the respective emergency department visit with 78.5% (CI [74.0, 82.5]; 278/354) vs. 16.2% (CI [12.7, 20.3]; 58/359) as a primary modality and 68.2% (CI [63.3, 72.8]; 245/359) vs. 2.5% (CI [1.3, 4.7]; 9/354) as an additional imaging modality. Interpretation:In non-traumatic emergency department patients, ULDCT of the chest offered more than twice the detection rate for main diagnoses compared to CXR. Funding:The Department of Biomedical Imaging and Image-guided Therapy of Medical University of Vienna received funding from Siemens Healthineers (Erlangen, Germany) to employ two research assistants for one year.

Background Diprosopus is a rare malformation of still unclear aetiology. It describes a laterally double faced monocephalic and single-trunk individual and has to be distinguished from the variant Janus type diprosopus. Results We examined seven double-faced foetuses, five showing true diprosopus, and one each presenting as monocephalic Janiceps and parasitic conjoined twins. Four of the foetuses presented with (cranio)rachischisis, and two had secondary hydrocephaly. Three foetuses showed cerebral duplication with concordant holoprosencephaly, Dandy-Walker cyst and/or intracranial anterior encephalocele. In the Janiceps twins, cerebral duplication was accompanied by cerebral di-symmetry. In the parasitic twins the cyclopic facial aspects were suggestive of concordant holoprosencephaly. In one of the true diprosopus cases, pregnancy was achieved after intracytoplasmic sperm injection. Whole-exome sequencing, perfomed in one case, did not reveal any possible causative variants.The comparison of our double-faced foetuses to corresponding artistic representations from the Tlatilco culture allowed retrospective assignment of hairstyles to brain malformations. Conclusion Brain malformations in patients with diprosopus may not be regarded as an independent event but rather as a sequel closely related to the duplication of the notochord and neural plate and as a consequence of the cerebral and associated craniospinal structural instabilities.

Background: Acute cerebellitis (AC) in children and adolescents is an inflammatory disease of the cerebellum due to viral or bacterial infections but also autoimmune-mediated processes.Objective: To investigate the frequency of autoantibodies in serum and CSF as well as the neuroradiological features in children with AC.Material and methods: Children presenting with symptoms suggestive of AC defined as acute/subacute onset of cerebellar symptoms and MRI evidence of cerebellar inflammation or additional CSF pleocytosis, positive oligoclonal bands (OCBs), and/or presence of autoantibodies in case of negative cerebellar MRI. Children fulfilling the above-mentioned criteria and a complete data set including clinical presentation, CSF studies, testing for neuronal/cerebellar and MOG antibodies as well as MRI scans performed at disease onset were eligible for this retrospective multicenter study.Results: 36 patients fulfilled the inclusion criteria for AC (f:m =14:22, median age 5.5 years). Ataxia was the most common cerebellar symptom present in 30/36 (83 %) in addition to dysmetria (15/36) or dysarthria (13/36). A substantial number of children (21/36) also had signs of encephalitis such as somnolence or seizures. In 10/36 (28 %) children the following autoantibodies (abs) were found: MOG-abs (n = 5) in serum, GFAP alpha-abs (n = 1) in CSF, GlyR-abs (n = 1) in CSF, mGluR1-abs (n = 1) in CSF and serum. In two further children, antibodies were detected only in serum (GlyR-abs, n = 1; GFAP alpha-abs, n = 1). MRI signal alterations in cerebellum were found in 30/36 children (83 %). Additional supra-and/or infratentorial lesions were present in 12/36 children, including all five children with MOG-abs. Outcome after a median follow-up of 3 months (range: 1 a 75) was favorable with an mRS <= 2 in 24/36 (67 %) after therapy. Antibody (ab)-positive children were significantly more likely to have a better outcome than ab-negative children (p = .022).Conclusion: In nearly 30 % of children in our study with AC, a range of abs was found, underscoring that autoantibody testing in serum and CSF should be included in the work-up of a child with suspected AC. The detection of MOG-abs in AC does expand the MOGAD spectrum.

Background Studies have investigated the value of various dual-energy CT (DECT) technologies for determining renal stone composition. However, sparse multivendor comparison data exist. Purpose To compare the performance of four DECT technologies in determining renal stone composition at standard- and low-dose acquisitions. Materials and Methods This was an in vitro phantom study. Seventy-one urinary stones (size: 2.7-14.1 mm) of known chemical composition (51 calcium, four struvite, four cystine, and 12 urate) were placed in a custom-made cylindrical phantom. Consecutive scans with manufacturer-recommended protocols and dose-optimized institutional protocols (up to 80% reduction in volumetric CT dose index) were obtained with rapid kilovolt peak switching DECT (rsDECT) (n = 2), dual-source DECT (n = 2), twin-beam DECT (tbDECT) (n = 1), and dual-layer detector-based CT (dlDECT) (n = 1) scanners. The image data sets were analyzed using effective atomic number and dual-energy ratio indexes of maximally available and comparable spectra. The performance of each combination of scanner technology, method, and acquisition was assessed. Logistic regression models were used to calculate the area under the receiver operating characteristic curve (AUC). Results After image analysis, all scanners except tbDECT had an AUC greater than 0.95 in at least one acquisition in distinguishing urate from other stones. All DECT techniques were able to help differentiate calcium oxalate monohydrate stones with moderate accuracy (AUC: 0.70-0.83), and brushite was differentiated from urate with AUC greater than 0.99. There was no correlation between performance and acquisition with dose-optimized and/or vendor-recommended settings. Conclusion All four dual-energy CT (DECT) technologies enabled accurate determination of stone composition at standard- and low-dose acquisitions; however, performance varied based on the scanner parameters, DECT technique, and stone type. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Ringl and Apfaltrer in this issue.

Measuring skeletal muscle area (SMA) at the third lumbar vertebra level (L3) using computed tomography (CT) is increasingly popular for diagnosing low muscle mass. The aim was to describe the effect of the CT L3 cut-off choice on the prevalence of low muscle mass in medical and surgical patients. Two hundred inpatients, who underwent an abdominal CT scan for any reason, were included. Skeletal muscle area (SMA) was measured according to Hounsfield units on a single CT scan at the L3 level. First, we calculated sex-specific cut-offs, adjusted for height or BMI and set at mean or mean-2 SD in our population. Second, we applied published cut-offs, which differed in statistical calculation and adjustment for body stature and age. Statistical calculation of the cut-off led to a prevalence of approximately 50 vs. 1% when cut-offs were set at mean vs. mean-2 SD in our population. Prevalence varied between 5 and 86% when published cut-offs were applied (p < 0.001). The adjustment of the cut-off for the same body stature variable led to similar prevalence distribution patterns across age and BMI classes. The cut-off choice highly influenced prevalence of low muscle mass and prevalence distribution across age and BMI classes.

Background & aims: Skeletal muscle area (SMA) in the computed tomography (CT) at the third lumbar vertebra (L3) level is a proxy for whole-body muscle mass but is only performed for clinical reasons. Ultrasound is a promising tool to determine muscle mass at the bedside. It is still unclear how well ultrasound and which ultrasound measuring points can predict CT L3 SMA. Methods: This prospective observational trial included 200 non-critically ill patients, who underwent an abdominal CT scan for any clinical reason within 48 h before the ultrasound examination. Ultrasound muscle thickness was evaluated at 3 measuring points on the thigh and 2 measuring points on the upper arm with minimal compression. On the CT scan, the entire L3 SMA was measured based on Hounsfield units. Using a model selection algorithm based on the Bayesian information criterion (BIC) and clinical considerations, a linear prediction model for CT L3 SMA based on the ultrasound muscle thickness and other independent variables was fitted and assessed with cross-validation. Results: 67,5% and 32,5% of the patients were from surgical and medical wards, respectively. Mean ultrasound muscle thickness values were between 2,2 and 3,6 cm on the thigh and between 1,4 and 2,8 cm on the upper arm. All ultrasound muscle thickness values were higher in men than in women (P < 0,05). CT L3 SMA was 40 cm2 higher in men than in women (P < 0,001). The final prediction model for CT L3 SMA included the following 4 independent variables: ultrasound muscle thickness at the ventral measuring point of the thigh in the short-axis plane, sex, weight, and height. It had a similar BIC (BIC of 1515) compared to larger models with 6-8 independent variables including multiple ultrasound measuring points (BIC of 1506-1519). Additional clinical considerations to choose the final model were less time consumption when measuring a single ultrasound measuring point and better anatomical overview at the short-axis plane. The final model predicted CT L3 SMA with a R2 of 0,74 (P < 0,001) and a cross-validated R2 of 0,65. Conclusions: One single ultrasound measuring point at the thigh together with sex, height and weight very well predicts CT L3 SMA across different clinical populations. Ultrasound is a safe and bedside method to measure muscle thickness longitudinally to monitor the effects of nutrition and physical therapy. (c) 2022 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Rationale: The CT skeletal muscle area (SMA) at L3 highly correlates with whole-body muscle mass. The CT skeletal muscle density (SMD) is a measure of muscle quality. The higher the SMD is, the less myosteatosis there is. The goal was to study the variations of SMA and SMD with age in 200 non-critically ill patients.

HomeRadiologyVol. 301, No. 2 PreviousNext Reviews and CommentaryFree AccessEditorialPersonalized Reference Intervals Will Soon Become Standard in Radiology ReportsHelmut Ringl Helmut Ringl Author AffiliationsFrom the Department of Radiology, Clinics Donaustadt, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Langobardenstrasse 122, 1220 Vienna, Austria.Address correspondence to the author (e-mail: [email protected]).Helmut Ringl Published Online:Aug 17 2021https://doi.org/10.1148/radiol.2021211221MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In See also the article by Kim and Ha et al in this issue.Dr Helmut Ringl is an associate professor of radiology affiliated with the Medical University of Vienna and is head of the Radiology Department at the Clinic Donaustadt in Vienna, Austria. His research interests focus on CT, advanced visualization, and artificial intelligence.Download as PowerPointOpen in Image Viewer The basic idea of population-based reference intervals is to classify the size of an organ as normal or healthy if it is located within the range of the reference intervals. The base for the calculation of these reference intervals is the whole population, without making use of additional parameters of the individual patient, such as age or sex, which might influence the target size. However, this approach results in rather broad reference intervals that prevent this method from becoming an accurate and valuable tool for the prediction of disease. To narrow these reference intervals to reach a sufficient diagnostic sensitivity for as-yet-to-be-determined diseases, personal factors, including age, sex, and body size, must be included in the analysis of the data of the population-forming so-called personalized reference intervals.The assessment of the size of the liver and the attempt to generate personalized reference intervals for this organ date far back to when only palpation and percussion were available. In 1969, Castell et al had already described that liver dullness was greater in male patients than in female patients, with a positive correlation between liver size and height for both sexes (1). Estimation of lean body mass from height and weight measurements in each patient resulted in better correlation with liver dullness. Castell et al then wrote an equation to predict the expected range of liver dullness measured with percussion from the height and weight of a given individual.The purpose of these reference intervals is to predict or at least suggest an underlying disease process in the organ. Hepatomegaly, for example, might be caused by various diseases, such as acute hepatitis, hepatic deposition disease, or hematologic malignancies. Liver cirrhosis, on the other hand, decreases liver volumes while increasing splenic volumes due to portal hypertension. The introduction of cross-sectional methods, like CT and MRI, as well as the availability of faster computers, soon brought us the option of volumetric assessment of organs and offered unprecedented accuracy compared with one or more length measurements and their mathematical products. However, the software tools for volumetric liver and splenic assessment have been available in radiology departments of most large hospitals for decades. In practice, volumetry of these organs was limited to a narrow field of referring diagnosis, such as liver surgery or liver transplantation, because volume segmentation was a time-consuming tedious task. Another reason for the limited use of this technique was the lack of appropriate reference intervals.With the advent of deep-learning algorithms in the past several years, automated and accurate organ segmentation of abdominal CT data sets became feasible and is available as a software package from most large picture archiving and communication system and image postprocessing vendors, as well as from many start-up companies. This allows for fast assessment of the volume parameters of the liver and spleen and reduces the work radiologists must expend to a fast check of the segmentation results and, eventually, a few minor corrections. The consequent aim is to automatically include these parameters as a standard in the radiology report. In addition, this technique also allows researchers to build large personalized reference standards for volume sizes of organs to enable the clinical physicians to use these data as predictors of disease in the future.In this issue of Radiology, Kim et al (2) used such a deep-learning volume segmentation algorithm to segment the liver and spleen of 2989 healthy adult liver donors (reference group) on contrast-enhanced CT scans. Population-based and personalized reference intervals were calculated in this group. All patients were registered in a single tertiary institution in Korea. Liver disease was ruled out for all patients in the reference cohort by histologic examination of tissue obtained with US-guided percutaneous liver biopsy, as well as by clinical and laboratory examination. Exclusion criteria were a history of excessive alcohol consumption, known liver disease, and technical issues, such as motion artifacts or failure of automated organ segmentation. An additional 472 healthy liver donors with identical inclusion and exclusion criteria were used as a healthy validation group. As a disease control group, the authors included 158 patients with proven viral hepatitis B or C who also underwent US-guided percutaneous liver biopsy.While all patients in the healthy liver donor groups (both the reference group and the healthy validation group) represented a homogeneous sample well suited to build the reference intervals, Table 1 shows that the disease control group had different stages of liver fibrosis that ranged from F0 (no fibrosis) to F4 (cirrhosis) using the viral hepatitis (METAVIR) fibrosis staging system (3).The study design was well thought out and perfectly suited to reach the study aim. The CT examinations and the volume measurements using a deep-learning algorithm were appropriately used to obtain the needed data, and central 95th percentiles were used to define the reference intervals. To account for variations in the volume indexes depending on demographic and anthropometric factors, quantile regression analysis was performed to model the 2.5th and 97.5th percentiles of the volume indexes, using age, sex, height, and weight as independent covariates.In addition to the regression models, the authors provide a Web calculator (https://i-pacs.com/calculators) that can easily be used to calculate personalized reference intervals for individuals. The Web calculator webpage provides these intervals if age, height, weight, and sex is entered. If these are not available, one can use the broader population-based reference intervals presented at the bottom of the page.Finally, after calculation of the population-based intervals and personalized reference intervals, Kim et al assessed the question of whether the narrower personalized reference intervals are better suited to separate diseased organs from healthy tissue. They found that the narrower personalized reference intervals allowed for the identification of significantly more patients with a liver volume outside the normal range than the population-based intervals for the viral hepatitis group (21.5% vs 13.3%). Similar results were found for spleen volumes (29.1% vs 22.2%) and liver-to-spleen volume ratios (35.4% vs 26.6%).These results could be interpreted as sensitivity to detect liver fibrosis or hepatitis, and thus, you might ask: Why are they so low? First, patients in the disease control group had different stages of liver fibrosis due to chronic hepatitis. The volume of the liver may considerably vary depending on the stage of liver disease. Second, Pickhardt et al found in a recent study (4), that the total liver volume itself is a poor predictor of fibrosis, as it fails to account for the dynamic intrahepatic changes between Couinaud segments I–III and IV–VIII. However, sensitivity could be increased using splenic volume, as well as liver-to-spleen volume ratios. After having established the personalized reference values, finding the positive predictive value for different diseases indicates that further studies are required.Estimated standard liver volumes have been published for different geographic regions and ethnic populations (5–7). Kim et al found strong agreement between the standard liver volumes estimated with the Japanese model (5) and their observed liver volume. This suggests that these personalized reference values are likely to be valid for the Asian population, which, represents the largest proportion of the world population. However, it should be noted that the agreement with the Middle Eastern model (7) and the Western model (6) was less pronounced, indicating that these personalized reference intervals should not be used yet for the Western population. It rather raises the need for further studies with a similar method in other populations and defines the aim for further studies: to integrate ethnicity and geographic regions as parameters for future personalized reference intervals of organs. Although studies that are designed to find reference intervals require large patient cohorts, the use of artificial intelligence for volume segmentation might reduce the amount of effort required for such studies, and we might see automatically measured organ volumes with corresponding personalized reference intervals in the future in our clinical reports as a standard parameter.Disclosures of Conflicts of Interest: H.R. disclosed no relevant relationships.References1. Castell DO, O'Brien KD, Muench H, Chalmers TC. Eastimation of liver size by percussion in normal individuals. Ann Intern Med 1969;70(6):1183–1189. Crossref, Medline, Google Scholar2. Kim DW, Ha J, Lee SS, et al. Population-based and personalized reference intervals for liver and spleen volumes in healthy individuals and those with viral hepatitis. Radiology 2021.https://doi.org/10.1148/radiol.2021204183. Published online August 17, 2021. Link, Google Scholar3. Bedossa P, Poynard T. An algorithm for the grading of activity in chronic hepatitis C. The METAVIR Cooperative Study Group. Hepatology 1996;24(2):289–293. Crossref, Medline, Google Scholar4. Pickhardt PJ, Malecki K, Hunt OF, et al. Hepatosplenic volumetric assessment at MDCT for staging liver fibrosis. Eur Radiol 2017;27(7):3060–3068. Crossref, Medline, Google Scholar5. Hashimoto T, Sugawara Y, Tamura S, et al. Estimation of standard liver volume in Japanese living liver donors. J Gastroenterol Hepatol 2006;21(11):1710–1713. Crossref, Medline, Google Scholar6. Vauthey JN, Abdalla EK, Doherty DA, et al. Body surface area and body weight predict total liver volume in Western adults. Liver Transpl 2002;8(3):233–240. Crossref, Medline, Google Scholar7. Poovathumkadavil A, Leung KF, Al Ghamdi HM, Othman IeH, Meshikhes AW. Standard formula for liver volume in Middle Eastern Arabic adults. Transplant Proc 2010;42(9):3600–3605. Crossref, Medline, Google ScholarArticle HistoryReceived: May 12 2021Revision requested: May 19 2021Revision received: May 20 2021Accepted: May 21 2021Published online: Aug 17 2021Published in print: Nov 2021 FiguresReferencesRelatedDetailsCited ByComputed tomography-based measurements of normative liver and spleen volumes in childrenViniciusde Padua V. Alves, Jonathan R.Dillman, ElanchezhianSomasundaram, Zachary P.Taylor, Samuel L.Brady, BinZhang, Andrew T.Trout2022 | Pediatric Radiology, Vol. 53, No. 3Accompanying This ArticlePopulation-based and Personalized Reference Intervals for Liver and Spleen Volumes in Healthy Individuals and Those with Viral HepatitisAug 17 2021RadiologyRecommended Articles Population-based and Personalized Reference Intervals for Liver and Spleen Volumes in Healthy Individuals and Those with Viral HepatitisRadiology2021Volume: 301Issue: 2pp. 339-347Fully Automated and Explainable Liver Segmental Volume Ratio and Spleen Segmentation at CT for Diagnosing CirrhosisRadiology: Artificial Intelligence2022Volume: 4Issue: 5Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent–enhanced CT Images in the LiverRadiology2018Volume: 289Issue: 3pp. 688-697Deep Learning for Automated Normal Liver Volume EstimationRadiology2021Volume: 302Issue: 2pp. 343-344Liver Fibrosis Staging with MR Elastography: Comparison of Diagnostic Performance between Patients with Chronic Hepatitis B and Those with Other Etiologic CausesRadiology2016Volume: 280Issue: 1pp. 88-97See More RSNA Education Exhibits Imaging in Liver Fibrosis: Evolving from the Subjective to the ObjectiveDigital Posters2019Advanced Liver Imaging: Can Deep Learning Solve Its Challenges?Digital Posters2020Hepatic Elastography For Fibrosis And Steatosis Quantification: An Overview Of Applications, Limitations And Perspectives With Multimodality ImagingDigital Posters2021 RSNA Case Collection LI-RADS 5RSNA Case Collection2022Post-liver Transplant IVC StenosisRSNA Case Collection2021Hepatic SteatosisRSNA Case Collection2021 Vol. 301, No. 2 Metrics Altmetric Score PDF download

Rationale: Low muscle mass has a high impact on mortality and quality of life. Skeletal muscle area of a computed tomography (CT) scan at the L3 level highly correlates with whole-body muscle mass. Numerous CT L3 cut-offs for low muscle mass have been published. The goal was to determine the impact of the cut-off choice on the prevalence of low muscle mass.

Previous studies have shown that split-bolus protocols in virtual non-contrast (VNC) reconstructions of dual-energy computed tomography (DE-CT) significantly decrease radiation dose in patients with urinary stone disease. To evaluate the impact on kidney stone detection rate of stone composition, size, tube voltage, and iodine concentration for VNC reconstructions of DE-CT. In this prospective study, 16 kidney stones of different sizes (1.2–4.5 mm) and compositions (struvite, cystine, whewellite, brushite) were placed within a kidney phantom. Seventy-two scans with nine different iodine contrast agents/saline solutions with increasing attenuation (0–1400 HU) and different kilovoltage settings (70 kV/150 kV; 80 kV/150 kV; 90 kV/150 kV; 100 kV/150 kV) were performed. Two experienced radiologists independently rated the images for the presence and absence of stones. Multivariate classification tree analysis and descriptive statistics were used to evaluate the diagnostic performance. Classification tree analysis revealed a higher detection rate of renal calculi > 2 mm in size compared with that of renal calculi < 2 mm (84.7%; 12.7%; p < 0.001). For stones with a diameter > 2 mm, the best results were found at 70 kV/Sn 150 kV and 80 kV/Sn 150 kV in scans with contrast media attenuation of 600 HU or less, with sensitivity of 99.6% and 96.0%, respectively. A higher luminal attenuation (> 600 HU) resulted in a significantly decreased detection rate (91.8%, 0–600 HU; 70.7%, 900–1400 HU; p < 0.001). In our study setup, the detection rates were best for cystine stones. Scan protocols in DE-CT with lower tube current and lower contrast medium attenuation show excellent results in VNC for stones larger than 2 mm but have limitations for small stones. • The detection rate of virtual non-contrast reconstructions is highly dependent on the surrounding contrast medium attenuation at the renal pelvis and should be kept as low as possible, as at an attenuation higher than 600 HU the VNC reconstructions are susceptible to masking ureteral stones. • Protocols with lower tube voltages (70 kV/Sn 150 kV and 80 kV/Sn 150 kV) improve the detection rate of kidney stones in VNC reconstructions. • The visibility of renal stones in virtual non-contrast of dual-energy CT is highly associated with the size, and results in a significantly lower detection rate in stones below 2 mm.

OBJECTIVES:The purpose of this study was to investigate the impact of a 150kV spectral filtration chest imaging protocol (Sn150kVp) combined with advanced modeled iterative reconstruction (ADMIRE) on radiation dose and image quality in patients after lung-transplantation.METHODS:This study included 102 patients who had unenhanced chest-CT examinations available on both, a second-generation dual-source CT (DSCT) using standard protocol (100kVp, filtered-back-projection) and, on a third-generation DSCT using Sn150kVp protocol with ADMIRE. Signal-to-noise-ratio (SNR) was measured in 6 standardized regions. A 5-point Likert scale was used to evaluate subjective image quality. Radiation metrics were compared.RESULTS:The mean time interval between the two acquisitions was 1.1±0.7 years. Mean-volume-CT-dose-index, dose-length-product and effective dose were significantly lower for Sn150kVp protocol (2.1±0.5mGy;72.6±16.9mGy*cm;1.3±0.3mSv) compared to 100kVp protocol (6.2±1.8mGy;203.6±55.6mGy*cm;3.7±1.0mSv) (p<0.001), equaling a 65% dose reduction. All studies were considered of diagnostic quality. SNR measured in lung tissue, air inside trachea, vertebral body and air outside the body was significantly higher in 100kVp protocol compared to Sn150kVp protocol (12.5±2.7vs.9.6±1.5;17.4±3.6vs.11.8±1.8;0.7±0.3vs.0.4±0.2;25.2±6.9vs.14.9±3.3;p<0.001). SNR measured in muscle tissue was significantly higher in Sn150kVp protocol (3.2±0.9vs.2.6±1.0;p<0.001). For SNR measured in descending aorta there was a trend towards higher values for Sn150kVp protocol (2.8±0.6 vs. 2.7±0.9;p = 0.3). Overall SNR was significantly higher in 100kVp protocol (5.0±4.0vs.4.0±4.0;p<0.001). On subjective analysis both protocols achieved a median Likert rating of 1 (25th-75th-percentile:1-1;p = 0.122). Interobserver agreement was good (intraclass correlation coefficient = 0.73).CONCLUSIONS:Combined use of 150kVp tin-filtered chest CT protocol with ADMIRE allows for significant dose reduction while maintaining highly diagnostic image quality in the follow up after lung transplantation when compared to a standard chest CT protocol using filtered back projection.

CT colonography (CTC) is the radiological examination of choice for the diagnosis of colorectal neoplasia. Faecal tagging is considered a mandatory part of bowel preparation. However, the colonic mucosa, obscured by tagged residue, is not accessible to endoluminal 3D views and requires time-consuming 2D evaluation. Electronic cleansing (EC) software algorithms can overcome this limitation by digitally subtracting tagged residue from the colonic lumen. Ideally, this enables a seamless 3D endoluminal evaluation. Despite this benefit, EC is a potential source of a wide range of artefacts. Accurate EC requires proper CTC examination technique and faecal tagging. The digital subtraction process has been shown to affect the relevant morphological features of both colonic anatomy and colonic lesions, if submerged under faecal residue. This article summarises the potential effects of EC on CTC imaging, the consequences for reporting and patient management, and strategies to avoid pitfalls. Furthermore, potentially negative effects on clinical reporting and patient management are shown, and problem-solving techniques, as well as recommendations for the appropriate use of EC techniques, are presented. Radiologists using EC should be familiar with EC-related effects on polyp size and also with correct measurement techniques.

To assess a novel low-dose CT-protocol, combining a 150 kV spectral filtration unenhanced protocol (Sn150 kVp) and a stone-targeted dual-energy CT (DECT) in patients with urolithiasis. 232 (151 male, 49 ± 16.4 years) patients with urolithiasis received a low-dose non-contrast enhanced CT (NCCT) for suspected urinary stones either on a third-generation dual-source CT system (DSCT) using Sn150 kVp (n = 116, group 1), or on a second-generation DSCT (n = 116 group 2) using single energy (SE) 120 kVp. For group 1, a subsequent dual-energy CT (DECT) with a short stone-targeted scan range was performed. Objective and subjective image qualities were assessed. Radiation metrics were compared. 534 stones (group 1: n = 242 stones; group 2: n = 292 stones) were found. In group 1, all 215 stones within the stone-targeted DECT-scan range were identified. DE analysis was able to distinguish between UA and non-UA calculi in all collected stones. 11 calculi (5.12%) were labeled as uric acid (UA) while 204 (94.88%) were labeled as non-UA calculi. There was no significant difference in overall Signal-to-noise-ratio between group 1 and group 2 (p = 0.819). On subjective analysis both protocols achieved a median Likert rating of 2 (p = 0.171). Mean effective dose was significantly lower for combined Sn150 kVp and stone-targeted DECT (3.34 ± 1.84 mSv) compared to single energy 120 kVp NCCT (4.45 ± 2.89 mSv) (p < 0.001), equaling a 24.9% dose reduction. The evaluated novel low-dose stone composition protocol allows substantial radiation dose reduction with consistent high diagnostic image quality.

Zielsetzung Evaluation eines neuartiges Niedrigdosis-CT Protokolls bei Patienten mit Urolithiasis: 150-kV-Spektral CT (Sn150kVp) in Kombination mit einem gezieltem Dual-Energy-CT (DECT) zur Steinanalyse.

The aim of this study was to assess the objective and subjective image characteristics of monoenergetic images (MEI[+]), using a noise-optimized algorithm at different kiloelectron volts (keV) compared to polyenergetic images (PEI), in patients with pancreatic ductal adenocarcinoma (PDAC). This retrospective, institutional review board-approved study included 45 patients (18 male, 27 female; mean age 66 years; range, 42–96 years) with PDAC who had undergone a dual-energy CT (DECT) of the abdomen for staging. One standard polyenergetic image (PEI) and five MEI(+) images in 10-keV intervals, ranging from 40 to 80 keV, were reconstructed. Line-density profile analysis, as well as the contrast-to-noise ratio (CNR) of the tumor, the signal-to-noise ratio (SNR) of the regular pancreas parenchyma and the tumor, and the CNR of the three main peripancreatic vessels, was calculated. For subjective quality assessment, two readers independently assessed the images using a 5-point Likert scale. Reader reliability was evaluated using an intraclass correlation coefficient. Line-density profile analysis revealed the largest gradient in attenuation between PDAC and regular tissue in MEI(+) at 40 keV. Low-keV MEI(+)reconstructions at 40 and 50 keV increased CNR and SNR compared to PEI (40 keV: CNR 46.8 vs. 7.5; SNRPankreas 32.5 vs. 15.7; SNRLesion 13.5 vs. 8.6; p < 0.001). MEI(+) at 40 keV and 50 keV were consistently preferred by the observers (p < 0.05), showing a high intra-observer 0.937 (0.92–0.95) and inter-observer 0.911 (0.89–0.93) agreement. MEI(+) reconstructions at 40 keV and 50 keV provide better objective and subjective image quality compared to conventional PEI of DECT in patients with PDAC. • Low-keV MEI(+) reconstructions at 40 and 50 keV increase tumor-to-pancreas contrast compared to PEI. • Low-keV MEI(+) reconstructions improve objective and subjective image quality parameters compared to PEI. • Dual-energy post-processing might be a valuable tool in the diagnostic workup of patients with PDAC.