Coronary Artery Calcium Scoring Using Virtual Versus True Noncontrast Images From Photon-Counting Coronary CT Angiography.

Background Coronary artery calcium scoring (CACS) for coronary artery disease requires true noncontrast (TNC) CT alongside contrast-enhanced coronary CT angiography (CCTA). Photon-counting CT provides an algorithm (PureCalcium) for reconstructing virtual noncontrast images from CCTA specifically for CACS. Purpose To assess CACS differences based on PureCalcium images derived from contrast-enhanced photon-counting CCTA compared with TNC images and evaluate the impact of these differences on the clinically relevant classification of patients into plaque burden groups. Materials and Methods Photon-counting CCTA images acquired between August 2022 and May 2023 were retrospectively identified. Agatston scores were derived from both TNC and PureCalcium images and tested for differences with use of the Wilcoxon signed-rank test. The agreement was assessed with use of equivalence tests, Bland-Altman analysis, and intraclass correlation coefficient. Plaque burden groups were established based on Agatston scores, and agreement was evaluated using weighted Cohen kappa. The dose-length product was analyzed. Results Among 170 patients (mean age, 63 years ± 13 [SD]; 92 male), 111 had Agatston scores higher than 0. Median Agatston scores did not differ between TNC and PureCalcium images (4.8 [IQR, 0-84.4; range, 0.0-2151.8] vs 2.7 [IQR, 0-90.7; range, 0.0-2377.1]; P = .99), with strong correlation (intraclass correlation coefficient, 0.98 [95% CI: 0.97, 0.99]). The equivalence test was inconclusive, with a 95% CI of 0.90, 1.19. Bland-Altman analysis showed wide repeatability limits, indicating low agreement between the two scores. With use of the PureCalcium algorithm, 125 of 170 patients (74%) were correctly classified into plaque burden groups (excellent agreement, κ = 0.88). Patients without plaque burden were misclassified at higher than normal rates (P < .001). TNC image acquisition contributed a mean of 19.7% ± 8.8 of the radiation dose of the entire examination. Conclusion PureCalcium images show potential to replace TNC images for measuring Agatston scores, thereby reducing radiation dose in CCTA. There was strong correlation in calcium scores between TNC and PureCalcium, but limited agreement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Sakuma in this issue.

Imaging of intracranial hemorrhage in photon counting computed tomography using virtual monoenergetic images.

PURPOSE: To determine the optimal virtual monoenergetic image (VMI) for detecting and assessing intracranial hemorrhage in unenhanced photon counting CT of the head based on the evaluation of quantitative and qualitative image quality parameters. METHODS: Sixty-three patients with acute intracranial hemorrhage and unenhanced CT of the head were retrospectively included. In these patients, 35 intraparenchymal, 39 intraventricular, 30 subarachnoidal, and 43 subdural hemorrhages were selected. VMIs were reconstructed using all available monoenergetic reconstruction levels (40-190 keV). Multiple regions of interest measurements were used for evaluation of the overall image quality, and signal, noise, signal-to-noise-ratio (SNR), and contrast-to-noise-ratio (CNR) of intracranial hemorrhage. Based on the results of the quantitative analysis, specific VMIs were rated by five radiologists on a 5-point Likert scale. RESULTS: Signal, noise, SNR, and CNR differed significantly between different VMIs (p < 0.001). Maximum CNR for intracranial hemorrhage was reached in VMI with keV levels > 120 keV (intraparenchymal 143 keV, intraventricular 164 keV, subarachnoidal 124 keV, and subdural hemorrhage 133 keV). In reading, no relevant superiority in the detection of hemorrhage could be demonstrated using VMIs above 66 keV. CONCLUSION: For the detection of hemorrhage in unenhanced CT of the head, the quantitative analysis of the present study on photon counting CT is generally consistent with the findings from dual-energy CT, suggesting keV levels just above 120 keV and higher depending on the location of the hemorrhage. However, on the basis of the qualitative analyses, no reliable statement can yet be made as to whether an additional VMI with higher keV is truly beneficial in everyday clinical practice.

Photon-counting CT Material Decomposition: Initial Experience in Assessing Adrenal Adenoma.

See also the editorial by Pourmorteza in this issue.

Validation of clinical-radiological scores for prognosis of mortality in acute pulmonary embolism.

INTRODUCTION: Acute pulmonary embolism (APE) is a hazardous disorder with a high mortality. Combination of clinical, radiological, and serological parameters can improve risk stratification of APE. Most of the proposed combined scores were not validated in independent cohorts. Our aim was to validate the proposed clinical-radiological scores for prognosis of 7- and 30-day mortality in APE. MATERIALS AND METHODS: Our sample comprised 531 patients with APE, mean age 64.8 ± 15.6 years, 221 (41.6%) females and 310 (58.4%) males. The following parameters were collected: Age and sex of the patients, mortality within the observation time of 30 days, simplified pulmonary embolism severity index (sPESI), pH troponin level (pg/ml), minimal systolic and diastolic blood pressures (mmHg), heart rate, O2 saturation, episodes of syncope, and need for vasopressors. On CT pulmonary angiography (CTPA), short axis ratio right ventricle/left ventricle (RV/LV), and reflux of contrast medium into the inferior vena cava were obtained. The following clinical-radiological scores were calculated: BOVA score, pulmonary embolism mortality score (PEMS), European Society of Cardiology (ESC) score, Kumamaru score, and Calgary acute pulmonary embolism (CAPE) score. RESULTS: Overall, 31 patients (5.8%) died within seven and 64 patients (12%) within 30 days. All scores showed high negative prognostic values ranging from 89.0 to 99.0%. PEMS and CAPE score demonstrated the highest specificity for 7-day mortality (93.4% and 85.0%), PEMS and BOVA for 30-day mortality (94.2% and 90.4%). The highest sensitivity was observed for ESC 2019 (96.8% and 95.3%). Kumamaru and CAPE scores had low sensitivity. All scores had low positive and high negative predictive values. CONCLUSION: For prognosis of 7- and 30-day mortality in APE, PEMS score has the highest specificity. ESC 2019 shows the highest sensitivity. All scores had low positive and high negative predictive values.

Low skeletal muscle mass predicts treatment response in oncology: a meta-analysis.

OBJECTIVES: Low skeletal muscle mass (LSMM) predicts relevant clinical outcomes in oncologic patients. The purpose of this study was to perform a meta-analysis of data regarding associations between LSMM and treatment response (TR) in oncology. METHODS: MEDLINE, Cochrane, and SCOPUS databases were screened for relationships between LSMM and TR in oncologic patients up to November 2022. Overall, 35 studies met the inclusion criteria. The meta-analysis was performed using RevMan 5.4 software. RESULTS: The collected 35 studies comprised 3858 patients. In 1682 patients (43.6%), LSMM was diagnosed. In the overall sample, LSMM predicted a negatively objective response rate (ORR), OR = 0.70, 95% CI = (0.54-0.91), p = 0.007, and disease control rate (DCR), OR = 0.69, 95% CI = (0.50-0.95), p = 0.02. In the curative setting, LSMM predicted a negatively ORR, OR = 0.24, 95% CI = (0.12-0.50), p = 0.0001, but not DCR, OR = 0.60, 95% CI = (0.31-1.18), p = 0.14. In palliative treatment with conventional chemotherapies, LSMM did not predict ORR: OR = 0.94, 95% CI (0.57-1.55), p = 0.81, and DCR: OR = 1.13, 95% CI (0.38-3.40), p = 0.82. In palliative treatment with tyrosine kinase inhibitors (TKI), LSMM did not predict TR: ORR, OR = 0.74, 95% CI (0.44-1.26), p = 0.27, and DCR, OR = 1.04, 95% CI (0.53-2.05), p = 0.90. In palliative immunotherapy, LSMM tended to predict ORR, OR = 0.74, 95% CI = (0.54-1.01), p = 0.06, and predicted DCR, OR = 0.53, 95% CI = (0.37-0.76), p = 0.0006. CONCLUSION: LSMM is a risk factor for poor TR in curative chemotherapy in the adjuvant and/or neoadjuvant setting. LSMM is a risk factor for treatment failure in treatment with immunotherapy. Finally, LSMM does not influence TR in palliative treatment with conventional chemotherapy and/or TKIs. KEY POINTS: • Low skeletal muscle mass (LSMM) predicts treatment response (TR) to chemotherapy in the adjuvant and/or neoadjuvant setting. • LSMM predicts TR in immunotherapy. • LSMM does not influence TR in palliative chemotherapy.

Metal artifact reduction in patients with total hip replacements: evaluation of clinical photon counting CT using virtual monoenergetic images.

OBJECTIVES: To investigate photon-counting CT (PCCT)-derived virtual monoenergetic images (VMI) for artifact reduction in patients with unilateral total hip replacements (THR). METHODS: Forty-two patients with THR and portal-venous phase PCCT of the abdomen and pelvis were retrospectively included. For the quantitative analysis, region of interest (ROI)-based measurements of hypodense and hyperdense artifacts, as well as of artifact-impaired bone and the urinary bladder, were conducted, and corrected attenuation and image noise were calculated as the difference of attenuation and noise between artifact-impaired and normal tissue. Two radiologists qualitatively evaluated artifact extent, bone assessment, organ assessment, and iliac vessel assessment using 5-point Likert scales. RESULTS: VMI110keV yielded a significant reduction of hypo- and hyperdense artifacts compared to conventional polyenergetic images (CI) and the corrected attenuation closest to 0, indicating best possible artifact reduction (hypodense artifacts: CI: 237.8 ± 71.4 HU, VMI110keV: 8.5 ± 122.5 HU; p < 0.05; hyperdense artifacts: CI: 240.6 ± 40.8 HU vs. VMI110keV: 13.0 ± 110.4 HU; p < 0.05). VMI110keV concordantly provided best artifact reduction in the bone and bladder as well as the lowest corrected image noise. In the qualitative assessment, VMI110keV received the best ratings for artifact extent (CI: 2 (1-3), VMI110keV: 3 (2-4); p < 0.05) and bone assessment (CI: 3 (1-4), VMI110keV: 4 (2-5); p < 0.05), whereas organ and iliac vessel assessments were rated highest in CI and VMI70keV. CONCLUSIONS: PCCT-derived VMI effectively reduce artifacts from THR and thereby improve assessability of circumjacent bone tissue. VMI110keV yielded optimal artifact reduction without overcorrection, yet organ and vessel assessments at that energy level and higher were impaired by loss of contrast. CLINICAL RELEVANCE STATEMENT: PCCT-enabled artifact reduction is a feasible method for improving assessability of the pelvis in patients with total hip replacements at clinical routine imaging. KEY POINTS: • Photon-counting CT-derived virtual monoenergetic images at 110 keV yielded best reduction of hyper- and hypodense artifacts, whereas higher energy levels resulted in artifact overcorrection. • The qualitative artifact extent was reduced best in virtual monoenergetic images at 110 keV, facilitating an improved assessment of the circumjacent bone. • Despite significant artifact reduction, assessment of pelvic organs as well as vessels did not profit from energy levels higher than 70 keV, due to the decline in image contrast.

Sarcopenia is a predictor of patient death in acute ischemic stroke.

BACKGROUND: Sarcopenia is proposed as a novel imaging biomarker in several acute conditions regarding outcome and mortality. The aim of the present study was to investigate the prognostic role of the masseter muscles in patients with acute ischemic stroke (AIS). METHODS: Overall, 189 patients with AIS that received mechanical thrombectomy were retrospectively enrolled in this study. Outcome and overall survival after 90 days were analyzed. Transversal surface area and density of the masseter muscles were measured. The diagnostic performance for the estimation of a) favorable modified ranking scale 90 days (mRS 90) outcome and b) death at 90 days was calculated using univariate and multivariate logistic regression analysis, followed by receiver operating characteristics and Odds ratios. RESULTS: The masseter muscle area provided a significant difference between patients who survived and those who died and between patients who had a favorable outcome (mRS 90 < 3) and those who did not. The cutoff for a favorable mRS 90 was found to be 435.8 mm2 for men and 338.8 mm2 for women, the cutoff for the prediction of death 421.3 mm2 for men and 326.6 mm2 for women. Masseter muscle area was the third strongest predictor in both categories after patient age and NIHSS. CONCLUSIONS: Masseter muscle area is an independent predictor of mortality in patients with AIS.

[State of the Art Diagnostics of the Esophagus]. / State of the Art Diagnostik des Ösophagus.

State of the Art Diagnostics of the Esophagus Abstract. Modern diagnostics of the esophagus is highly technical. It mainly includes endoscopic, radiological, nuclear medicine, functional and electrochemical examinations. Diagnostic tools for esophageal disorders involve esophagogastroduodenoscopies with chromoendoscopy, manometric and pH-impedance catheters as well as radiological techniques, such as CT, MRI or PET-CTs. The patient's history including the main clinical symptoms such as heartburn or dysphagia, and the physical examination will determine the choice and order of subsequent examinations. The esophagogastroduodenoscopy is one of the most important diagnostic tools and has a very low complication rate. During esophagogastroduodenoscopy biopsies, chromoendoscopy or therapeutic interventions can be performed. Endosonography is essential for the staging of esophageal cancer and accuracy can be improved by endosonographically guided biopsies. A CT scan completes the tumor staging and is essential to search for metastases. For motility disorders high resolution manometry is the gold standard which can be supplemented with esophagus barium swallow exams. pH-impedance catheters can be used for diagnosis of reflux. MRI swallow exams are predominantly applied in clinical studies but may be more frequently used in the future.

[Complications and Management of Complications After Resection and Reconstruction of the Esophagus]. / Komplikationen und Komplikationsmanagement nach Resektion und Rekonstruktion der Speiseröhre.

Complications and Management of Complications After Resection and Reconstruction of the Esophagus Abstract. A curative therapy of advanced esophagus carcinoma is primarily made possible by radical esophagectomy with lymphadenectomy. Impressive advances in the surgical techniques of esophageal surgery through minimally invasive and robotic oesophagectomy have been made in the last two decades. The perioperative management with prehabilitation, PDK application, early mobilization and early food intake also contributed significantly to a reduction in complications. However, esophageal surgery is fraught with complications. Anastomotic leakage is the most common technical-surgical complication. The rate is approximately 10-16%, independent of the technique and procedure. In addition to an experienced, subtle, atraumatic and rapid surgical technique, early detection (clinical, endoscopic, radiological) and adequate, interdisciplinary management of perioperative complications in resecting esophageal surgery are the key to increasing the safety of these complex interventions. The treatment of the complications includes conservative, interventional and surgical measures. In the last few decades, there has been a radical change from once exclusively surgical revisions with a high degree of invasiveness and a poor outcome to today's mostly conservative-interventional management with little patient burden and - in centers with the appropriate expertise - good results.

Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning.

BACKGROUND: Precise volumetric assessment of brain tumors is relevant for treatment planning and monitoring. However, manual segmentations are time-consuming and impeded by intra- and interrater variabilities. PURPOSE: To investigate the performance of a deep-learning model (DLM) to automatically detect and segment primary central nervous system lymphoma (PCNSL) on clinical MRI. STUDY TYPE: Retrospective. POPULATION: Sixty-nine scans (at initial and/or follow-up imaging) from 43 patients with PCNSL referred for clinical MRI tumor assessment. FIELD STRENGTH/SEQUENCE: T1 -/T2 -weighted, T1 -weighted contrast-enhanced (T1 CE), and FLAIR at 1.0, 1.5, and 3.0T from different vendors and study centers. ASSESSMENT: Fully automated voxelwise segmentation of tumor components was performed using a 3D convolutional neural network (DeepMedic) trained on gliomas (n = 220). DLM segmentations were compared to manual segmentations performed in a 3D voxelwise manner by two readers (radiologist and neurosurgeon; consensus reading) from T1 CE and FLAIR, which served as the reference standard. STATISTICAL TESTS: Dice similarity coefficient (DSC) for comparison of spatial overlap with the reference standard, Pearson's correlation coefficient (r) to assess the relationship between volumetric measurements of segmentations, and Wilcoxon rank-sum test for comparison of DSCs obtained in initial and follow-up imaging. RESULTS: The DLM detected 66 of 69 PCNSL, representing a sensitivity of 95.7%. Compared to the reference standard, DLM achieved good spatial overlap for total tumor volume (TTV, union of tumor volume in T1 CE and FLAIR; average size 77.16 ± 62.4 cm3 , median DSC: 0.76) and tumor core (contrast enhancing tumor in T1 CE; average size: 11.67 ± 13.88 cm3 , median DSC: 0.73). High volumetric correlation between automated and manual segmentations was observed (TTV: r = 0.88, P < 0.0001; core: r = 0.86, P < 0.0001). Performance of automated segmentations was comparable between pretreatment and follow-up scans without significant differences (TTV: P = 0.242, core: P = 0.177). DATA CONCLUSION: In clinical MRI scans, a DLM initially trained on gliomas provides segmentation of PCNSL comparable to manual segmentation, despite its complex and multifaceted appearance. Segmentation performance was high in both initial and follow-up scans, suggesting its potential for application in longitudinal tumor imaging. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Fully Automated MR Detection and Segmentation of Brain Metastases in Non-small Cell Lung Cancer Using Deep Learning.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the most common tumor entity spreading to the brain and up to 50% of patients develop brain metastases (BMs). Detection of BMs on MRI is challenging with an inherent risk of missed diagnosis. PURPOSE: To train and evaluate a deep learning model (DLM) for fully automated detection and 3D segmentation of BMs in NSCLC on clinical routine MRI. STUDY TYPE: Retrospective. POPULATION: Ninety-eight NSCLC patients with 315 BMs on pretreatment MRI, divided into training (66 patients, 248 BMs) and independent test (17 patients, 67 BMs) and control (15 patients, 0 BMs) cohorts. FIELD STRENGTH/SEQUENCE: T1 -/T2 -weighted, T1 -weighted contrast-enhanced (T1 CE; gradient-echo and spin-echo sequences), and FLAIR at 1.0, 1.5, and 3.0 T from various vendors and study centers. ASSESSMENT: A 3D convolutional neural network (DeepMedic) was trained on the training cohort using 5-fold cross-validation and evaluated on the independent test and control sets. Three-dimensional voxel-wise manual segmentations of BMs by a neurosurgeon and a radiologist on T1 CE served as the reference standard. STATISTICAL TESTS: Sensitivity (recall) and false positive (FP) findings per scan, dice similarity coefficient (DSC) to compare the spatial overlap between manual and automated segmentations, Pearson's correlation coefficient (r) to evaluate the relationship between quantitative volumetric measurements of segmentations, and Wilcoxon rank-sum test to compare the volumes of BMs. A P value <0.05 was considered statistically significant. RESULTS: In the test set, the DLM detected 57 of the 67 BMs (mean volume: 0.99 ± 4.24 cm3 ), resulting in a sensitivity of 85.1%, while FP findings of 1.5 per scan were observed. Missed BMs had a significantly smaller volume (0.05 ± 0.04 cm3 ) than detected BMs (0.96 ± 2.4 cm3 ). Compared with the reference standard, automated segmentations achieved a median DSC of 0.72 and a good volumetric correlation (r = 0.95). In the control set, 1.8 FPs/scan were observed. DATA CONCLUSION: Deep learning provided a high detection sensitivity and good segmentation performance for BMs in NSCLC on heterogeneous scanner data while yielding a low number of FP findings. Level of Evidence 3 Technical Efficacy Stage 2.

Quantitative distribution of iodinated contrast media in body computed tomography: data from a large reference cohort.

OBJECTIVES: Dual-energy computed tomography allows for an accurate and reliable quantification of iodine. However, data on physiological distribution of iodine concentration (IC) is still sparse. This study aims to establish guidance for IC in abdominal organs and important anatomical landmarks using a large cohort of individuals without radiological tumor burden. METHODS: Five hundred seventy-one oncologic, portal venous phase dual-layer spectral detector CT studies of the chest and abdomen without tumor burden at time point of imaging confirmed by > 3-month follow-up were included. ROI were placed in parenchymatous organs (n = 25), lymph nodes (n = 6), and vessels (n = 3) with a minimum of two measurements per landmark. ROI were placed on conventional images and pasted to iodine maps to retrieve absolute IC. Normalization to the abdominal aorta was conducted to obtain iodine perfusion ratios. Bivariate regression analysis, t tests, and ANOVA with Tukey-Kramer post hoc test were used for statistical analysis. RESULTS: Absolute IC showed a broad scatter and varied with body mass index, between different age groups and between the sexes in parenchymatous organs, lymph nodes, and vessels (range 0.0 ± 0.0 mg/ml-6.6 ± 1.3 mg/ml). Unlike absolute IC, iodine perfusion ratios did not show dependency on body mass index; however, significant differences between the sexes and age groups persisted, showing a tendency towards decreased perfusion ratios in elderly patients (e.g., liver 18-44 years/≥ 64 years: 0.50 ± 0.11/0.43 ± 0.10, p ≤ 0.05). CONCLUSIONS: Distribution of IC obtained from a large-scale cohort is provided. As significant differences between sexes and age groups were found, this should be taken into account when obtaining quantitative iodine concentrations and applying iodine thresholds. KEY POINTS: • Absolute iodine concentration showed a broad variation and differed between body mass index, age groups, and between the sexes in parenchymatous organs, lymph nodes, and vessels. • The iodine perfusion ratios did not show dependency on body mass index while significant differences between sexes and age groups persisted. • Provided guidance values may serve as reference when aiming to differentiate healthy and abnormal tissue based on iodine perfusion ratios.

Reduction of CT artifacts from cardiac implantable electronic devices using a combination of virtual monoenergetic images and post-processing algorithms.

OBJECTIVES: To evaluate the reduction of artifacts from cardiac implantable electronic devices (CIEDs) by virtual monoenergetic images (VMI), metal artifact reduction (MAR) algorithms, and their combination (VMIMAR) derived from spectral detector CT (SDCT) of the chest compared to conventional CT images (CI). METHODS: In this retrospective study, we included 34 patients (mean age 74.6 ± 8.6 years), who underwent a SDCT of the chest and had a CIED in place. CI, MAR, VMI, and VMIMAR (10 keV increment, range: 100-200 keV) were reconstructed. Mean and standard deviation of attenuation (HU) among hypo- and hyperdense artifacts adjacent to CIED generator and leads were determined using ROIs. Two radiologists qualitatively evaluated artifact reduction and diagnostic assessment of adjacent tissue. RESULTS: Compared to CI, MAR and VMIMAR ≥ 100 keV significantly increased attenuation in hypodense and significantly decreased attenuation in hyperdense artifacts at CIED generator and leads (p < 0.05). VMI ≥ 100 keV alone only significantly decreased hyperdense artifacts at the generator (p < 0.05). Qualitatively, VMI ≥ 100 keV, MAR, and VMIMAR ≥ 100 keV provided significant reduction of hyper- and hypodense artifacts resulting from the generator and improved diagnostic assessment of surrounding structures (p < 0.05). Diagnostic assessment of structures adjoining to the leads was only improved by MAR and VMIMAR 100 keV (p < 0.05), whereas keV values ≥ 140 with and without MAR significantly worsened diagnostic assessment (p < 0.05). CONCLUSIONS: The combination of VMI and MAR as well as MAR as a standalone approach provides effective reduction of artifacts from CIEDs. Still, higher keV values should be applied with caution due to a loss of soft tissue and vessel contrast along the leads. KEY POINTS: • The combination of VMI and MAR as well as MAR as a standalone approach enables effective reduction of artifacts from CIEDs. • Higher keV values of both VMI and VMIMAR at CIED leads should be applied with caution since diagnostic assessment can be hampered by a loss of soft tissue and vessel contrast. • Recommended keV values for CIED generators are between 140 and 200 keV and for leads around 100 keV.

Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.

PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH). METHODS: Three different DLMs were trained on CTA datasets of 68 aSAH patients with 79 aneurysms with their outputs being combined applying ensemble learning (DLM-Ens). The DLM-Ens was evaluated on an independent test set of 104 aSAH patients with 126 aneuryms (mean volume 129.2 ± 185.4 mm3, 13.0% at the posterior circulation), which were determined by two radiologists and one neurosurgeon in consensus using CTA and digital subtraction angiography scans. CTA scans of the test set were then presented to three blinded radiologists (reader 1: 13, reader 2: 4, and reader 3: 3 years of experience in diagnostic neuroradiology), who assessed them individually for aneurysms. Detection sensitivities for aneurysms of the readers with and without the assistance of the DLM were compared. RESULTS: In the test set, the detection sensitivity of the DLM-Ens (85.7%) was comparable to the radiologists (reader 1: 91.2%, reader 2: 86.5%, and reader 3: 86.5%; Fleiss κ of 0.502). DLM-assistance significantly increased the detection sensitivity (reader 1: 97.6%, reader 2: 97.6%,and reader 3: 96.0%; overall P=.024; Fleiss κ of 0.878), especially for secondary aneurysms (88.2% of the additional aneurysms provided by the DLM). CONCLUSION: Deep learning significantly improved the detection sensitivity of radiologists for aneurysms in aSAH, especially for secondary aneurysms. It therefore represents a valuable adjunct for physicians to establish an accurate diagnosis in order to optimize patient treatment.

MRI Follow-up of Astrocytoma: Automated Coregistration and Color-Coding of FLAIR Sequences Improves Diagnostic Accuracy With Comparable Reading Time.

BACKGROUND: MRI follow-up is widely used for longitudinal assessment of astrocytoma, yet reading can be tedious and error-prone, in particular when changes are subtle. PURPOSE/HYPOTHESIS: To determine the effect of automated, color-coded coregistration (AC) of fluid attenuated inversion recovery (FLAIR) sequences on diagnostic accuracy, certainty, and reading time compared to conventional follow-up MRI assessment of astrocytoma patients. STUDY TYPE: Retrospective. POPULATION: In all, 41 patients with neuropathologically confirmed astrocytoma. FIELD STRENGTH/SEQUENCE: 1.0-3.0T/FLAIR ASSESSMENT: The presence or absence of tumor progression was determined based on FLAIR sequences, contrast-enhanced T1 sequences, and clinical data. Three radiologists assessed 47 MRI study pairs in a conventional reading (CR) and in a second reading supported by AC after 6 weeks. Readers determined the presence/absence of tumor progression and indicated diagnostic certainty on a 5-point Likert scale. Reading time was recorded by an independent assessor. STATISTICAL TESTS: The Wilcoxon test was used to assess reading time and diagnostic certainty. Differences in diagnostic accuracy, sensitivity, and specificity were analyzed with the McNemar mid-p test. RESULTS: Readers attained significantly higher overall sensitivity (0.86 vs. 0.75; P < 0.05) and diagnostic accuracy (0.84 vs. 0.73; P < 0.05) for detection of progressive nonenhancing tumor burden when using AC compared to CR. There was a strong trend towards higher specificity within the AC-augmented reading, yet without statistical significance (0.83 vs. 0.71; P = 0.08). Sensitivity for unequivocal disease progression was similarly high in both approaches (AC: 0.94, CR: 0.92), while for marginal disease progressions, it was significantly higher in AC (AC: 0.78, CR: 0.58; P < 0.05). Reading time including application loading time was comparable (AC: 38.1 ± 16.8 sec, CR: 36.0 ± 18.9 s; P = 0.25). DATA CONCLUSION: Compared to CR, AC improves comparison of FLAIR signal hyperintensity at MRI follow-up of astrocytoma patients, allowing for a significantly higher diagnostic accuracy, particularly for subtle disease progression at a comparable reading time. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY STAGE: 6 J. Magn. Reson. Imaging 2020;52:1197-1206.

Single-slice CT measurements allow for accurate assessment of sarcopenia and body composition.

OBJECTIVES: To evaluate the correlation between simple planimetric measurements in axial computed tomography (CT) slices and measurements of patient body composition and anthropometric data performed with bioelectrical impedance analysis (BIA) and metric clinical assessments. METHODS: In this prospective cross-sectional study, we analyzed data of a cohort of 62 consecutive, untreated adult patients with advanced malignant melanoma who underwent concurrent BIA assessments at their radiologic baseline staging by CT between July 2016 and October 2017. To assess muscle and adipose tissue mass, we analyzed the areas of the paraspinal muscles as well as the cross-sectional total patient area in a single CT slice at the height of the third lumbar vertebra. These measurements were subsequently correlated with anthropometric (body weight) and body composition parameters derived from BIA (muscle mass, fat mass, fat-free mass, and visceral fat mass). Linear regression models were built to allow for estimation of each parameter based on CT measurements. RESULTS: Linear regression models allowed for accurate prediction of patient body weight (adjusted R2 = 0.886), absolute muscle mass (adjusted R2 = 0.866), fat-free mass (adjusted R2 = 0.855), and total as well as visceral fat mass (adjusted R2 = 0.887 and 0.839, respectively). CONCLUSIONS: Our data suggest that patient body composition can accurately and quantitatively be determined by using simple measurements in a single axial CT slice. This could be useful in various medical and scientific settings, where the knowledge of the patient's anthropometric parameters is not immediately or easily available. KEY POINTS: • Easy to perform measurements on a single CT slice highly correlate with clinically valuable parameters of body composition. • Body composition data were acquired using bioelectrical impedance analysis to correlate CT measurements with a non-imaging-based method, which is frequently lacking in previous studies. • The obtained equations facilitate a quick, opportunistic assessment of relevant parameters of body composition.

Adjustment of Stent Retriever Length to Clot Extent Affects First-Pass Reperfusion in Endovascular Treatment of Acute Ischemic Stroke.

BACKGROUND: Stent retriever technology has evolved, and significantly longer devices have become available for mechanical thrombectomy (MT) of large cerebral vessel occlusions in ischemic stroke. We hypothesized that increased stent retriever length may improve the rate of complete angiographic reperfusion and decrease the respective number of attempts, resulting in a better clinical outcome. METHODS: Retrospective analysis of patients with large vessel occlusion in the anterior and posterior circulation treated with stent retriever MT. The study group was dichotomized into short (20 mm) and long (>20 mm) retrievers using propensity matching. In the anterior circulation, the clot burden score was evaluated. Primary end points were first-pass modified thrombolysis in cerebral infarction (mTICI) 3 reperfusion and first-pass mTICI ≥ 2b reperfusion, and the secondary end point was functional independence (defined as modified Rankin Scale score 0-2) at discharge and 90 days. RESULTS: Overall, 394 patients were included in the analysis. In the anterior circulation, short stent retrievers had a significantly higher rate of first-pass reperfusion in cases with low clot burden (mTICI 3: 27% vs. 17%; p = 0.009; mTICI ≥ 2b: 42 vs. 30%; p = 0.005) and in middle cerebral artery occlusions (mTICI ≥ 2b: 51 vs. 41%; p = 0.024). Higher rates of favorable outcome at discharge and 90 days were observed for the short stent retriever group (p < 0.001). CONCLUSION: Stent retriever length should be adjusted to clot burden score and vessel occlusion site.

Virtual non-contrast for evaluation of liver parenchyma and vessels: results from 25 patients using multi-phase spectral-detector CT.

BACKGROUND: In abdominal imaging, contrast-enhanced computed tomography (CT) examinations are most commonly applied; however, unenhanced examinations are still needed for several clinical questions but require additional scanning and radiation exposure. PURPOSE: To evaluate accuracy of virtual non-contrast (VNC) from arterial and venous phase spectral-detector CT (SDCT) scans compared to true-unenhanced (TNC) images for the evaluation of liver parenchyma and vessels. MATERIAL AND METHODS: A total of 25 patients undergoing triphasic SDCT examinations were included. VNC was reconstructed from arterial and venous phases and compared to TNC images. Quantitative image analysis was performed by region of interest (ROI)-based assessment of mean and SD of attenuation (HU) in each liver segment, spleen, portal vein, common hepatic artery, and abdominal aorta. Subjectively, iodine subtraction and diagnostic assessment were rated on 5-point Likert scales. RESULTS: Attenuation and image noise measured in the liver from VNC were not significantly different from TNC (TNC: 54.6 ± 10.8 HU, VNC arterial phase: 55.7 ± 10.8 HU; VNC venous phase: 58.3 ± 10.0 HU; P > 0.05). VNC also showed accurate results regarding attenuation and image noise for spleen, portal vein, and abdominal aorta. Only iodine subtraction in the common hepatic artery in the arterial phase was insufficient which was confirmed by the subjective reading. Apart from that, subjective reading showed accurate iodine subtraction and comparable diagnostic assessment. CONCLUSION: VNC from the arterial and venous phases were very similar to TNC yielding mostly negligible differences in attenuation, image noise, and diagnostic utility. Inadequate iodine subtraction occurred in hepatic arteries in the arterial phase.

Does SPECT Provide Incremental Value to CT or MRI in Assessing Mandibular Invasion by Oral Squamous Cell Carcinoma?

PURPOSE: Single photon emission computed tomography (SPECT) has been commonly used as an additional method to assess mandibular bone invasion in patients with oral squamous cell carcinoma (OSCC). In the present study, we measured the diagnostic validity of SPECT findings compared with the histologic findings. PATIENTS AND METHODS: We implemented a retrospective cross-sectional study and enrolled a sample of patients with OSCC adjacent to the mandible. The staging examinations included magnetic resonance imaging (MRI) and/or computed tomography (CT) and additional SPECT. The patients' medical records and imaging data were reviewed by 2 readers, and bone invasion was classified as positive or negative for each diagnostic method. The predictor was bone invasion found on CT and/or MRI compared with the combination of CT and/or MRI with either positive or negative SPECT results. The primary outcome variable was histologic bone invasion. Other variables of interest were clinicopathologic data, type of mandibular resection, and resection margin status. Bivariate tests were used to compare the diagnostic specificity, sensitivity, and accuracy of each imaging modality. RESULTS: The study enrolled 122 patients, with a mean age of 67 years (55% male; study period, January 2010 to December 2017). In 60 patients (49%), segmental mandibular resection was performed. The sensitivity and specificity for bone invasion were 100% and 39% for SPECT and 84% and 75% for CT and/or MRI. The negative results for bone invasion using SPECT did not match the false-positive CT and/or MRI results in 5% (n = 6 of 122). Positive SPECT findings, in addition to positive CT and/or MRI findings increased the sensitivity to 100% but decreased the specificity to 29% (P < .001). Considering only negative SPECT findings increased the specificity to 85% (P = .03), sensitivity remaining unaffected. The accuracy of CT and/or MRI alone was 80% and was 84% when combining CT and/or MRI and negative SPECT findings (P = .03). CONCLUSIONS: In oncologic staging with CT and/or MRI, the addition of SPECT provided only small benefits. Only negative SPECT results allowed for greater specificity and accuracy. The use of SPECT could be considered to rule out bone invasion in cases of radiologic uncertainty of positive CT or MRI findings.

Dual-Energy CT-derived Iodine Maps: Use in Assessing Pleural Carcinomatosis.

Purpose To evaluate the use of spectral CT for differentiation between noncalcified benign pleural lesions and pleural carcinomatosis. Materials and Methods In this retrospective study, patients who underwent contrast agent-enhanced late venous phase spectral CT of the chest between June 1, 2016, and July 1, 2018 with histopathologic and/or imaging confirmation of noncalcified pleural lesions were evaluated. Conventional images, iodine overlay (IO) images, and virtual monoenergetic images at 40 keV (hereafter, VMI40keV) were reconstructed from contrast-enhanced spectral chest CT. Four blinded radiologists determined lesion presence and indicated lesion conspicuity and diagnostic certainty. Hounsfield unit attenuation from conventional images and iodine concentration (IC) (in milligrams per milliliter) from IO images were determined. Area under the receiver operating characteristics curve determined thresholds for quantitative lesion differentiation and cutoff values were validated in an independent data set. Results Eighty-four patients were included (mean age, 66.2 years; 54 men and 30 women; 44 patients with cancer with confirmed pleural carcinomatosis and 40 patients with benign pleural lesions). The area under the receiver operating characteristics curve for IC was greater than that of conventional Hounsfield units (0.96 vs 0.91; P ≤ .05, respectively). The optimal IC threshold was 1.3 mg/mL, with comparable sensitivity and specificity when applied to the test data set. The sensitivities to depict pleural carcinomatosis with spectral reconstructions versus conventional CT were 96% (199 of 208) and 83% (172 of 208), respectively, with specificities of 84% (161 of 192) and 63% (120 of 192), respectively (P ≤ .001 each). Conclusion Compared with conventional images, spectral CT with iodine maps improved both quantitative and qualitative determination of pleural carcinomatosis versus noncalcified benign pleural lesions. © RSNA, 2019 See also the editorial by K. S. Lee and H. Y. Lee .