CT-guided High-Dose-Rate Brachytherapy versus Transarterial Chemoembolization in Patients with Unresectable Hepatocellular Carcinoma.

Background CT-guided high-dose-rate (HDR) brachytherapy (hereafter, HDR brachytherapy) has been shown to be safe and effective for patients with unresectable hepatocellular carcinoma (HCC), but studies comparing this therapy with other local-regional therapies are scarce. Purpose To compare patient outcomes of HDR brachytherapy and transarterial chemoembolization (TACE) in patients with unresectable HCC. Materials and Methods This multi-institutional retrospective study included consecutive treatment-naive adult patients with unresectable HCC who underwent either HDR brachytherapy or TACE between January 2010 and December 2022. Overall survival (OS) and progression-free survival (PFS) were compared between patients matched for clinical and tumor characteristics by propensity score matching. Not all patients who underwent TACE had PFS available; thus, a different set of patients was used for PFS and OS analysis for this treatment. Hazard ratios (HRs) were calculated from Kaplan-Meier survival curves. Results After propensity matching, 150 patients who underwent HDR brachytherapy (median age, 71 years [IQR, 63-77 years]; 117 males) and 150 patients who underwent TACE (OS analysis median age, 70 years [IQR, 63-77 years]; 119 male; PFS analysis median age, 68 years [IQR: 63-76 years]; 119 male) were analyzed. Hazard of death was higher in the TACE versus HDR brachytherapy group (HR, 4.04; P < .001). Median estimated PFS was 32.8 months (95% CI: 12.5, 58.7) in the HDR brachytherapy group and 11.6 months (95% CI: 4.9, 22.7) in the TACE group. Hazard of disease progression was higher in the TACE versus HDR brachytherapy group (HR, 2.23; P < .001). Conclusion In selected treatment-naive patients with unresectable HCC, treatment with CT-guided HDR brachytherapy led to improved OS and PFS compared with TACE. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Chapiro in this issue.

Low bone mineral density is a prognostic factor for elderly patients with HCC undergoing TACE: results from a multicenter study.

OBJECTIVES: Low bone mineral density (BMD) was recently identified as a novel risk factor for patients with hepatocellular carcinoma (HCC). In this multicenter study, we aimed to validate the role of BMD as a prognostic factor for patients with HCC undergoing transarterial chemoembolization (TACE). METHODS: This retrospective multicenter trial included 908 treatment-naïve patients with HCC who were undergoing TACE as a first-line treatment, at six tertiary care centers, between 2010 and 2020. BMD was assessed by measuring the mean Hounsfield units (HUs) in the midvertebral core of the 11th thoracic vertebra, on contrast-enhanced computer tomography performed before treatment. We assessed the influence of BMD on median overall survival (OS) and performed multivariate analysis including established estimates for survival. RESULTS: The median BMD was 145 HU (IQR, 115-175 HU). Patients with a high BMD (≥ 114 HU) had a median OS of 22.2 months, while patients with a low BMD (< 114 HU) had a lower median OS of only 16.2 months (p < .001). Besides albumin, bilirubin, tumor number, and tumor diameter, BMD remained an independent prognostic factor in multivariate analysis. CONCLUSIONS: BMD is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. The integration of BMD into novel scoring systems could potentially improve survival prediction and clinical decision-making. KEY POINTS: • Bone mineral density can be easily assessed in routinely acquired pre-interventional computed tomography scans. • Bone mineral density is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. • Thus, bone mineral density is a novel imaging biomarker for prognosis prediction in elderly patients with HCC undergoing TACE.

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

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

Inter-scan and inter-scanner variation of quantitative dual-energy CT: evaluation with three different scanner types.

OBJECTIVES: To investigate inter-scan and inter-scanner variation of iodine concentration (IC) and attenuation in virtual monoenergetic images at 65 keV (HU65keV) in patients with repeated abdominal examinations on dual-source (dsDECT), rapid kV switching (rsDECT), and dual-layer detector DECT (dlDECT). METHODS: We retrospectively included 131 patients who underwent two abdominal DECT examinations on the same scanner (dsDECT: n = 46, rsDECT: n = 45, dlDECT: n = 40). IC and HU65keV were measured by placing regions of interest in the liver, spleen, kidneys, aorta, portal vein, and inferior vena cava. Overall IC and HU65keV for each scanner, their inter-scan differences and proportional variation were calculated and compared between scanner types. RESULTS: The three scanner-specific cohorts showed similar weight, body diameter, age, sex, and contrast media injection parameters as well as inter-scan differences hereof (p range: 0.23-0.99). Absolute inter-scan differences of HU65keV and IC were comparable between scanners (p range: 0.08-1.0). Overall inter-scan variation was significantly higher in IC than HU65keV (p < 0.05). For the liver, rsDECT showed significantly lower inter-scan variation of IC compared to dsDECT/dlDECT (p = 0.005/0.01), while for the spleen, this difference was only significant compared to dsDECT (p = 0.015). Normalizing IC of the liver to the portal vein and of the spleen to the aorta did not significantly reduce inter-scan variation (p = 0.97 and 0.50). CONCLUSIONS: Iodine measurements across different DECT scanners show inter-scan variation which is higher compared to variation of attenuation values. Inter-scanner differences in longitudinal variation and overall iodine concentration depend on the scanner pairs and organs assessed and should be acknowledged in clinical and scientific DECT applications. KEY POINTS: • All scanner types showed comparable inter-scan variation of attenuation, while for iodine, the rapid kV switching DECT showed lower variability in the liver and spleen. • Iodine concentration showed higher inter-scan variation than attenuation measurements; normalization to vessels did not significantly improve inter-scan reproducibility of iodine concentration in parenchymal organs. • Differences between the three scanner types regarding overall iodine concentration and attenuation obtained from both timepoints were within the range of average intra-patient, inter-scan differences for most assessed organs and vessels.

Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network.

OBJECTIVES: The goal of the present study was to classify the most common types of plain radiographs using a neural network and to validate the network's performance on internal and external data. Such a network could help improve various radiological workflows. METHODS: All radiographs from the year 2017 (n = 71,274) acquired at our institution were retrieved from the PACS. The 30 largest categories (n = 58,219, 81.7% of all radiographs performed in 2017) were used to develop and validate a neural network (MobileNet v1.0) using transfer learning. Image categories were extracted from DICOM metadata (study and image description) and mapped to the WHO manual of diagnostic imaging. As an independent, external validation set, we used images from other institutions that had been stored in our PACS (n = 5324). RESULTS: In the internal validation, the overall accuracy of the model was 90.3% (95%CI: 89.2-91.3%), whereas, for the external validation set, the overall accuracy was 94.0% (95%CI: 93.3-94.6%). CONCLUSIONS: Using data from one single institution, we were able to classify the most common categories of radiographs with a neural network. The network showed good generalizability on the external validation set and could be used to automatically organize a PACS, preselect radiographs so that they can be routed to more specialized networks for abnormality detection or help with other parts of the radiological workflow (e.g., automated hanging protocols; check if ordered image and performed image are the same). The final AI algorithm is publicly available for evaluation and extension. KEY POINTS: • Data from one single institution can be used to train a neural network for the correct detection of the 30 most common categories of plain radiographs. • The trained model achieved a high accuracy for the majority of categories and showed good generalizability to images from other institutions. • The neural network is made publicly available and can be used to automatically organize a PACS or to preselect radiographs so that they can be routed to more specialized neural networks for abnormality detection.

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.

Virtual Noncontrast Images From Portal Venous Phase Spectral-Detector CT Acquisitions for Adrenal Lesion Characterization.

OBJECTIVE: The aim of this study was to investigate if Hounsfield unit (HU) values from virtual noncontrast (VNC) images derived from portal venous phase spectral-detector computed tomography can help to differentiate adrenal adenomas and metastases. METHODS: Spectral-detector computed tomography datasets of 33 patients with presence of adrenal lesions and standard of reference for lesion origin by follow-up/prior examinations or dedicated magnetic resonance imaging were included. Conventional and VNC images were reconstructed from the same scan. Region of interest-based image analysis was performed in adrenal lesions and contralateral healthy adrenal tissue. RESULTS: The 33 lesions consisted of 23 adenomas and 10 metastases. Hounsfield unit values of all lesions in VNC images were significantly lower compared with conventional images (18.2 ± 12.6 HU vs 59.6 ± 21.7 HU, P < 0.001). Hounsfield unit values in adenomas were significantly lower in VNC images (11.3 ± 6.5 HU vs 34.1 ± 9.1 HU, P < 0.001). CONCLUSIONS: Virtual noncontrast HU values differed significantly between adrenal adenomas and metastases and can therefore be used for improved characterization of incidental adrenal lesions and definition of adrenal adenomas.

Use and Control of Artificial Intelligence in Patients Across the Medical Workflow: Single-Center Questionnaire Study of Patient Perspectives.

BACKGROUND: Artificial intelligence (AI) is gaining increasing importance in many medical specialties, yet data on patients' opinions on the use of AI in medicine are scarce. OBJECTIVE: This study aimed to investigate patients' opinions on the use of AI in different aspects of the medical workflow and the level of control and supervision under which they would deem the application of AI in medicine acceptable. METHODS: Patients scheduled for computed tomography or magnetic resonance imaging voluntarily participated in an anonymized questionnaire between February 10, 2020, and May 24, 2020. Patient information, confidence in physicians vs AI in different clinical tasks, opinions on the control of AI, preference in cases of disagreement between AI and physicians, and acceptance of the use of AI for diagnosing and treating diseases of different severity were recorded. RESULTS: In total, 229 patients participated. Patients favored physicians over AI for all clinical tasks except for treatment planning based on current scientific evidence. In case of disagreement between physicians and AI regarding diagnosis and treatment planning, most patients preferred the physician's opinion to AI (96.2% [153/159] vs 3.8% [6/159] and 94.8% [146/154] vs 5.2% [8/154], respectively; P=.001). AI supervised by a physician was considered more acceptable than AI without physician supervision at diagnosis (confidence rating 3.90 [SD 1.20] vs 1.64 [SD 1.03], respectively; P=.001) and therapy (3.77 [SD 1.18] vs 1.57 [SD 0.96], respectively; P=.001). CONCLUSIONS: Patients favored physicians over AI in most clinical tasks and strongly preferred an application of AI with physician supervision. However, patients acknowledged that AI could help physicians integrate the most recent scientific evidence into medical care. Application of AI in medicine should be disclosed and controlled to protect patient interests and meet ethical standards.

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.

Iodine overlays to improve differentiation between peritoneal carcinomatosis and benign peritoneal lesions.

OBJECTIVES: Peritoneal carcinomatosis (PC) is a prognostically relevant metastatic disease which may be difficult to depict in postoperative patients, particularly in early stages. This study aimed to determine whether PC could be diagnosed more accurately when using a combination of spectral detector CT (SDCT)-derived conventional images (CI) and iodine overlay images (IO) compared with CI only. METHODS: Thirty patients with PC and 30 patients with benign peritoneal alterations (BPA) who underwent portal-venous abdominal SDCT were included. Four radiologists determined the presence/absence of PC for each patient and assessed lesion conspicuity, diagnostic certainty, and image quality using 5-point Likert scales. Subjective assessment was conducted in two sessions comprising solely CI and CI/IO between which a latency of 6 weeks was set. Iodine uptake and HU attenuation were determined ROI-based to analyze quantitative differentiation of PC/BPA. RESULTS: Specificity for PC was significantly higher when using CI/IO compared with using CI only (0.86 vs. 0.78, p ≤ 0.05), while sensitivity was comparable (0.79 vs. 0.81, p = 1). In postoperative patients, the increase in specificity was the highest (0.93 vs. 0.80, p ≤ 0.05). Lesion conspicuity was rated higher in CI/IO (4 (3-5)) compared with that in CI only (3 (3-4); p ≤ 0.05). Diagnostic certainty was comparable (both 4 (3-5); p = 0.5). CI/IO received the highest rating for overall image quality and assessability (CI/IO 5 (4-5) vs. CI 4 (4-4) vs. IO 4 (3-4); p ≤ 0.05). Area under the receiver operating characteristics curve (AUC) for quantitative differentiation between PC and BPA was higher for iodine (AUCIodine = 0.95, AUCHU = 0.90). CONCLUSIONS: Compared with CI, combination of CI/IO improves specificity in the assessment of peritoneal carcinomatosis at comparable sensitivity, particularly in postoperative patients. KEY POINTS: • Combination of iodine overlays and conventional images improves specificity when assessing patients with peritoneal carcinomatosis at comparable sensitivity. • Particularly in postsurgical patients, iodine overlays could help to avoid false-positive diagnosis of peritoneal disease. • Iodine overlays alone provided inferior image quality and assessability than conventional images, while the combination of both received the highest ratings. Iodine overlays should therefore be used in addition to and not as a substitute for conventional images.

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 .

Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI.

OBJECTIVES: Magnetic resonance imaging (MRI) is the method of choice for imaging meningiomas. Volumetric assessment of meningiomas is highly relevant for therapy planning and monitoring. We used a multiparametric deep-learning model (DLM) on routine MRI data including images from diverse referring institutions to investigate DLM performance in automated detection and segmentation of meningiomas in comparison to manual segmentations. METHODS: We included 56 of 136 consecutive preoperative MRI datasets [T1/T2-weighted, T1-weighted contrast-enhanced (T1CE), FLAIR] of meningiomas that were treated surgically at the University Hospital Cologne and graded histologically as tumour grade I (n = 38) or grade II (n = 18). The DLM was trained on an independent dataset of 249 glioma cases and segmented different tumour classes as defined in the brain tumour image segmentation benchmark (BRATS benchmark). The DLM was based on the DeepMedic architecture. Results were compared to manual segmentations by two radiologists in a consensus reading in FLAIR and T1CE. RESULTS: The DLM detected meningiomas in 55 of 56 cases. Further, automated segmentations correlated strongly with manual segmentations: average Dice coefficients were 0.81 ± 0.10 (range, 0.46-0.93) for the total tumour volume (union of tumour volume in FLAIR and T1CE) and 0.78 ± 0.19 (range, 0.27-0.95) for contrast-enhancing tumour volume in T1CE. CONCLUSIONS: The DLM yielded accurate automated detection and segmentation of meningioma tissue despite diverse scanner data and thereby may improve and facilitate therapy planning as well as monitoring of this highly frequent tumour entity. KEY POINTS: • Deep learning allows for accurate meningioma detection and segmentation • Deep learning helps clinicians to assess patients with meningiomas • Meningioma monitoring and treatment planning can be improved.

Metal artifacts in patients with large dental implants and bridges: combination of metal artifact reduction algorithms and virtual monoenergetic images provides an approach to handle even strongest artifacts.

OBJECTIVES: This study compares reduction of strong metal artifacts from large dental implants/bridges using spectral detector CT-derived virtual monoenergetic images (VMI), metal artifact reduction algorithms/reconstructions (MAR), and a combination of both methods (VMIMAR) to conventional CT images (CI). METHODS: Forty-one spectral detector CT (SDCT) datasets of patients that obtained additional MAR reconstructions due to strongest artifacts from large oral implants were included. CI, VMI, MAR, and VMIMAR ranging from 70 to 200 keV (10 keV increment) were reconstructed. Objective image analyses were performed ROI-based by measurement of attenuation (HU) and standard deviation in most pronounced hypo-/hyperdense artifacts as well as artifact impaired soft tissue (mouth floor/soft palate). Extent of artifact reduction, diagnostic assessment of soft tissue, and appearance of new artifacts were rated visually by two radiologists. RESULTS: The hypo-/hyperattenuating artifacts showed an increase and decrease of HU values in MAR and VMIMAR (CI/MAR/VMIMAR-200keV: - 369.8 ± 239.6/- 37.3 ± 109.6/- 46.2 ± 71.0 HU, p < 0.001 and 274.8 ± 170.2/51.3 ± 150.8/36.6 ± 56.0, p < 0.001, respectively). Higher keV values in hyperdense artifacts allowed for additional artifact reduction; however, this trend was not significant. Artifacts in soft tissue were reduced significantly by MAR and VMIMAR. Visually, high-keV VMI, MAR, and VMIMAR reduced artifacts and improved diagnostic assessment of soft tissue. Overcorrection/new artifacts were reported that mostly did not hamper diagnostic assessment. Overall interrater agreement was excellent (ICC = 0.85). CONCLUSIONS: In the presence of strong artifacts due to large oral implants, MAR is a powerful mean for artifact reduction. For hyperdense artifacts, MAR should be supplemented by VMI ranging from 140 to 200 keV. This combination yields optimal artifact reduction and improves the diagnostic image assessment in imaging of the head and neck. KEY POINTS: • Large oral implants can cause strong artifacts. • MAR is a powerful tool for artifact reduction considering such strong artifacts. • Hyperdense artifact reduction is supplemented by VMI of 140-200 keV from SDCT.

Follow-up MRI in multiple sclerosis patients: automated co-registration and lesion color-coding improves diagnostic accuracy and reduces reading time.

OBJECTIVES: In multiple sclerosis (MS), the heterogeneous and numerous appearances of lesions may impair diagnostic accuracy. This study investigates if a combined automated co-registration and lesion color-coding method (AC) improves assessment of MS follow-up MRI compared with conventional reading (CR). METHODS: We retrospectively assessed 70 follow-up MRI of 53 patients. Heterogeneous datasets of diverse scanners and institutions were used. Two readers determined presence of (a) progression, (b) regression, (c) mixed change, or (d) stable disease between the two examinations using corresponding FLAIR sequences in CR and AC-assisted reading. Consensus reference reading was provided by two blinded radiologists. Kappa statistics tested interrater agreement, McNemar's test dichotomous variables, and Wilcoxon's test continuous variables (statistical significance p ≤ 0.05). RESULTS: The cohort comprised 41 female and 12 male patients with a mean age of 40 (± 14) years. Average rating time was reduced from 78 (± 36) to 44 (±22) s with the AC approach (p < 0.001). The time needed to start and match datasets with AC was 14 (± 1) s. Compared with CR, AC improved interrater agreement, both between raters (0.52 vs. 0.67) and between raters and consensus reference reading (0.47/0.5 vs. 0.83/0.78). Compared with CR, the diagnostic accuracy increased from 67 to 90% (reader 1, p < 0.01) and from 70 to 87% (reader 2, p < 0.05) in the AC-assisted reading. CONCLUSIONS: Compared with CR, automated co-registration and lesion color-coding of MS-associated FLAIR-lesions in follow-up MRI increased diagnostic accuracy and reduced the time required for follow-up evaluation significantly. The AC algorithm therefore appears to be helpful to improve MS follow-up assessments in clinical routine. KEY POINTS: • Automated co-registration and lesion color-coding increases diagnostic accuracy in the assessment of MRI follow-up examinations in patients with multiple sclerosis. • Automated co-registration and lesion color-coding reduces reading time of MRI follow-up examinations in patients with multiple sclerosis. • Automated co-registration and lesion color-coding improved interrater agreement in the assessment of MRI follow-up examinations in patients with multiple sclerosis.

Intra-individual consistency of spectral detector CT-enabled iodine quantification of the vascular and renal blood pool.

OBJECTIVES: The objective of this study was to evaluate the intra-individual, longitudinal consistency of iodine measurements regarding the vascular and renal blood pool in patients that underwent repetitive spectral detector computed tomography (SDCT) examinations to evaluate their utility for oncologic imaging. METHODS: Seventy-nine patients with two (n = 53) or three (n = 26) clinically indicated biphasic SDCT scans of the abdomen were retrospectively included. ROI-based measurements of Hounsfield unit (HU) attenuation in conventional images and iodine concentration were performed by an experienced radiologist in the following regions (two ROIs each): abdominal aorta, vena cava inferior, portal vein, and renal cortices. Modified variation coefficients (MVCs) were computed to assess intra-individual longitudinal between the different time points. RESULTS: Variation of HU attenuation and iodine concentration measurements was significantly lower in the venous than in the arterial phase images (attenuation/iodine concentration: arterial - 4.2/- 3.9, venous 0.4/1.0; p ≤ 0.05). Regarding attenuation in conventional images of the arterial phase, the median MVC was - 1.8 (- 20.5-21.3) % within the aorta and - 6.5 (- 44.0-25.0) % within the renal cortex while in the portal venous phase, it was 0.62 (- 11.1-11.7) % and - 1.6 (- 16.2-10.6) %, respectively. Regarding iodine concentration, MVC for arterial phase was - 2.5 (- 22.9-28.4) % within the aorta and - 5.8 (- 55.9-29.6) % within the renal cortex. The referring MVCs of the portal venous phase were - 0.7 (- 17.9-16.9) % and - 2.6 (- 17.6-12.5) %. CONCLUSIONS: Intra-individual iodine quantification of the vascular and cortical renal blood pool at different time points works most accurately in venous phase images whereas measurements conducted in arterial phase images underlay greater variability. KEY POINTS: • There is an intra-individual, physiological variation in iodine map measurements from dual-energy computed tomography. • This variation is smaller in venous phase examinations compared with arterial phase and therefore venous phase images should be preferred to minimize this intra-individual variation. • Care has to be taken, when considering iodine measurements for clinical decision-making, particularly in the context of oncologic initial or follow-up imaging.

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

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

Oversizing of the Woven EndoBridge for Treatment of Intracranial Aneurysms Improves Angiographic Results (WEBINAR).

OBJECTIVE: Several studies have demonstrated a high safety and efficacy profile of the Woven EndoBridge (WEB) for endovascular aneurysm treatment. However, contemporary large-scale studies of the WEB are rare. This multicenter study attempts to set a benchmark for state-of-the-art WEB treatment with consistent application of the WEB oversizing technique. METHODS: This is a retrospective, multicenter study of aneurysms (dome width 2-10 mm) treated with the WEB between 2015 and 2023. Patient and aneurysm characteristics, complications, and clinical and angiographic outcomes were analyzed. RESULTS: The study consisted of 247 patients treated for 251 aneurysms (25.5% ruptured, 5.6% recurrent). WEB implantation was feasible in 98.8%, achieving a mean WEB/dome ratio of 1.2 ± 0.1. The thromboembolic complication rate was 7.2%, which was higher in ruptured versus unruptured aneurysms (hazard ratio: 2.8, 95%CI: 1.0-7.6, P = 0.04), but lower in cases where WEB 17 was used (hazard ratio: 4.0, 95%CI: 1.4-11.2, P = 0.01). Neurological complications occurred in 8 procedures (3.2%), including 3 (1.2%) major, and 5 (2.0%) minor events. Procedural morbidity and mortality were 0.8% and 0%, respectively. Mid-term complete and adequate occlusion rates were 66.3% and 88.4%, respectively. The retreatment rate was 5.2%. Feasibility, complication, and occlusion rates were comparable between typical and atypical aneurysm locations. CONCLUSIONS: Oversizing the WEB and using currently available WEB types in this series resulted in slightly better treatment outcomes compared to early WEB studies, confirming the high safety, feasibility, and efficacy of this technique.

Long-term Safety and Efficacy of the Derivo Embolization Device in a Single-center Series.

PURPOSE: This study analyzes the long-term clinical and angiographic outcomes of the Derivo Embolization Device (DED), an advanced flow diverter device with an electropolished surface, for the treatment of intracranial aneurysms. METHODS: A consecutive series of 101 patients (mean age: 58 years, 72% female) treated with the DED for 122 aneurysms at a single center between 2017 and 2023 was retrospectively analyzed for major (change in National Institutes of Health Stroke Scale [NIHSS] score ≥ 4 points) and minor (change in NIHSS score < 4 points) neurological events, procedural morbidity (increase of at least one point on the modified Rankin Scale), and angiographic results. RESULTS: There were 14 (11%) recurrent aneurysms, 15 (12%) ruptured aneurysms, 26 (21%) posterior circulation aneurysms and 16 (13%) fusiform or dissecting aneurysms. Device deployment failed in 1 case (1%). Procedure-related symptomatic procedural complications consisted of 2 (2%) major events (1 major stroke and 1 vessel perforation with intracranial hemorrhage and infarction) and 6 minor events (6 minor strokes). Procedural morbidity was 5%. There were no late ischemic or hemorrhagic events during follow-up. Complete and favorable aneurysm occlusion was achieved in 54% (40/74) and 62% (46/74) at a mean of 5 months, 71% (27/38) and 87% (33/38) at a mean of 12 months, and 76% (25/33) and 97% (32/33) at a mean of 35 months, respectively. CONCLUSION: The results demonstrate progressive aneurysm occlusion beyond 12 months after DED implantation with an almost 100% favorable occlusion rate. Procedural morbidity was low and there were no late complications.