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

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

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

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

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

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

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.

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.

Dose independent characterization of renal stones by means of dual energy computed tomography and machine learning: an ex-vivo study.

OBJECTIVES: To predict the main component of pure and mixed kidney stones using dual-energy computed tomography and machine learning. METHODS: 200 kidney stones with a known composition as determined by infrared spectroscopy were examined using a non-anthropomorphic phantom on a spectral detector computed tomography scanner. Stones were of either pure (monocrystalline, n = 116) or compound (dicrystalline, n = 84) composition. Image acquisition was repeated twice using both, normal and low-dose protocols, respectively (ND/LD). Conventional images and low and high keV virtual monoenergetic images were reconstructed. Stones were semi-automatically segmented. A shallow neural network was trained using data from ND1 acquisition split into training (70%), testing (15%) and validation-datasets (15%). Performance for ND2 and both LD acquisitions was tested. Accuracy on a per-voxel and a per-stone basis was calculated. RESULTS: Main components were: Whewellite (n = 80), weddellite (n = 21), Ca-phosphate (n = 39), cysteine (n = 20), struvite (n = 13), uric acid (n = 18) and xanthine stones (n = 9). Stone size ranged from 3 to 18 mm. Overall accuracy for predicting the main component on a per-voxel basis attained by ND testing dataset was 91.1%. On independently tested acquisitions, accuracy was 87.1-90.4%. CONCLUSIONS: Even in compound stones, the main component can be reliably determined using dual energy CT and machine learning, irrespective of dose protocol. KEY POINTS: • Spectral Detector Dual Energy CT and Machine Learning allow for an accurate prediction of stone composition. • Ex-vivo study demonstrates the dose independent assessment of pure and compound stones. • Lowest accuracy is reported for compound stones with struvite as main component.

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.

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.

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 .

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.

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.

Correction to: CT metal artifacts in patients with total hip replacements: for artifact reduction monoenergetic reconstructions and post-processing algorithms are both efficient but not similar.

The original version of this article, published on 03 May 2018, unfortunately contained a mistake. The following correction has therefore been made in the original.

Precision and reliability of liver iodine quantification from spectral detector CT: evidence from phantom and patient data.

OBJECTIVE: To comprehensively assess precision, reproducibility, and repeatability of iodine maps from spectral detector CT (SDCT) in a phantom and in patients with repetitive examination of the abdomen. METHODS: Seventy-seven patients who underwent examination two (n = 52) or three (n = 25) times according to clinical indications were included in this IRB-approved, retrospective study. The anthropomorphic liver phantom and all patients were scanned with a standardized protocol (SSDE in patients 15.8 mGy). In patients, i.v. contrast was administered and portal venous images were acquired using bolus-tracking technique. The phantom was scanned three times at three time points; in one acquisition, image reconstruction was repeated three times. Region of interest (ROI) were placed automatically (phantom) or manually (patients) in the liver parenchyma (mimic) and the portal vein; attenuation in conventional images (CI [HU]) and iodine map concentrations (IM [mg/ml]) were recorded. The coefficient of variation (CV [%]) was used to compare between repetitive acquisitions. If present, additional ROI were placed in cysts (n = 29) and hemangioma (n = 29). RESULTS: Differences throughout all phantom examinations were < 2%. In patients, differences between two examinations were higher (CV for CI/IM: portal vein, 2.5%/3.2%; liver parenchyma, -0.5%/-3.0% for CI/IM). In 80% of patients, these differences were within a ± 20% limit. Differences in benign liver lesions were even higher (68% and 38%, for CI and IM, respectively). CONCLUSIONS: Iodine maps from SDCT allow for reliable quantification of iodine content in phantoms; while in patients, rather large differences between repetitive examinations are likely due to differences in biological distribution. This underlines the need for careful clinical interpretation and further protocol optimization. KEY POINTS: • Spectral detector computed tomography allows for reliable quantification of iodine in phantoms. • In patients, the offset between repetitive examinations varies by 20%, likely due to differences in biological distribution. • Clinically, iodine maps should be interpreted with caution and should take the intra-individual variability of iodine distribution over time into account.

Accuracy of iodine density thresholds for the separation of vertebral bone metastases from healthy-appearing trabecular bone in spectral detector computed tomography.

PURPOSE: To evaluate quantitative iodine density mapping (IDM) with spectral detector computed tomography (SDCT) as a quantitative biomarker for separation of vertebral trabecular bone metastases (BM) from healthy-appearing trabecular bone (HTB). MATERIALS AND METHODS: IRB-approved retrospective single-center-study of portal venous SDCT datasets acquired between June 2016 and March 2017. Inclusion of 43 consecutive cancer patients with BM and 40 without. Target lesions and non-affected control vertebrae were defined using follow-up imaging, MRI, and/or bone scintigraphy. ID and standard deviation were determined with ROI measures by two readers in (a) bone metastases, (b) HTB of BM patients and controls, and (c) ID of various vessels. Volumetric bone mineral density (vBMD) of the lumbar spine and age were recorded. Multivariate ROC analyses und Wilcoxon test were used to determine thresholds for separation of BM and HTB. p < 0.05 was considered significant. RESULTS: ID measurements of 40 target lesions and 83 reference measurements of HTB were acquired. Age (p < 0.0001) and vBMD (p < 0.05) affected ID measurements independently in multivariate models. There were significant differences of ID between metastases (n = 43) and HTB ID (n = 124; mean 5.5 ± 0.9 vs. 3.5 ± 0.9; p < 0.0001), however, with considerable overlap. In univariate analysis, increased ID discriminated bone lesions (AUC 0.90) with a maximum combined specificity/sensitivity of 77.5%/90.7% when applying a threshold of 4.5 mg/ml. Multivariate regression models improved significantly when considering vBMD, the noise of ID, and vertebral venous ID (AUC 0.98). CONCLUSION: IDM of SDCT yielded a statistical separation of vertebral bone lesions and HTB. Adjustment for confounders such as age and lumbar vBMD as well as for vertebral venous ID and lesion heterogeneity improved discrimination of trabecular lesions. KEY POINTS: • SDCT iodine density mapping provides the possibility for quantitative analysis of iodine uptake in tissue, which allows to differentiate bone lesions from healthy bone marrow. • Age and vBMD have a significant impact on iodine density measurements. • Iodine density measured in SDCT yielded highest sensitivity and specificity for the statistical differentiation of vertebral trabecular metastases and healthy trabecular bone using an iodine density threshold of 4.5 mg/ml (most performant)-5.0 mg/ml (optimized for specificity).