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.

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.

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.

[Imaging in the acute abdomen - part 1 : Case examples of frequent organ-specific causes: liver, gallbladder, pancreas, spleen and vessels]. / Bildgebung bei akutem Abdomen ­ Teil 1 : Fallbeispiele häufiger organbezogener Ursachen: Leber, Gallenblase, Pankreas, Milz und Gefäße.

The acute abdomen is characterized by acute abdominal pain with defensive muscular tension, can be triggered by a variety of diseases and sometimes represents a life-threatening condition. After clinical inspection, in most cases dedicated imaging should be performed immediately. The frequently causal appendicitis and cholecystitis can mostly be diagnosed with ultrasound. In other cases with unclear ultrasound findings or unclear severe symptoms, computer tomography (CT) is usually necessary without delay. In contrast, magnetic resonance imaging (MRI) is predominantly indicated in pregnant women and children with unclear ultrasound findings. Thus, the radiologist is an important gatekeeper in the diagnostics of acute abdomen. The radiologist should therefore be familiar with the correct imaging indications, the frequent and rare causes as well as the corresponding morphological imaging characteristics.

[Imaging in the acute abdomen-part 2 : Case examples of frequent organ-specific causes: gastrointestinal tract and urogenital system]. / Bildgebung bei akutem Abdomen ­ Teil 2 : Fallbeispiele häufiger organbezogener Ursachen: Gastrointestinaltrakt und Urogenitalsystem.

The acute abdomen is a potentially life-threatening condition and requires a rapid diagnosis. After clinical inspection and in cases with unclear ultrasound findings or unclear serious symptoms computed tomography (CT) and in pregnant women and children magnetic resonance imaging (MRI) is usually necessary. This second part of "Imaging in the acute abdomen" focuses on frequent organ specific causes of the gastrointestinal tract and the urogenital system.

Transdiaphragmatic Mucormycosis.

Mucormycosis is a life-threatening infection. This is the first report of transdiaphragmatic mucormycosis in a series of 3 patients. We observed this phenomenon in 11% of patients. Clinicians should be aware of this possibly underreported entity, and as a consequence we envision more comprehensive imaging studies in patients with mucormycosis.

Five-minute knee MRI: An AI-based super resolution reconstruction approach for compressed sensing. A validation study on healthy volunteers.

PURPOSE: To investigate the potential of combining Compressed Sensing (CS) and a newly developed AI-based super resolution reconstruction prototype consisting of a series of convolutional neural networks (CNN) for a complete five-minute 2D knee MRI protocol. METHODS: In this prospective study, 20 volunteers were examined using a 3T-MRI-scanner (Ingenia Elition X, Philips). Similar to clinical practice, the protocol consists of a fat-saturated 2D-proton-density-sequence in coronal, sagittal and transversal orientation as well as a sagittal T1-weighted sequence. The sequences were acquired with two different resolutions (standard and low resolution) and the raw data reconstructed with two different reconstruction algorithms: a conventional Compressed SENSE (CS) and a new CNN-based algorithm for denoising and subsequently to interpolate and therewith increase the sharpness of the image (CS-SuperRes). Subjective image quality was evaluated by two blinded radiologists reviewing 8 criteria on a 5-point Likert scale and signal-to-noise ratio calculated as an objective parameter. RESULTS: The protocol reconstructed with CS-SuperRes received higher ratings than the time-equivalent CS reconstructions, statistically significant especially for low resolution acquisitions (e.g., overall image impression: 4.3 ±â€¯0.4 vs. 3.4 ±â€¯0.4, p < 0.05). CS-SuperRes reconstructions for the low resolution acquisition were comparable to traditional CS reconstructions with standard resolution for all parameters, achieving a scan time reduction from 11:01 min to 4:46 min (57 %) for the complete protocol (e.g. overall image impression: 4.3 ±â€¯0.4 vs. 4.0 ±â€¯0.5, p < 0.05). CONCLUSION: The newly-developed AI-based reconstruction algorithm CS-SuperRes allows to reduce scan time by 57% while maintaining unchanged image quality compared to the conventional CS reconstruction.

CT-derived lung vessel morphology correlates with prognostic markers in precapillary pulmonary hypertension.

BACKGROUND: While computed tomography pulmonary angiography (CTPA) is an integral part of the work-up in patients with suspected pulmonary hypertension (PH), there is no established CTPA-derived prognostic marker. We aimed to assess whether quantitative readouts of lung vessel morphology correlate with established prognostic indicators in PH. METHODS: We applied a fully-automatic in-house developed algorithm for segmentation of arteries and veins to determine lung vessel morphology in patients with precapillary PH who underwent right heart catheterization and CTPA between May 2016 and May 2019. Primary endpoint of this retrospective study was the calculation of receiver operating characteristics for identifying low and high mortality risk according to the 3-strata risk assessment model presented in the current guidelines. RESULTS: We analyzed 73 patients, median age 65 years (interquartile range (IQR): 54-76), female/male ratio 35/38, median mean pulmonary arterial pressure 37 mm Hg (IQR: 30-46), and found significant correlations with important prognostic factors in pulmonary arterial hypertension. N-terminal pro-brain natriuretic peptide, cardiac index, mixed venous oxygen saturation, and 6-minute walking distance were correlated with the ratio of the number of arteries over veins with vessel diameters of 6-10 mm (Spearman correlation coefficients ρ = 0.64, p < 0.001; ρ = -0.60, p < 0.001; ρ = -0.47, p = 0.005; ρ = -0.45, p = 0.001, respectively). This ratio predicted a low- and high-risk score with an area under the curve of 0.73 (95% confidence interval (CI): 0.56-0.90) and 0.86 (95% CI: 0.74-0.97), respectively. CONCLUSIONS: The ratio of the number of arteries over veins with diameters between 6 and 10 mm is significantly correlated with prognostic markers in pulmonary hypertension and predicts low and high mortality risk.

Light-Controlled Electric Stimulation with Organic Electrolytic Photocapacitors Achieves Complex Neuronal Network Activation: Semi-Chronic Study in Cortical Cell Culture and Rat Model.

Neurostimulation employing photoactive organic semiconductors offers an appealing alternative to conventional techniques, enabling targeted action and wireless control through light. In this study, organic electrolytic photocapacitors (OEPC) are employed to investigate the effects of light-controlled electric stimulation on neuronal networks in vitro and in vivo. The interactions between the devices and biological systems are characterized. Stimulation of primary rat cortical neurons results in an elevated expression of c-Fos within a mature neuronal network. OEPC implantation for three weeks and subsequent stimulation of the somatosensory cortex leads to an increase of c-Fos in neurons at the stimulation site and in connected brain regions (entorhinal cortex, hippocampus), both in the ipsi- and contralateral hemispheres. Reactivity of glial and immune cells after semi-chronic implantation of OEPC in the rat brain is comparable to that of surgical controls, indicating minimal foreign body response. Device functionality is further substantiated through retained charging dynamics following explantation. OEPC-based, light-controlled electric stimulation has a significant impact on neural responsiveness. The absence of detrimental effects on both the brain and device encourages further use of OEPC as cortical implants. These findings highlight its potential as a novel mode of neurostimulation and instigate further exploration into applications in fundamental neuroscience.

Robustness of radiomic features in healthy abdominal parenchyma of patients with repeated examinations on dual-layer dual-energy CT.

OBJECTIVES: Robustness of radiomic features in physiological tissue is an important prerequisite for quantitative analysis of tumor biology and response assessment. In contrast to previous studies which focused on different tumors with mostly short scan-re-scan intervals, this study aimed to evaluate the robustness of radiomic features in cancer-free patients and over a clinically encountered inter-scan interval. MATERIALS AND METHODS: Patients without visible tumor burden who underwent at least two portal-venous phase dual energy CT examinations of the abdomen between May 2016 and January 2020 were included, while macroscopic tumor burden was excluded based upon follow-up imaging for all patients (≥3 months). Further, patients were excluded if no follow-up imaging was available, or if the CT protocol showed deviations between repeated examinations. Circular regions of interest were placed and proofread by two board-certified radiologists (4 years and 5 years experience) within the liver (segments 3 and 6), the psoas muscle (left and right), the pancreatic head, and the spleen to obtain radiomic features from normal-appearing organ parenchyma using PyRadiomics. Radiomic feature robustness was tested using the concordance correlation coefficient with a threshold of 0.75 considered indicative for deeming a feature robust. RESULTS: In total, 160 patients with 480 repeated abdominal CT examinations (range: 2-4 per patient) were retrospectively included in this single-center, IRB-approved study. Considering all organs and feature categories, only 4.58 % (25/546) of all features were robust with the highest rate being found in the first order feature category (20.37 %, 22/108). Other feature categories (grey level co-occurrence matrix, grey level dependence matrix, grey level run length matrix, grey level size zone matrix, and neighborhood gray-tone difference matrix) yielded an overall low percentage of robust features (range: 0.00 %-1.19 %). A subgroup analysis revealed the reconstructed field of view and the X-ray tube current as determinants of feature robustness (significant differences in subgroups for all organs, p < 0.001) as well as the size of the region of interest (no significant difference for the pancreatic head with p = 0.135, significant difference with p < 0.001 for all other organs). CONCLUSION: Radiomic feature robustness obtained from cancer-free subjects with repeated examinations using a consistent protocol and CT scanner was limited, with first order features yielding the highest proportion of robust features.

Deep-Learning-Based Image Denoising in Imaging of Urolithiasis: Assessment of Image Quality and Comparison to State-of-the-Art Iterative Reconstructions.

This study aimed to compare the image quality and diagnostic accuracy of deep-learning-based image denoising reconstructions (DLIDs) to established iterative reconstructed algorithms in low-dose computed tomography (LDCT) of patients with suspected urolithiasis. LDCTs (CTDIvol, 2 mGy) of 76 patients (age: 40.3 ± 5.2 years, M/W: 51/25) with suspected urolithiasis were retrospectively included. Filtered-back projection (FBP), hybrid iterative and model-based iterative reconstruction (HIR/MBIR, respectively) were reconstructed. FBP images were processed using a Food and Drug Administration (FDA)-approved DLID. ROIs were placed in renal parenchyma, fat, muscle and urinary bladder. Signal- and contrast-to-noise ratios (SNR/CNR, respectively) were calculated. Two radiologists evaluated image quality on five-point Likert scales and urinary stones. The results showed a progressive decrease in image noise from FBP, HIR and DLID to MBIR with significant differences between each method (p < 0.05). SNR and CNR were comparable between MBIR and DLID, while it was significantly lower in HIR followed by FBP (e.g., SNR: 1.5 ± 0.3; 1.4 ± 0.4; 1.0 ± 0.3; 0.7 ± 0.2, p < 0.05). Subjective analysis confirmed best image quality in MBIR, followed by DLID and HIR, both being superior to FBP (p < 0.05). Diagnostic accuracy for urinary stone detection was best using MBIR (0.94), lowest using FBP (0.84) and comparable between DLID (0.90) and HIR (0.90). Stone size measurements were consistent between all reconstructions and showed excellent correlation (r2 = 0.958-0.975). In conclusion, MBIR yielded the highest image quality and diagnostic accuracy, with DLID producing better results than HIR and FBP in image quality and matching HIR in diagnostic precision.

Artificial Intelligence in Ophthalmology - Status Quo and Future Perspectives.

Artificial intelligence (AI) is an emerging technology in healthcare and holds the potential to disrupt many arms in medical care. In particular, disciplines using medical imaging modalities, including e.g. radiology but ophthalmology as well, are already confronted with a wide variety of AI implications. In ophthalmologic research, AI has demonstrated promising results limited to specific diseases and imaging tools, respectively. Yet, implementation of AI in clinical routine is not widely spread due to availability, heterogeneity in imaging techniques and AI methods. In order to describe the status quo, this narrational review provides a brief introduction to AI ("what the ophthalmologist needs to know"), followed by an overview of different AI-based applications in ophthalmology and a discussion on future challenges.Abbreviations: Age-related macular degeneration, AMD; Artificial intelligence, AI; Anterior segment OCT, AS-OCT; Coronary artery calcium score, CACS; Convolutional neural network, CNN; Deep convolutional neural network, DCNN; Diabetic retinopathy, DR; Machine learning, ML; Optical coherence tomography, OCT; Retinopathy of prematurity, ROP; Support vector machine, SVM; Thyroid-associated ophthalmopathy, TAO.

Association between pouch morphology, cardiovascular risk factors and ischemic brain lesions in patients with left-sided septal pouches.

BACKGROUND: Left atrial outpouching structures such as left atrial diverticula (LADs) and left-sided septal pouches (LSSPs) might be a source of cryptogenic stroke. This imaging study evaluates the association between pouch morphology, patient comorbidities and ischemic brain lesions (IBLs). METHODS: This is a retrospective single-center analysis of 195 patients who received both a cardiac CT and a cerebral MRI. LADs, LSSPs, and IBLs were retrospectively identified. Size measurements included pouch width, length and volume for LADs and circumference, area and volume for LSSPs. The association between LADs/LSSPs, IBLs and cardiovascular comorbidities was determined by univariate and bivariate regression analyses. RESULTS: The prevalence and mean volume were 36.4% and 372 ± 569 mm3 for LSSPs, and 40.5% and 415 ± 541 mm3 for LADs. The IBL prevalence was 67.6% in the LSSP group and 48.1% in the LAD group. LSSPs had 2.9-fold increased hazards of IBLs (95%CI: 1.2-7.4, p = 0.024), and LADs showed no significant correlation with IBLs. Size measurements had no impact on IBLs. A co-existing LSSP was associated with an increased prevalence of IBLs in patients with coronary artery disease (HR: 1.5, 95%CI: 1.1-1.9, p = 0.048), heart failure (HR: 3.7, 95%CI: 1.1-14.6, p = 0.032), arterial hypertension (HR: 1.9, 95%CI: 1.1-3.3, p = 0.017), and hyperlipidemia (HR: 2.2, 95%CI: 1.1-4.4, p = 0.018). CONCLUSION: Co-existing LSSPs were associated with IBLs in patients with cardiovascular risk factors, however, pouch morphology did not correlate with the IBL rate. Upon confirmation by further studies, these findings might be considered in the treatment, risk stratification, and stroke prophylaxis of these patients.

Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals.

Purpose: The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of bone marrow iodine uptake after intravenous contrast application, and examine its dependence on vBMD, iodine blood pool, patient age, and sex. Method: Retrospective analysis of oncological patients without evidence of metastatic disease. DECT examinations were performed on a spectral detector CT scanner in portal venous contrast phase. The thoracic and lumbar spine were segmented by a pre-trained neural network, obtaining volumetric iodine concentration data [mg/ml]. vBMD was assessed using a phantomless, CE-certified software [mg/cm3]. The iodine blood pool was estimated by ROI-based measurements in the great abdominal vessels. A multivariate regression model was fit with the dependent variable "median bone marrow iodine uptake". Standardized regression coefficients (ß) were calculated to assess the impact of each covariate. Results: 678 consecutive DECT exams of 189 individuals (93 female, age 61.4 ± 16.0 years) were evaluated. AI-based segmentation provided volumetric data of 97.9% of the included vertebrae (n=11,286). The 95th percentile of bone marrow iodine uptake, as a surrogate for the upper margin of the physiological distribution, ranged between 4.7-6.4 mg/ml. vBMD (p <0.001, mean ß=0.50) and portal vein iodine blood pool (p <0.001, mean ß=0.43) mediated the strongest impact. Based thereon, adjusted reference values were calculated. Conclusion: The bone marrow iodine uptake demonstrates a distinct profile depending on vBMD, iodine blood pool, patient age, and sex. This study is the first to provide the adjusted reference values.

Is there an association between left atrial outpouching structures and recurrence of atrial fibrillation after catheter ablation?

OBJECTIVE: The aim of this study was to investigate the impact of left atrial diverticula (LADs), left sided septal pouches (LSSPs) and middle right pulmonary veins (MRPVs) on recurrent atrial fibrillation (rAF) in patients undergoing laser pulmonary vein isolation procedure (PVI). MATERIAL AND METHODS: This retrospective study enrolled 139 patients with pre-procedural multiple detector computed tomography (MDCT) imaging and 12 months follow-up examination. LADs, LSSPs and MRPV were identified by two radiologists on a dedicated workstation using multiplanar reconstructions and volume rendering technique. Univariate and bivariate regression analyses with patient demographics and cardiovascular risk factors as covariates were performed to reveal independent factors associated with rAF. RESULTS: LADs were recorded in 41 patients (29%), LSSPs in 20 (14%) and MRPVs in 15 (11%). The right anterosuperior wall of the left atrium was the most prevalent location of LADs (68%). rAF occured in 20 patients, thereof, 15 exhibited an outpouching structure of the left atrium (LAD: 9, LSSP: 2 and MRPV: 3). Presence of an LAD (HR: 2.7, 95%CI: 1.0-8.4, p = 0.04) and permanent AF (HR: 4.8, 95%CI: 1.5-16.3, p = 0.01) were independently associated with rAF. CONCLUSIONS: LAD, LSSP and MRPV were common findings on pre-procedural cardiac computed tomography. LADs were revealed as potential independent risk factor of rAF, which might be considered for treatment planning and post-treatment observation.

Dual-Energy CT, Virtual Non-Calcium Bone Marrow Imaging of the Spine: An AI-Assisted, Volumetric Evaluation of a Reference Cohort with 500 CT Scans.

Virtual non-calcium (VNCa) images from dual-energy computed tomography (DECT) have shown high potential to diagnose bone marrow disease of the spine, which is frequently disguised by dense trabecular bone on conventional CT. In this study, we aimed to define reference values for VNCa bone marrow images of the spine in a large-scale cohort of healthy individuals. DECT was performed after resection of a malignant skin tumor without evidence of metastatic disease. Image analysis was fully automated and did not require specific user interaction. The thoracolumbar spine was segmented by a pretrained convolutional neuronal network. Volumetric VNCa data of the spine's bone marrow space were processed using the maximum, medium, and low calcium suppression indices. Histograms of VNCa attenuation were created for each exam and suppression setting. We included 500 exams of 168 individuals (88 female, patient age 61.0 ± 15.9). A total of 8298 vertebrae were segmented. The attenuation histograms' overlap of two consecutive exams, as a measure for intraindividual consistency, yielded a median of 0.93 (IQR: 0.88-0.96). As our main result, we provide the age- and sex-specific bone marrow attenuation profiles of a large-scale cohort of individuals with healthy trabecular bone structure as a reference for future studies. We conclude that artificial-intelligence-supported, fully automated volumetric assessment is an intraindividually robust method to image the spine's bone marrow using VNCa data from DECT.

Value of spectral detector computed tomography to differentiate infected from noninfected thoracoabominal fluid collections.

PURPOSE: To investigate the diagnostic value of spectral detector CT (SDCT)-derived virtual non-contrast (VNC), virtual monoenergetic images (VMI) and iodine overlays (IO) for distinguishing infected from noninfected fluid collections (FC) in the chest or abdomen. METHOD: This retrospective study included 58 patients with venous phase SDCT with 77 FC. For all included FC, microbiological analysis of aspirated fluid served as reference. For quantitative analysis, wall thickness was measured, and (ROI)-based analysis performed within the fluid, the FC's wall (if any) and the aorta. Two radiologists qualitatively evaluated visibility of wall enhancement, diagnostic confidence regarding infection of fluid collection, confidence of CT-guided drainage catheter placement and visibility of anatomical landmarks in conventional images (CI) and VNC, VMI40keV, IO. RESULTS: Wall thickness significantly differed between infected (n = 46) and noninfected (n = 31) FC (3.5 ± 1.8 mm vs. 1.4 ± 1.8 mm, AUC = 0.81; p < 0.05). Fluid attenuation and wall enhancement was significantly higher in infected as compared to noninfected FC in all reconstructions (p < 0.05, respectively). Highest AUC regarding A) attenuation in fluid was yielded in CI and VMI70,80keV (0.75); B) wall enhancement in CI (0.88) followed by iodine concentration (0.86). Contrast-to-noise ratio of wall vs. fluid was highest in VMI40keV (p < 0.05). All assessed qualitative parameters received significantly higher ratings when using spectral reconstructions vs. CI (p for all <0.05), except for visibility of wall enhancement. CONCLUSION: Spectral reconstructions improve the assessment of infected from noninfected thoracoabdominal fluid collections and depiction of wall enhancement. Diagnostic performance of the quantitative measurements in spectral reconstructions were comparable with measurements in conventional images.

Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.

PURPOSE: Volumetric assessment of meningiomas represents a valuable tool for treatment planning and evaluation of tumor growth as it enables a more precise assessment of tumor size than conventional diameter methods. This study established a dedicated meningioma deep learning model based on routine magnetic resonance imaging (MRI) data and evaluated its performance for automated tumor segmentation. METHODS: The MRI datasets included T1-weighted/T2-weighted, T1-weighted contrast-enhanced (T1CE) and FLAIR of 126 patients with intracranial meningiomas (grade I: 97, grade II: 29). For automated segmentation, an established deep learning model architecture (3D deep convolutional neural network, DeepMedic, BioMedIA) operating on all four MR sequences was used. Segmentation included the following two components: (i) contrast-enhancing tumor volume in T1CE and (ii) total lesion volume (union of lesion volume in T1CE and FLAIR, including solid tumor parts and surrounding edema). Preprocessing of imaging data included registration, skull stripping, resampling, and normalization. After training of the deep learning model using manual segmentations by 2 independent readers from 70 patients (training group), the algorithm was evaluated on 56 patients (validation group) by comparing automated to ground truth manual segmentations, which were performed by 2 experienced readers in consensus. RESULTS: Of the 56 meningiomas in the validation group 55 were detected by the deep learning model. In these patients the comparison of the deep learning model and manual segmentations revealed average dice coefficients of 0.91 ± 0.08 for contrast-enhancing tumor volume and 0.82 ± 0.12 for total lesion volume. In the training group, interreader variabilities of the 2 manual readers were 0.92 ± 0.07 for contrast-enhancing tumor and 0.88 ± 0.05 for total lesion volume. CONCLUSION: Deep learning-based automated segmentation yielded high segmentation accuracy, comparable to manual interreader variability.

Value of spectral detector CT for pretherapeutic, locoregional assessment of esophageal cancer.

PURPOSE: To investigate the diagnostic value of spectral detector dual-energy CT-derived low-keV virtual monoenergetic images (VMI) and iodine overlays (IO) for locoregional, pretherapeutic assessment of esophageal cancer. METHOD: 74 patients with biopsy-proven esophageal cancer who underwent pre-therapeutic, portal-venous-phase staging examinations of the chest and abdomen were retrospectively included. Quantitative image analysis was performed ROI-based within the tumor, healthy esophageal wall, peri-esophageal lymph nodes, azygos vein, aorta, liver, diaphragm, and mediastinal fat. Two radiologists evaluated delineation of the primary tumor and locoregional lymph nodes, assessment of the celiac trunk and diagnostic certainty regarding tumor infiltration in conventional images (CI), VMI from 40 to 70 keV and IO. Moreover, presence/absence of advanced tumor infiltration (T3/T4) was determined binary using all available images. RESULTS: VMI40-60keV showed significantly higher attenuation and signal-to-noise ratio compared to CI for all assessed ROIs, peaking at VMI40keV (p < 0.05). Contrast-to-noise ratio of tumor/esophagus (VMI40keV/CI: 7.7 ±â€¯4.7 vs. 2.3 ±â€¯1.5), tumor/diaphragm (VMI40keV/CI: 9.0 ±â€¯5.5 vs. 2.2 ±â€¯1.7) and tumor/liver (4.3 ±â€¯5.5 vs. 1.9 ±â€¯2.1) were all significantly higher compared to CI (p < 0.05). Qualitatively, lymph node delineation and diagnostic certainty regarding tumor infiltration received highest ratings both in IO and VMI40keV, whereas vascular assessment was rated highest in VMI40keV and primary tumor delineation in IO. Sensitivity/Specificity/Accuracy for detecting advanced tumor infiltration using the combination of CI, VMI40-70keV and IO was 42.4 %/82.0 %/56.3 %. CONCLUSIONS: IO and VMI40-60keV improve qualitative assessment of the primary tumor and depiction of lymph nodes and vessels at pretherapeutic SDCT of esophageal cancer patients yet do not mitigate the limitations of CT in determining tumor infiltration.