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Background: Radiopaque breast markers cause artifacts in dedicated spiral breast-computed tomography (SBCT). This study investigates the extent of artifacts in different marker types and the feasibility of reducing artifacts through a metal artifact reduction (MAR) algorithm. Methods: The pilot study included 18 women who underwent contrast-enhanced SBCT. In total, 20 markers of 4 different types were analyzed for artifacts. The extent of artifacts with and without MAR was measured via the consensus of two readers. Image noise was quantitatively evaluated, and the effect of MAR on the detectability of breast lesions was evaluated on a 3-point Likert scale. Results: Breast markers caused significant artifacts that impaired image quality and the detectability of lesions. MAR decreased artifact size in all analyzed cases, even in cases with multiple markers in a single slice. The median length of in-plain artifacts significantly decreased from 31 mm (range 11–51 mm) in uncorrected to 2 mm (range 1–5 mm) in corrected images (p ≤ 0.05). Artifact size was dependent on marker size. Image noise in slices affected by artifacts was significantly lower in corrected (13.6 ± 2.2 HU) than in uncorrected images (19.2 ± 6.8 HU, p ≤ 0.05). MAR improved the detectability of lesions affected by artifacts in 5 out of 11 cases. Conclusion: MAR is feasible in SBCT and improves the image quality and detectability of lesions.

(1) Purpose: to compare right ventricular (RV) functional parameters in children with surgically repaired congenital heart disease (CHD) using single/double breath hold (BH) and free-breathing (FB) real-time compressed sensing (CS) cine cardiac magnetic resonance (cMRI) with standard retrospective segmented multi breath hold (RMB) cine cMRI. (2) Methods: Twenty patients with CHD underwent BH and FB, as well as RMB cine cMRI, at 3T to obtain a stack of continuous axial images of the RV. Two radiologists independently performed qualitative analysis of the image quality (rated on a 5-point scale; 1 = non-diagnostic to 5 = excellent) and quantitative analysis of the RV volume measurements. (3) Results: The best image quality was provided by RMB (4.5; range 2–5) compared to BH (3.9; range 3–5; p = 0.04) and FB (3.6; range 3–5; p < 0.01). The RV functional parameters were comparable among BH, FB, and RMB with a difference of less than 5%. The scan times for BH (44 ± 38 s, p < 0.01) and FB (24 ± 7 s, p < 0.01) were significantly reduced compared to for RMB (261 ± 68 s). (4) Conclusions: CS-FB and CS-BH real-time cine cMRI in children with CHD provides diagnostic image quality with excellent accuracy for measuring RV function with a significantly reduced scan time compared to RMB.

The aim of this study was to assess the diagnostic value of ADC distribution curves for differentiation between benign and malignant parotid gland tumors and to compare with mean ADC values. 73 patients with parotid gland tumors underwent head-and-neck MRI on a 1.5 Tesla scanner prior to surgery and histograms of ADC values were extracted. Histopathological results served as a reference standard for further analysis. ADC histograms were evaluated by comparing their similarity to a reference distribution using Chi2-test-statistics. The assumed reference distribution for benign and malignant parotid gland lesions was calculated after pooling the entire ADC data. In addition, mean ADC values were determined. For both methods, we calculated and compared the sensitivity and specificity between benign and malignant parotid gland tumors and three subgroups (pleomorphic adenoma, Warthin tumor, and malignant lesions), respectively. Moreover, we performed cross-validation (CV) techniques to estimate the predictive performance between ADC distributions and mean values. Histopathological results revealed 30 pleomorphic adenomas, 22 Warthin tumors, and 21 malignant tumors. ADC histogram distribution yielded a better specificity for detection of benign parotid gland lesions (ADChistogram: 75.0% vs. ADCmean: 71.2%), but mean ADC values provided a higher sensitivity (ADCmean: 71.4% vs. ADChistogram: 61.9%). The discrepancies are most pronounced in the differentiation between malignant and Warthin tumors (sensitivity ADCmean: 76.2% vs. ADChistogram: 61.9%; specificity ADChistogram: 81.8% vs. ADCmean: 68.2%). Using CV techniques, ADC distribution revealed consistently better accuracy to differentiate benign from malignant lesions (“leave-one-out CV” accuracy ADChistogram: 71.2% vs. ADCmean: 67.1%). ADC histogram analysis using full distribution curves is a promising new approach for differentiation between primary benign and malignant parotid gland tumors, especially with respect to the advantage in predictive performance based on CV techniques.

To evaluate the reader’s diagnostic performance against the ground truth with and without the help of a novel content-based image retrieval system (CBIR) that retrieves images with similar CT patterns from a database of 79 different interstitial lung diseases. We evaluated three novice readers’ and three resident physicians‘ (with at least three years of experience) diagnostic performance evaluating 50 different CTs featuring 10 different patterns (e.g., honeycombing, tree-in bud, ground glass, bronchiectasis, etc.) and 24 different diseases (sarcoidosis, UIP, NSIP, Aspergillosis, COVID-19 pneumonia etc.). The participants read the cases first without assistance (and without feedback regarding correctness), and with a 2-month interval in a random order with the assistance of the novel CBIR. To invoke the CBIR, a ROI is placed into the pathologic pattern by the reader and the system retrieves diseases with similar patterns. To further narrow the differential diagnosis, the readers can consult an integrated textbook and have the possibility of selecting high-level semantic features representing clinical information (chronic, infectious, smoking status, etc.). We analyzed readers’ accuracy without and with CBIR assistance and further tested the hypothesis that the CBIR would help to improve diagnostic performance utilizing Wilcoxon signed rank test. The novice readers demonstrated an unassisted accuracy of 18/28/44%, and an assisted accuracy of 84/82/90%, respectively. The resident physicians demonstrated an unassisted accuracy of 56/56/70%, and an assisted accuracy of 94/90/96%, respectively. For each reader, as well as overall, Sign test demonstrated statistically significant (p < 0.01) difference between the unassisted and the assisted reads. For students and physicians, Chi²-test and Mann-Whitney-U test demonstrated statistically significant (p < 0.01) difference for unassisted reads and statistically insignificant (p > 0.01) difference for assisted reads. The evaluated CBIR relying on pattern analysis and featuring the option to filter the results of the CBIR by predominant characteristics of the diseases via selecting high-level semantic features helped to drastically improve novices’ and resident physicians’ accuracy in diagnosing interstitial lung diseases in CT.

The primary objective of the study was to compare a spiral breast computed tomography system (SBCT) to digital breast tomosynthesis (DBT) for the detection of microcalcifications (MCs) in breast specimens. The secondary objective was to compare various reconstruction modes in SBCT. In total, 54 breast biopsy specimens were examined with mammography as a standard reference, with DBT, and with a dedicated SBCT containing a photon-counting detector. Three different reconstruction modes were applied for SBCT datasets (Recon1 = voxel size (0.15 mm)3, smooth kernel; Recon2 = voxel size (0.05 mm)3, smooth kernel; Recon3 = voxel size (0.05 mm)3, sharp kernel). Sensitivity and specificity of DBT and SBCT for the detection of suspicious MCs were analyzed, and the McNemar test was used for comparisons. Diagnostic confidence of the two readers (Likert Scale 1 = not confident; 5 = completely confident) was analyzed with ANOVA. Regarding detection of MCs, reader 1 had a higher sensitivity for DBT (94.3%) and Recon2 (94.9%) compared to Recon1 (88.5%; p < 0.05), while sensitivity for Recon3 was 92.4%. Respectively, reader 2 had a higher sensitivity for DBT (93.0%), Recon2 (92.4%), and Recon3 (93.0%) compared to Recon1 (86.0%; p < 0.05). Specificities ranged from 84.7–94.9% for both readers (p > 0.05). The diagnostic confidence of reader 1 was better with SBCT than with DBT (DBT 4.48 ± 0.88, Recon1 4.77 ± 0.66, Recon2 4.89 ± 0.44, and Recon3 4.75 ± 0.72; DBT vs. Recon1/2/3: p < 0.05), while reader 2 found no differences. Sensitivity and specificity for the detection of MCs in breast specimens is equal for DBT and SBCT when a small voxel size of (0.05 mm)3 is used with an equal or better diagnostic confidence for SBCT compared to DBT.

Low-dose dual-source computed tomography (DSCT) protocols for the evaluation of lung diseases in children and adolescents are of importance since this age group is particularly prone to radiation damage. The aim of this study was to evaluate image quality of low-dose DSCT of the lung and to assess the potential of radiation dose reduction compared to digital radiographs (DR). Three groups, each consisting of 19 patients, were examined with different DSCT protocols using tin prefiltration (Sn96/64/32 ref. mAs at 100 kV). Different strengths of iterative reconstruction were applied (ADMIRE 2/3/4). DSCT groups were compared to 19 matched patients examined with posterior–anterior DR. Diagnostic confidence, detectability of anatomical structures and small lung lesions were evaluated on a 4-point Likert scale (LS 1 = unacceptable, 4 = fully acceptable; a value ≥ 3 was considered acceptable). Effective dose (ED) was 31-/21-/9-fold higher in Sn96/Sn64/Sn32 compared to DR. Diagnostic confidence was sufficient in Sn96/Sn64 (LS 3.4/3.2), reduced in Sn32 (LS 2.7) and the worst in DR (LS 2.4). In DSCT, detectability of small anatomical structures was always superior to DR (p < 0.05). Mean lesion size ranged from 5.1–7 mm; detectability was acceptable in all DSCT groups (LS 3.0–3.4) and superior to DR (LS 1.9; p < 0.05). Substantial dose lowering in DSCT of the pediatric lung enables acceptable detectability of small lung lesions with a radiation dose being about 10-fold higher compared to DR.