Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging

BACKGROUND To assess the accuracy of fully automated deep learning (DL) based coronary artery calcium scoring (CACS) from non-contrast computed tomography (CT) as acquired for attenuation correction (AC) of cardiac single-photon-emission computed tomography myocardial perfusion imaging (SPECT-MPI). METHODS AND RESULTS Patients were enrolled in this study as part of a larger prospective study (NCT03637231). In this study, 56 Patients who underwent cardiac SPECT-MPI due to suspected coronary artery disease (CAD) were prospectively enrolled. All patients underwent non-contrast CT for AC of SPECT-MPI twice. CACS was manually assessed (serving as standard of reference) on both CT datasets (n = 112) and by a cloud-based DL tool. The agreement in CAC scores and CAC score risk categories was quantified. For the 112 scans included in the analysis, interscore agreement between the CAC scores of the standard of reference and the DL tool was 0.986. The agreement in risk categories was 0.977 with a reclassification rate of 3.6%. Heart rate, image noise, body mass index (BMI), and scan did not significantly impact (p=0.09 - p=0.76) absolute percentage difference in CAC scores. CONCLUSION A DL tool enables a fully automated and accurate estimation of CAC scores in patients undergoing non-contrast CT for AC of SPECT-MPI

Amide Proton Transfer Contrast Distribution in Different Brain Regions in Young Healthy Subjects

ObjectivesTo define normal signal intensity values of amide proton transfer-weighted (APTw) magnetic resonance (MR) imaging in different brain regions.Materials and MethodsTwenty healthy subjects (9 females, mean age 29 years, range 19 – 37 years) underwent MR imaging at 3 Tesla. 3D APTw (RF saturation B1,rms = 2 μT, duration 2 s, 100% duty cycle) and 2D T2-weighted turbo spin echo (TSE) images were acquired. Postprocessing (image fusion, ROI measurements of APTw intensity values in 22 different brain regions) was performed and controlled by two independent neuroradiologists. Values were measured separately for each brain hemisphere. A subject was scanned both in prone and supine position to investigate differences between hemispheres. A mixed model on a 5% significance level was used to assess the effect of gender, brain region and side on APTw intensity values.ResultsMean APTw intensity values in the hippocampus and amygdala varied between 1.13 and 1.57%, in the deep subcortical nuclei (putamen, globus pallidus, head of caudate nucleus, thalamus, red nucleus, substantia nigra) between 0.73 and 1.84%, in the frontal, occipital and parietal cortex between 0.56 and 1.03%; in the insular cortex between 1.11 and 1.15%, in the temporal cortex between 1.22 and 1.37%, in the frontal, occipital and parietal white matter between 0.32 and 0.54% and in the temporal white matter between 0.83 and 0.89%. APTw intensity values were significantly impacted both by brain region (p < 0.001) and by side (p < 0.001), whereby overall values on the left side were higher than on the right side (1.13 vs. 0.9%). Gender did not significantly impact APTw intensity values (p = 0.24). APTw intensity values between the left and the right side were partially reversed after changing the position of one subject from supine to prone.ConclusionWe determined normal baseline APTw intensity values in different anatomical localizations in healthy subjects. APTw intensity values differed both between anatomical regions and between left and right brain hemisphere

Semi-automated volumetry of pulmonary nodules: Intra-individual comparison of standard dose and chest X-ray equivalent ultralow dose chest CT scans

PURPOSE To assess the performance of semi-automated volumetry of solid pulmonary nodules on single-energy tin-filtered ultralow dose (ULD) chest CT scans at a radiation dose equivalent to chest X-ray relative to standard dose (SD) chest CT scans and assess the impact of kernel and iterative reconstruction selection. METHODS Ninety-four consecutive patients from a prospective single-center study were included and underwent clinically indicated SD chest CT (1.9 ± 0.8 mSv) and additional ULD chest CT (0.13 ± 0.01 mSv) in the same session. All scans were reconstructed with a soft tissue (Br40) and lung (Bl64) kernel as well as with Filtered Back Projection (FBP) and Iterative Reconstruction (ADMIRE-3 and ADMIRE-5). One hundred and forty-eight solid pulmonary nodules were identified and analysed by semi-automated volumetry on all reconstructions. Nodule volumes were compared amongst all reconstructions thereby focusing on the agreement between SD and ULD scans. RESULTS Nodule volumes ranged from 58.5 (28.8-126) mm$^{3}$ for ADMIRE-5 Br40 ULD reconstructions to 72.5 (39-134) mm$^{3}$ for FBP Bl64 SD reconstructions with significant differences between reconstructions (p < 0.001). Interscan agreement of volumes between two given reconstructions ranged from ICC = 0.605 to ICC = 0.999. Between SD and ULD scans, agreement of nodule volumes was highest for FBP Br40 (ICC = 0.995), FBP Bl64 (ICC = 0.939) and ADMIRE-5 Bl64 (ICC = 0.994) reconstructions. ADMIRE-3 reconstructions exhibited reduced interscan agreement of nodule volumes (ICCs from 0.788 - 0.882). CONCLUSIONS The interscan agreement of node volumes between SD and ULD is high depending on the choice of kernel and reconstruction algorithm. However, caution should be exercised when comparing two image series that were not identically reconstructed

Impact of photon-counting-detector-CT derived virtual-monoenergetic-images and iodine-maps on the diagnosis of pleural empyema

PURPOSE The purpose of this study was to evaluate the impact of virtual monoenergetic image (VMI) energies and iodine maps on the diagnosis of pleural-empyema with photon-counting-detector computed-tomography (PCD-CT). MATERIALS AND METHODS In this IRB-approved retrospective study, consecutive patients with non-infectious pleural effusion or histopathology-proven empyema were included. PCD-CT examinations were performed on a dual-source PCD-CT in the multi-energy (QuantumPlus) mode at 120 kV with weight-adjusted intravenous contrast-agent. VMIs from 40-70 keV obtained in 10 keV intervals and an iodine map was reconstructed for each scan. CT-attenuation was measured in the aorta, the pleura and the peripleural fat (between autochthonous dorsal muscles and dorsal ribs). Contrast-to-noise (CNR) and signal-to-noise (SNR) ratios were calculated. Two blinded radiologists evaluated if empyema was present (yes/no), and rated diagnostic confidence (1 to 4; not confident to fully confident, respectively) with and without using the iodine map. Sensitivity, specificity and diagnostic confidence were estimated. Interobserver agreement was estimated using an unweighted Cohen kappa test. A one-way ANOVA was used to compare variables. Differences in sensitivity and specificity between the different levels of energy were searched using McNemar test. To compare AUC values DeLong test was performed. McNemar test was performed to compare values for sensitivity and specificity. RESULTS Sixty patients (median age, 60 years; 26 women) were included. A strong negative correlation was found between image noise and VMI energies (r = -0.98; P = 0.001) and CNR increased with lower VMI energies (r = -0.98; P = 0.002). Diagnostic accuracy (96%; 95% CI: 82-100) as well as diagnostic confidence (3.4 ± 0.75 [SD]) were highest at 40 keV. Diagnostic accuracy and confidence at higher VMI energies improved with the addition of iodine maps (P ≤0.001). Overall, no difference in CT attenuation of peripleural fat between patients with empyema and those with pleural effusion was found (P = 0.07). CONCLUSION Low VMI energies lead to a higher diagnostic accuracy and diagnostic confidence in the diagnosis of pleural empyema. Iodine maps help in diagnosing empyema only at high VMI energies

Impact of radiation dose on the detection of interstitial lung changes and image quality in low-dose chest CT - Assessment in multiple dose levels from a single patient scan

PURPOSE To assess image quality and detectability of interstitial lung changes using multiple radiation doses from the same chest CT scan of patients with suspected interstitial lung disease (ILD). METHOD Retrospective study of consecutive adult patients with suspected ILD receiving unenhanced chest CT as single-energy dual-source acquisition at 100 kVp (Dual-split mode). 67% and 33% of the overall tube current time product were assigned to tube A and B, respectively. 100%-dose was 2.34 ± 0.97 mGy. Five different radiation doses (100%, 67%, 45%, 39%, 33%) were reconstructed from this single acquisition using linear-blending technique. Two blinded radiologists assessed reticulations, ground-glass opacities (GGO) and honeycombing as well as subjective image noise. Percentage agreement (PA) as compared to 100%-dose were calculated. Non-parametric statistical tests were used. RESULTS A total of 228 patients were included (61.2 ± 14.6 years,146 female). PA was highest for honeycombing (>96%) and independent of dose reduction (P > 0.8). PA for reticulations and GGO decreased when reducing the radiation dose from 100% to 67% for both readers (reticulations: 83.3% and 93.9%; GGO: 87.7% and 79.8% for reader 1 and 2, respectively). Additional dose reduction did not significantly change PA for both readers (all P > 0.05). Subjective image noise increased with decreasing radiation dose (Spearman Rho of ρ = 0.34 and ρ = 0.53 for reader 1 and 2, respectively, P < 0.001). CONCLUSIONS Radiation dose reduction had a stronger impact on subtle interstitial lung changes. Detectability decreased with initial dose reduction indicating that a minimum dose is needed to maintain diagnostic accuracy in chest CT for suspected ILD

Sex and age dependencies of aqueductal cerebrospinal fluid dynamics parameters in healthy subjects

Objectives: To assess the influence of age and sex on 10 cerebrospinal fluid (CSF) flow dynamics parameters measured with an MR phase contrast (PC) sequence within the cerebral aqueduct at the level of the intercollicular sulcus.Materials and Methods: 128 healthy subjects (66 female subjects with a mean age of 52.9 years and 62 male subjects with a mean age of 51.8 years) with a normal Evans index, normal medial temporal atrophy (MTA) score, and without known disorders of the CSF circulation were included in the study. A PC MR sequence on a 3T MR scanner was used. Ten different flow parameters were analyzed using postprocessing software. Ordinal and linear regression models were calculated.Results: The parameters stroke volume (sex: p < 0.001, age: p = 0.003), forward flow volume (sex: p < 0.001, age: p = 0.002), backward flow volume (sex: p < 0.001, age: p = 0.018), absolute stroke volume (sex: p < 0.001, age: p = 0.005), mean flux (sex: p < 0.001, age: p = 0.001), peak velocity (sex: p = 0.009, age: p = 0.0016), and peak pressure gradient (sex: p = 0.029, age: p = 0.028) are significantly influenced by sex and age. The parameters regurgitant fraction, stroke distance, and mean velocity are not significantly influenced by sex and age.Conclusion: CSF flow dynamics parameters measured in the cerebral aqueduct are partly age and sex dependent. For establishment of reliable reference values for clinical use in future studies, the impact of sex and age should be considered and incorporated

Prediction of treatment response to transarterial radioembolization of liver metastases: Radiomics analysis of pre-treatment cone-beam CT: A proof of concept study

Purpose To investigate the potential of texture analysis and machine learning to predict treatment response to transarterial radioembolization (TARE) on pre-interventional cone-beam computed tomography (CBCT) images in patients with liver metastases. Materials and Methods In this IRB-approved retrospective single-center study 36 patients with a total of 104 liver metastases (56 % male, mean age 61.1 ± 13 years) underwent CBCT prior to TARE and follow-up imaging 6 months after therapy. Treatment response was evaluated according to RECIST version 1.1 and dichotomized into disease control (partial response/stable disease) versus disease progression (progressive disease). After target lesion segmentation, 104 radiomics features corresponding to seven different feature classes were extracted with the pyRadiomics package. After dimension reduction machine learning classifications were performed on a custom artificial neural network (ANN). Ten-fold cross validation on a previously unseen test data set was performed. Results The average administered cumulative activity from TARE was 1.6 Gbq (± 0.5 Gbq). At a mean follow-up of 5.9 ± 0.8 months disease control was achieved in 82 % of metastases. After dimension reduction, 15 of 104 (15 %) texture analysis features remained for further analysis. On a previously unseen set of liver metastases the Multilayer Perceptron ANN yielded a sensitivity of 94.2 %, specificity of 67.7 % and an area-under-the receiver operating characteristics curve of 0.85. Conclusion Our study indicates that texture analysis-based machine learning may has potential to predict treatment response to TARE using pre-treatment CBCT images of patients with liver metastases with high accuracy

Humor in radiological breast cancer screening: a way of improving patient service?

BACKGROUND Breast cancer screening is essential in detecting breast tumors, however, the examination is stressful. In this study we analyzed whether humor enhances patient satisfaction. METHODS In this prospective randomized study 226 patients undergoing routine breast cancer screening at a single center during October 2020 to July 2021 were included. One hundred thirty-two were eligible for the study. Group 1 (66 patients) received an examination with humorous intervention, group 2 (66 patients) had a standard breast examination. In the humor group, the regular business card was replaced by a self-painted, humorous business card, which was handed to the patient at the beginning of the examination. Afterwards, patients were interviewed with a standardized questionnaire. Scores between the two study groups were compared with the Mann-Whitney U test or Fisher's exact test. P-values were adjusted with the Holm's method. Two-sided p-values < 0.05 were considered significant. RESULTS One hundred thirty-two patients, 131 female and 1 male, (mean age 59 ± 10.6 years) remained in the final study cohort. Patients in the humor group remembered the radiologist's name better (85%/30%, P < .001), appreciated the final discussion with the radiologist more (4.67 ± 0.73-5;[5, 5] vs. 4.24 ± 1.1-5;[4, 5], P = .017), felt the radiologist was more empathetic (4.94 ± 0.24-5;[5, 5] vs.4.59 ± 0.64-5;[4, 5], P < .001), and rated him as a humorous doctor (4.91 ± 0.29-5;[5, 5] vs. 2.26 ± 1.43-1;[1, 4], P < .001). Additionally, patients in the humor group tended to experience less anxiety (p = 0.166) and felt the doctor was more competent (p = 0.094). CONCLUSION Humor during routine breast examinations may improve patient-radiologist relationship because the radiologist is considered more empathetic and competent, patients recall the radiologist's name more easily, and value the final discussion more. TRIAL REGISTRATION We have a general approval from our ethics committee because it is a retrospective survey, the patient lists for the doctors were anonymized and it is a qualitative study, since the clinical processes are part of the daily routine examinations and are used independently of the study. The patients have given their consent to this study and survey

Opportunistic deep learning powered calcium scoring in oncologic patients with very high coronary artery calcium (≥ 1000) undergoing 18F-FDG PET/CT

Our aim was to identify and quantify high coronary artery calcium (CAC) with deep learning (DL)-powered CAC scoring (CACS) in oncological patients with known very high CAC (≥ 1000) undergoing 18F-FDG-PET/CT for re-/staging. 100 patients were enrolled: 50 patients with Agatston scores ≥ 1000 (high CACS group), 50 patients with Agatston scores < 1000 (negative control group). All patients underwent oncological 18F-FDG-PET/CT and cardiac SPECT myocardial perfusion imaging (MPI) by 99mTc-tetrofosmin within 6 months. CACS was manually performed on dedicated non-contrast ECG-gated CT scans obtained from SPECT-MPI (reference standard). Additionally, CACS was performed fully automatically with a user-independent DL-CACS tool on non-contrast, free-breathing, non-gated CT scans from 18F-FDG-PET/CT examinations. Image quality and noise of CT scans was assessed. Agatston scores obtained by manual CACS and DL tool were compared. The high CACS group had Agatston scores of 2200 ± 1620 (reference standard) and 1300 ± 1011 (DL tool, average underestimation of 38.6 ± 26%) with an intraclass correlation of 0.714 (95% CI 0.546, 0.827). Sufficient image quality significantly improved the DL tool's capability of correctly assigning Agatston scores ≥ 1000 (p = 0.01). In the control group, the DL tool correctly assigned Agatston scores < 1000 in all cases. In conclusion, DL-based CACS performed on non-contrast free-breathing, non-gated CT scans from 18F-FDG-PET/CT examinations of patients with known very high (≥ 1000) CAC underestimates CAC load, but correctly assigns an Agatston scores ≥ 1000 in over 70% of cases, provided sufficient CT image quality. Subgroup analyses of the control group showed that the DL tool does not generate false-positives

Dual-energy CT kidney stone characterization-can diagnostic accuracy be achieved at low radiation dose?

OBJECTIVES To assess the accuracy of low-dose dual-energy computed tomography (DECT) to differentiate uric acid from non-uric acid kidney stones in two generations of dual-source DECT with stone composition analysis as the reference standard. METHODS Patients who received a low-dose unenhanced DECT for the detection or follow-up of urolithiasis and stone extraction with stone composition analysis between January 2020 and January 2022 were retrospectively included. Collected stones were characterized using X-ray diffraction. Size, volume, CT attenuation, and stone characterization were assessed using DECT post-processing software. Characterization as uric acid or non-uric acid stones was compared to stone composition analysis as the reference standard. Sensitivity, specificity, and accuracy of stone classification were computed. Dose length product (DLP) and effective dose served as radiation dose estimates. RESULTS A total of 227 stones in 203 patients were analyzed. Stone composition analysis identified 15 uric acid and 212 non-uric acid stones. Mean size and volume were 4.7 mm × 2.8 mm and 114 mm$^{3}$, respectively. CT attenuation of uric acid stones was significantly lower as compared to non-uric acid stones (p < 0.001). Two hundred twenty-five of 227 kidney stones were correctly classified by DECT. Pooled sensitivity, specificity, and accuracy were 1.0 (95%CI: 0.97, 1.00), 0.93 (95%CI: 0.68, 1.00), and 0.99 (95%CI: 0.97, 1.00), respectively. Eighty-two of 84 stones with a diameter of  ≤ 3 mm were correctly classified. Mean DLP was 162 ± 57 mGy*cm and effective dose was 2.43 ± 0.86 mSv. CONCLUSIONS Low-dose dual-source DECT demonstrated high accuracy to discriminate uric acid from non-uric acid stones even at small stone sizes. KEY POINTS • Two hundred twenty-five of 227 stones were correctly classified as uric acid vs. non-uric acid stones by low-dose dual-energy CT with stone composition analysis as the reference standard. • Pooled sensitivity, specificity, and accuracy for stone characterization were 1.0, 0.93, and 0.99, respectively. • Low-dose dual-energy CT for stone characterization was feasible in the majority of small stones  < 3 mm