Advances in spatial resolution and radiation dose reduction using super-resolution deep learning-based reconstruction for abdominal computed tomography: A phantom study.

RATIONALE AND OBJECTIVES: This study evaluated the performance of super-resolution deep learning-based reconstruction (SR-DLR) and compared with it that of hybrid iterative reconstruction (HIR) and normal-resolution DLR (NR-DLR) for enhancing image quality in computed tomography (CT) images across various field of view (FOV) sizes, radiation doses, and noise reduction strengths. MATERIALS AND METHODS: A Catphan phantom equipped with an external body ring was used. CT images were reconstructed using filtered back-projection (FBP), HIR, NR-DLR, and SR-DLR across three noise reduction strengths: mild, standard, and strong. The noise power spectrum (NPS) was obtained from the FBP, HIR, NR-DLR, and SR-DLR images at various FOVs, radiation doses, and noise reduction strengths. The noise magnitude ratio (NMR) and central frequency ratio (CFR) were calculated from the HIR, NR-DLR, and SR-DLR images relative to the FBP images using NPS. The high-contrast value was obtained from the amplitude values of the peaks and valleys of profile curve and the task-based transfer function were also analyzed. RESULTS: SR-DLR consistently demonstrated superior noise reduction capabilities, with NMR of 0.29-0.36 at reduced dose and 0.35-0.45 at standard dose, outperforming HIR and showing comparable efficiency to NR-DLR. The high-contrast values for SR-DLR were highest at mild and standard levels for both low and standard doses (0.610 and 0.726 at mild and 0.725 and 0.603 at standard levels). At the standard dose, the spatial resolution of SR-DLR was significantly improved, regardless of the noise reduction strength and FOV. CONCLUSION: SR-DLR images achieved more substantial noise reduction than HIR and similar noise reduction as NR-DLR reconstructions while also improving spatial resolution.

Non-contrast spectral CT vs chemical-shift MRI in discriminating lipid-poor adrenal lesions.

OBJECTIVES: To compare the diagnostic performance of conventional non-contrast CT, dual-energy spectral CT, and chemical-shift MRI (CS-MRI) in discriminating lipid-poor adenomas (> 10-HU on non-contrast CT) from non-adenomas. METHODS: A total of 110 patients (69 men; 41 women; mean age 66.5 ± 13.4 years) with 80 lipid-poor adenomas and 30 non-adenomas who underwent non-contrast dual-layer spectral CT and CS-MRI were retrospectively identified. For each lesion, non-contrast attenuation on conventional 120-kVp images, ΔHU-index ([attenuation difference between virtual monoenergetic 140-keV and 40-keV images]/conventional attenuation × 100), and signal intensity index (SI-index) were quantified. Each parameter was compared between adenomas and non-adenomas using the Mann-Whitney U-test. The area under the receiver operating characteristic curve (AUC) and sensitivity to achieve > 95% specificity for adenoma diagnosis were determined. RESULTS: Conventional non-contrast attenuation was lower in adenomas than in non-adenomas (22.4 ± 8.6 HU vs 32.8 ± 48.5 HU), whereas ΔHU-index (148.0 ± 103.2 vs 19.4 ± 25.8) and SI-index (41.6 ± 19.6 vs 4.2 ± 10.2) were higher in adenomas (all, p < 0.001). ΔHU-index showed superior performance to conventional non-contrast attenuation (AUC: 0.919 [95% CI: 0.852-0.963] vs 0.791 [95% CI: 0.703-0.863]; sensitivity: 75.0% [60/80] vs 27.5% [22/80], both p < 0.001), and near equivalent to SI-index (AUC: 0.952 [95% CI: 0.894-0.984], sensitivity 85.0% [68/80], both p > 0.05). Both the ΔHU-index and SI-index provided a sensitivity of 96.0% (48/50) for hypoattenuating adenomas (≤ 25 HU). For hyperattenuating (> 25 HU) adenomas, SI-index showed higher sensitivity than ΔHU-index (66.7% [20/30] vs 40.0% [12/30], p = 0.022). CONCLUSIONS: Non-contrast spectral CT and CS-MRI outperformed conventional non-contrast CT in distinguishing lipid-poor adenomas from non-adenomas. While CS-MRI demonstrated superior sensitivity for adenomas measuring > 25 HU, non-contrast spectral CT provided high discriminative values for adenomas measuring ≤ 25 HU. CLINICAL RELEVANCE STATEMENT: Spectral attenuation analysis improves the diagnostic performance of non-contrast CT in discriminating lipid-poor adrenal adenomas, potentially serving as an alternative to CS-MRI and obviating the necessity for additional diagnostic workup in indeterminate adrenal incidentalomas, particularly for lesions measuring ≤ 25 HU. KEY POINTS: Incidental adrenal lesion detection has increased as abdominal CT use has become more frequent. Non-contrast spectral CT and CS-MRI differentiated lipid-poor adenomas from non-adenomas better than conventional non-contrast CT. For lesions measuring ≤ 25 HU, spectral CT may obviate the need for additional evaluation.

Super-resolution deep-learning reconstruction for cardiac CT: impact of radiation dose and focal spot size on task-based image quality.

This study aimed to evaluate the impact of radiation dose and focal spot size on the image quality of super-resolution deep-learning reconstruction (SR-DLR) in comparison with iterative reconstruction (IR) and normal-resolution DLR (NR-DLR) algorithms for cardiac CT. Catphan-700 phantom was scanned on a 320-row scanner at six radiation doses (small and large focal spots at 1.4-4.3 and 5.8-8.8 mGy, respectively). Images were reconstructed using hybrid-IR, model-based-IR, NR-DLR, and SR-DLR algorithms. Noise properties were evaluated through plotting noise power spectrum (NPS). Spatial resolution was quantified with task-based transfer function (TTF); Polystyrene, Delrin, and Bone-50% inserts were used for low-, intermediate, and high-contrast spatial resolution. The detectability index (d') was calculated. Image noise, noise texture, edge sharpness of low- and intermediate-contrast objects, delineation of fine high-contrast objects, and overall quality of four reconstructions were visually ranked. Results indicated that among four reconstructions, SR-DLR yielded the lowest noise magnitude and NPS peak, as well as the highest average NPS frequency, TTF50%, d' values, and visual rank at each radiation dose. For all reconstructions, the intermediate- to high-contrast spatial resolution was maximized at 4.3 mGy, while the lowest noise magnitude and highest d' were attained at 8.8 mGy. SR-DLR at 4.3 mGy exhibited superior noise performance, intermediate- to high-contrast spatial resolution, d' values, and visual rank compared to the other reconstructions at 8.8 mGy. Therefore, SR-DLR may yield superior diagnostic image quality and facilitate radiation dose reduction compared to the other reconstructions, particularly when combined with small focal spot scanning.

Clinical characteristics of patients with high extracellular volume fraction evaluated by cardiac computed tomography for coronary artery evaluation.

Aims: This study aims to evaluate the distribution of extracellular volume fraction detected via computed tomography, clinical characteristics of high extracellular volume fraction detected via computed tomography, and the rate of incidental detection of cardiac amyloidosis in patients undergoing cardiac computed tomography for coronary artery evaluation. Methods and results: This study included 874 consecutive patients (mean age, 74.4 ± 7.1 years; men, 65%), comprising men aged ≥60 years and women aged ≥70 years, who had undergone cardiac computed tomography between January 2020 and September 2022. The mean extracellular volume fraction detected via computed tomography was 29.7 ± 5.2%, and 108 patients (12.4%) had an extracellular volume fraction detected via computed tomography of ≥35%. Older age (75.9 ± 8.2 years vs. 74.2 ± 6.9 years; P = 0.042), male sex (75.9% vs. 63.0%; P = 0.007), impaired left ventricular ejection fraction, increased high-sensitivity cardiac troponin T and B-type natriuretic peptide levels, and increased left ventricular thickness showed significant associations with an extracellular volume fraction detected via computed tomography of ≥35%. Cardiac amyloidosis was diagnosed incidentally in 15 patients based on an increase in extracellular volume fraction detected via computed tomography. The prevalence of cardiac amyloidosis was 1.7% (15/874) and 14.3% (15/105) in the entire study population and in patients with an extracellular volume fraction detected via computed tomography of ≥35%, respectively. An increase in the extracellular volume fraction detected via computed tomography was suggestive of cardiac amyloidosis. Conclusion: Elevated extracellular volume fraction detected via computed tomography, associated with elevated cardiac biomarker levels and myocardial structural changes, may lead to the incidental diagnosis of cardiac amyloidosis.

Diagnostic performance of hepatic CT and chemical-shift MRI to discriminate lipid-poor adrenal adenomas from hepatocellular carcinoma metastases.

PURPOSE: To evaluate the diagnostic performance of multiphase hepatic CT parameters (non-contrast attenuation, absolute and relative washout ratios [APW and RPW, respectively], and relative enhancement ratio [RER]) and chemical-shift MRI (CS-MRI) for discriminating lipid-poor adrenal adenomas (with non-contrast CT attenuation > 10 HU) from metastases in patients with hepatocellular carcinoma (HCC). METHODS: This retrospective study included HCC patients with lipid-poor adrenal lesions who underwent multiphase hepatic CT between January 2010 and December 2021. For each adrenal lesion, non-contrast attenuation, APW, RPW, RER, and signal-intensity index (SI-index) were measured. Each parameter was compared between adenomas and metastases. The area under the receiver operating characteristic curves (AUCs) and sensitivities to achieve 100% specificity for adenoma diagnoses were determined. RESULTS: 104 HCC patients (78 men; mean age, 71.8 ± 9.6 years) with 63 adenomas and 48 metastases were identified; CS-MRI was performed in 66 patients with 49 adenomas and 21 metastases within one year of CT. Lipid-poor adenomas showed lower non-contrast attenuation (22.9 ± 7.1 vs. 37.9 ± 9.4 HU) and higher APW (40.5% ± 12.8% vs. 23.7% ± 17.4%), RPW (30.0% ± 10.2% vs. 12.4% ± 9.6%), RER (329% ± 152% vs. 111% ± 43.0%), and SI-index (43.3 ± 20.7 vs. 10.8 ± 13.4) than HCC metastases (all p < .001). AUC for non-contrast attenuation, APW, RPW, RER, and SI-index were 0.894, 0.786, 0.904, 0.969, and 0.902, respectively. The sensitivities to achieve 100% specificity were 7.9%, 25.4%, 30.2%, 63.5%, and 24.5%, respectively. Combined RER and APW achieved the highest sensitivity of 73.0%. CONCLUSION: Multiphase hepatic CT allows for better discrimination between lipid-poor adrenal adenomas and metastases relative to CS-MRI, especially when combined with RER and washout parameters.

Cardiac MRI T1 and T2 Mapping as a Quantitative Imaging Biomarker in Transthyretin Amyloid Cardiomyopathy.

RATIONALE AND OBJECTIVES: This study aimed to assess the utility of cardiac magnetic resonance imaging (MRI) T1 and T2 mapping as quantitative imaging biomarkers in transthyretin amyloid cardiomyopathy (ATTR-CM). MATERIALS AND METHODS: This study retrospectively evaluated 74 patients with confirmed wild-type ATTR-CM who underwent cardiac MRI, 99mTc-labeled pyrophosphate (99mTc-PYP) scintigraphy, and echocardiography. We assessed the quantitative disease parameters, for example, left ventricular ejection fraction (LVEF), and global longitudinal strain (GLS) by echocardiography, native T1, extracellular volume fraction (ECV), and native T2 value by cardiac MRI, heart-to-contralateral ratio (H/CL) by 99mTc-PYP, and high-sensitive cardiac troponin T. Myocardial native T2 of ≥50 ms was defined as myocardial edema. Correlations between the disease's quantitative parameters were evaluated, and the ECV was compared to other parameters in ATTR-CM with/without myocardial edema. RESULTS: ECV in all patients with ATTR-CM revealed a strong correlation with native T1 (r = 0.62), a moderate correlation with hs-TnT (r = 0.59), LVEF (r = -0.48), GLS (r = 0.58), and H/CL (r = 0.48). Correlations between ECV and other quantitative parameters decreased in ATTR-CM with myocardial edema except for H/CL. Meanwhile, the correlations increased in ATTR-CM without myocardial edema. CONCLUSION: The presence of myocardial edema affected the interpretation of ECV assessment, although ECV can be a comprehensive imaging biomarker for ATTR-CM. ECV showed a significant correlation with various quantitative disease parameters and can be a reliable disease monitoring marker in patients with ATTR-CM when myocardial edema was excluded.

Myocardial extracellular volume quantification in cardiac amyloidosis: a comparative study between cardiac computed tomography and magnetic resonance imaging.

OBJECTIVES: Myocardial extracellular volume (ECV) on computed tomography (CT), an alternative to cardiac magnetic resonance (CMR), has significant practical clinical advantages. However, the consistency between ECVs quantified via CT and CMR in cardiac amyloidosis (CA) has not been investigated sufficiently. Therefore, the current study investigated the application of CT-ECV in CA with CMR-ECV as the reference standard. METHODS: We retrospectively evaluated 31 patients with CA who underwent cardiac CT and CMR. Pearson correlation analysis was performed to investigate correlations between CT-ECV and CMR-ECV at each segment. Further, correlations between ECV and clinical parameters were assessed. RESULTS: There were no significant differences in the mean global ECVs between CT scan and CMR (51.3% ± 10.2% vs 50.0% ± 10.5%). CT-ECV was correlated with CMR-ECV at the septal (r = 0.88), lateral (r = 0.80), inferior (r = 0.79), anterior (r = 0.77) segments, and global (r = 0.87). In both CT and CMR, the ECV had a weak to strong correlation with high-sensitivity cardiac troponin T level, a moderate correlation with global longitudinal strain, and an inverse correlation with left ventricular ejection fraction. Further, the septal ECV and global ECV had a slightly higher correlation with the clinical parameters. CONCLUSIONS: Cardiac CT can quantify myocardial ECV and yield results comparable to CMR in patients with CA. Moreover, a significant correlation between CT-ECV and clinical parameters was observed. Thus, CT-ECV can be an imaging biomarker and alternative to CMR-ECV. CLINICAL RELEVANCE STATEMENT: Cardiac CT can quantify myocardial ECV and yield results comparable to CMR in patients with CA, and CT-ECV can be used clinically as an imaging biomarker and alternative to CMR-ECV. KEY POINTS: • A significant correlation was found between CT myocardial extracellular volume and cardiac MR myocardial extracellular volume in patients with cardiac amyloidosis. • In CT and cardiac MR, the myocardial extracellular volume correlated well with high-sensitivity cardiac troponin T level, global longitudinal strain, and left ventricular ejection fraction. • CT myocardial extracellular volume can be an imaging biomarker and alternative to cardiac MR myocardial extracellular volume.

Cardiac MRI-derived Extracellular Volume Fraction versus Myocardium-to-Lumen R1 Ratio at Postcontrast T1 Mapping for Detecting Cardiac Amyloidosis.

Purpose: To evaluate the diagnostic performance of myocardium-to-lumen R1 (1/T1) ratio on postcontrast T1 maps for the detection of cardiac amyloidosis in a large patient sample. Materials and Methods: This retrospective study included consecutive patients who underwent MRI-derived extracellular volume fraction (MRI ECV) analysis between March 2017 and July 2021 because of known or suspected heart failure or cardiomyopathy. Pre- and postcontrast T1 maps were generated using the modified Look-Locker inversion recovery sequence. Diagnostic performances of MRI ECV and myocardium-to-lumen R1 ratio on postcontrast T1 maps (a simplified index not requiring a native T1 map and hematocrit level data) for detecting cardiac amyloidosis were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results: Of 352 patients (mean age, 63 years ± 16 [SD]; 235 men), 136 had cardiac amyloidosis. MRI ECV showed 89.0% (121 of 136; 95% CI: 82%, 94%) sensitivity and 98.6% (213 of 216; 95% CI: 96%, 100%) specificity for helping detect cardiac amyloidosis (cutoff value of 40% [AUC, 0.99 {95% CI: 0.97, 1.00}; P < .001]). Postcontrast myocardium-to-lumen R1 ratio showed 92.6% (126 of 136; 95% CI: 89%, 96%) sensitivity and 93.1% (201 of 216; 95% CI: 89%, 96%) specificity (cutoff value of 0.84 [AUC, 0.98 {95% CI: 0.95, 0.99}; P < .001]). There was no evidence of a difference in AUCs for each parameter (P = .10). Conclusion: Postcontrast myocardium-to-lumen R1 ratio showed excellent diagnostic performance comparable to that of MRI ECV in the detection of cardiac amyloidosis.Keywords: MR Imaging, Cardiac, Heart, Cardiomyopathies Supplemental material is available for this article. © RSNA, 2023.

Clinical characteristics, outcome, and therapeutic effect of tafamidis in wild-type transthyretin amyloid cardiomyopathy.

AIMS: Tafamidis improves prognosis in patients with transthyretin amyloid cardiomyopathy (ATTR-CM). However, real-world data on the therapeutic effect of tafamidis are lacking. This study aimed to evaluate the clinical course, outcomes, and effectivity monitoring of the therapeutic effect of tafamidis in patients with ATTR-CM. METHODS AND RESULTS: This is a single-centre, retrospective observational study. We evaluated the clinical characteristics and outcomes in 125 consecutive patients with wild-type ATTR-CM (ATTRwt-CM) treated with tafamidis (treatment group) and 55 untreated patients (treatment-naïve group). We monitored the therapeutic effect of tafamidis for 12 months by evaluating serial cardiac biomarker and imaging findings. The treatment group had significantly more favourable outcome in all-cause mortality and hospitalization due to heart failure than the treatment-naïve group in both the entire cohort (P < 0.01) and the propensity score-matched cohort (P < 0.05). Kaplan-Meier survival curves showed that tafamidis treatment significantly reduced all-cause mortality (P = 0.03, log-rank test), with the curves diverging after approximately 18 months of treatment in the propensity score-matched cohort. On inverse probability of treatment weighting analysis, tafamidis treatment showed a reduced all-cause mortality [hazard ratio (HR), 0.31; 95% confidence interval (CI), 0.11-0.93; P = 0.04]. High-sensitivity cardiac troponin T (hs-cTnT) > 0.05 ng/mL, B-type natriuretic peptide (BNP) > 250 pg/mL, and estimated glomerular filtration rate (eGFR) < 45 mL/min/1.73 m2 scored 1 point each. Multivariate logistic regression analysis revealed that a high score (2-3 points) was a significantly poor prognostic factor of composite clinical outcomes, including all-cause death and hospitalization for heart failure (HR, 1.55; 95% CI, 1.22-1.98; P < 0.01) for patients in the treatment group. After 12 months of tafamidis treatment, hs-cTnT levels decreased significantly [0.054 (0.036-0.082) vs. 0.044 (0.033-0.076); P = 0.002], with no significant changes in BNP levels, echocardiographic parameters, native T1 value, and extracellular volume fraction on cardiac magnetic resonance imaging. CONCLUSIONS: The prognosis of patients with ATTRwt-CM treated with tafamidis was more favourable than that of untreated patients. Patient stratification combined with biomarkers (hs-cTnT, BNP, and eGFR) predicted clinical outcomes. hs-cTnT may be a useful biomarker for evaluating the therapeutic effect of tafamidis.

Deep learning-based reconstruction can improve the image quality of low radiation dose head CT.

OBJECTIVES: To evaluate the image quality of deep learning-based reconstruction (DLR), model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose (LD) unenhanced head CT and compare it with those of standard-dose (STD) HIR images. METHODS: This retrospective study included 114 patients who underwent unenhanced head CT using the STD (n = 57) or LD (n = 57) protocol on a 320-row CT. STD images were reconstructed with HIR; LD images were reconstructed with HIR (LD-HIR), MBIR (LD-MBIR), and DLR (LD-DLR). The image noise, gray and white matter (GM-WM) contrast, and contrast-to-noise ratio (CNR) at the basal ganglia and posterior fossa levels were quantified. The noise magnitude, noise texture, GM-WM contrast, image sharpness, streak artifact, and subjective acceptability were independently scored by three radiologists (1 = worst, 5 = best). The lesion conspicuity of LD-HIR, LD-MBIR, and LD-DLR was ranked through side-by-side assessments (1 = worst, 3 = best). Reconstruction times of three algorithms were measured. RESULTS: The effective dose of LD was 25% lower than that of STD. Lower image noise, higher GM-WM contrast, and higher CNR were observed in LD-DLR and LD-MBIR than those in STD (all, p ≤ 0.035). Compared with STD, the noise texture, image sharpness, and subjective acceptability were inferior for LD-MBIR and superior for LD-DLR (all, p < 0.001). The lesion conspicuity of LD-DLR (2.9 ± 0.2) was higher than that of HIR (1.2 ± 0.3) and MBIR (1.8 ± 0.4) (all, p < 0.001). Reconstruction times of HIR, MBIR, and DLR were 11 ± 1, 319 ± 17, and 24 ± 1 s, respectively. CONCLUSION: DLR can enhance the image quality of head CT while preserving low radiation dose level and short reconstruction time. KEY POINTS: • For unenhanced head CT, DLR reduced the image noise and improved the GM-WM contrast and lesion delineation without sacrificing the natural noise texture and image sharpness relative to HIR. • The subjective and objective image quality of DLR was better than that of HIR even at 25% reduced dose without considerably increasing the image reconstruction times (24 s vs. 11 s). • Despite the strong noise reduction and improved GM-WM contrast performance, MBIR degraded the noise texture, sharpness, and subjective acceptance with prolonged reconstruction times relative to HIR, potentially hampering its feasibility.

Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging.

The application of machine learning (ML) and deep learning (DL) in radiology has expanded exponentially. In recent years, an extremely large number of studies have reported about the hepatobiliary domain. Its applications range from differential diagnosis to the diagnosis of tumor invasion and prediction of treatment response and prognosis. Moreover, it has been utilized to improve the image quality of DL reconstruction. However, most clinicians are not familiar with ML and DL, and previous studies about these concepts are relatively challenging to understand. In this review article, we aimed to explain the concepts behind ML and DL and to summarize recent achievements in their use in the hepatobiliary region.

Performance of Machine Learning Methods Based on Multi-Sequence Textural Parameters Using Magnetic Resonance Imaging and Clinical Information to Differentiate Malignant and Benign Soft Tissue Tumors.

RATIONALE AND OBJECTIVES: To evaluate the performance of a machine learning method to differentiate malignant from benign soft tissue tumors based on textural features on multiparametric magnetic resonance imaging (mpMRI). MATERIALS AND METHODS: We enrolled 163 patients with soft tissue tumors whose diagnosis was pathologically proven (71 malignant, 92 benign). All patients underwent mpMRI. Twelve histographic and textural parameters were assessed on T1-weighted imaging (T1WI), T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient maps, and contrast-enhanced T1WI imaging. We compared mean signals of all sequences from the malignant and benign tumors using Welch's t-test. Prediction models were developed via a machine learning technique (support vector machine) using textural features of each sequence, clinical information (sex + age + tumor size), and the combined model incorporating all features. Areas under the receiver operating characteristic curves (AUCs) of these models were calculated using fivefold cross validation. RESULTS: The diagnostic ability of clinical information model (AUC 0.85) was not inferior to the model with textural features of each sequence (AUC 0.79-0.84). The combined model showed the highest diagnostic ability (AUC 0.89). The AUC of the combined model (0.89) was comparable to those of two board-certified radiologists (0.89 and 0.87). CONCLUSIONS: Machine learning methods based on textural features on mpMRI and clinical information offer adequate diagnostic performance to differentiate between malignant and benign soft tissue tumors.

CT Extracellular Volume Fraction versus Myocardium-to-Lumen Signal Ratio for Cardiac Amyloidosis.

Background Large studies on the diagnostic performance of CT-derived myocardial extracellular volume fraction (ECV) for detecting cardiac amyloidosis are lacking. A simple and practical index as a surrogate for CT ECV would be clinically useful. Purpose To compare the diagnostic performances between CT-derived myocardial ECV and myocardium-to-lumen signal ratio for the detection of cardiac amyloidosis in a large patient sample. Materials and Methods This retrospective study included patients who underwent CT ECV analysis because of suspected heart failure or cardiomyopathy between January 2018 and July 2021. CT ECV was quantified using routine pre-transcatheter aortic valve replacement planning cardiac CT, pre-atrial fibrillation ablation planning cardiac CT, or coronary CT angiography with the addition of unenhanced and delayed phase cardiac CT scans. The diagnostic performances of CT ECV and myocardium-to-lumen signal ratio in delayed phase cardiac CT (a simplified index not requiring unenhanced CT and hematocrit) for detecting cardiac amyloidosis were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results Of 552 patients (mean age, 69 years ± 14 [SD]; 295 men), 41 had cardiac amyloidosis. The sensitivity of CT ECV for amyloidosis was 90% (37 of 41 patients [95% CI: 77, 97]), with a specificity of 92% (472 of 511 patients [95% CI: 90, 95]) and optimal ECV cutoff value of 37% (AUC, 0.97 [95% CI: 0.96, 0.99]). The sensitivity of myocardium-to-lumen signal ratio was 88% (36 of 41 patients [95% CI: 74, 96]), with a specificity of 92% (469 of 511 patients [95% CI: 89, 94]) and optimal myocardium-to-lumen signal ratio cutoff value of 0.87 (AUC, 0.96 [95% CI: 0.94, 0.97]; P = .27 for comparison with ECV). Conclusion CT-derived myocardial extracellular volume fraction and myocardium-to-lumen signal ratio showed comparable and excellent diagnostic performance in detecting cardiac amyloidosis in a large patient sample. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Williams in this issue.

Assessing the treatment effect of daratumumab by serial measurements of cardiac biomarkers and imaging parameters in light-chain cardiac amyloidosis.

Daratumumab, an anti-human CD38 monoclonal antibody, has become the standard of care in patients with systemic light-chain (AL) amyloidosis and multiple myeloma (MM). Herein, we report two cases of AL cardiac amyloidosis with MM who were treated with daratumumab, lenalidomide, and dexamethasone (DRd). Serial evaluation of cardiac biomarkers, echocardiography, and cardiac magnetic resonance imaging (CMR) were performed during 12 months of DRd treatment. A complete hematologic response was achieved three months after treatment initiation and sustained during the observation period. Twelve months after DRd treatment, we found improvements in levels (values for case 1 and case 2, respectively) of B-type natriuretic peptide (593.2 → 312.2 pg/mL and 202.4 → 104.3 pg/mL), N-terminal pro-brain natriuretic peptide (4005 → 1800 pg/mL and 2576 → 1170 pg/mL), high-sensitivity cardiac troponin T (0.156 → 0.072 ng/mL and 0.0678 → 0.0467 ng/mL), and global longitudinal strain (-6.8 → -10.4 % and -11.8 → -14.8 %). CMR revealed no noticeable changes in native T1 value or extracellular volume fraction. However, one case showed decreased native T2 value (61 → 55 ms). In conclusion, DRd treatment improved heart failure and cardiac function, relieved myocardial damage, and prevented amyloid deposition progression in the patients with AL cardiac amyloidosis. Cardiac biomarkers and imaging findings may be useful for monitoring the therapeutic effects of daratumumab-containing regimens. Learning objective: Daratumumab-containing regimens led to a rapid complete hematologic response, improvements in heart failure symptoms, cardiac function, and regression of myocardial damage in light-chain cardiac amyloidosis. This treatment prevents additional amyloid deposition and suppresses the direct cardiotoxic effects of amyloidogenic immunoglobulin light-chains. Serial assessments of cardiac biomarkers and imaging findings are useful for evaluating the therapeutic effect of daratumumab-containing regimens.

Correlation Between Cardiac Images, Biomarkers, and Amyloid Load in Wild-Type Transthyretin Amyloid Cardiomyopathy.

Background Several imaging parameters and biomarkers provide diagnostic and prognostic information for wild-type transthyretin amyloid cardiomyopathy. However, the relevance of these parameters and their association with cardiac amyloid load requires further substantiation. We aimed to elucidate the association of imaging parameters obtained using 99mTc-labeled pyrophosphate scintigraphy, cardiovascular magnetic resonance imaging, global longitudinal strain (GLS), and cardiac biomarkers with cardiac amyloid load in patients with wild-type transthyretin amyloid cardiomyopathy. Methods and Results Eighty-eight patients with wild-type transthyretin amyloid cardiomyopathy who underwent 99mTc-labeled pyrophosphate scintigraphy and cardiovascular magnetic resonance were retrospectively evaluated. Quantitative cardiac amyloid load was obtained from 61 patients after myocardial biopsy. Correlations were assessed using Pearson's correlation coefficient applied to medical record data. The mean heart to contralateral ratio, native T1, extracellular volume, and GLS were 1.91±0.36, 1419.4±56.4 ms, 56.5±13.6%, and -9.4±2.5%, respectively. Median high-sensitivity cardiac troponin T (hs-cTnT) and BNP (B-type natriuretic peptide) levels were 0.0478 (0.0334-0.0691) ng/mL and 213.8 (125.8-392.7) pg/mL, respectively. The mean cardiac amyloid load was 22.9±15.0%. The heart to contralateral ratio correlated significantly with native T1 (r=0.397), extracellular volume (r=0.477), GLS (r=0.363), cardiac amyloid load (r=0.379), and Ln (hs-cTnT) (r=0.247). Further, cardiac amyloid load correlated significantly with native T1 (r=0.509), extracellular volume (r=0.310), GLS (r=0.446), and Ln (hs-cTnT) (r=0.354). Compared with BNP, hs-cTnT levels better correlated with several imaging parameters and cardiac amyloid load. Conclusions Increased cardiac amyloid load correlated with increased 99mTc-labeled pyrophosphate positivity, native T1, extracellular volume, and hs-cTnT levels, and an impaired GLS, suggesting that imaging parameters and cardiac biomarkers may reflect histological and functional changes attributable to amyloid deposition in the myocardium.

Extracardiac Biopsy Sensitivity in Transthyretin Amyloidosis Cardiomyopathy Patients With Positive 99 mTc-Labeled Pyrophosphate Scintigraphy Findings.

BACKGROUND: The accurate sensitivity of amyloid deposition in extracardiac tissue (subcutaneous tissue and gastrointestinal tract) has not been evaluated in transthyretin amyloidosis cardiomyopathy (ATTR-CM) patients. This study aimed to evaluate the sensitivity of amyloid deposition in obtained endomyocardial and extracardiac biopsies.Methods and Results: This study retrospectively evaluated 175 consecutive ATTR-CM patients (wild-type [ATTRwt]: 134, hereditary [ATTRv]: 41) who had positive findings on 99 mTc-labeled pyrophosphate (99 mTc-PYP) scintigraphy and underwent tissue biopsy of at least one organ (subcutaneous tissue, gastrointestinal tract, and endomyocardium). Amyloid deposition was observed in the subcutaneous tissue of 57/150 patients (38%), gastrointestinal tract of 80/131 patients (61%), and endomyocardium of 108/109 patients (99%). Compared to patients with ATTRv, ATTRwt had significantly lower sensitivity in subcutaneous tissue (73% vs. 25%, P<0.01) and tended to be lower in the gastrointestinal tract (74% vs. 57%, P=0.08) biopsies. Among 124 patients who underwent both subcutaneous tissue and gastrointestinal tract biopsies, amyloid was detected in at least 1 specimen in 91 (73%) patients. The sensitivity of the combination of extracardiac biopsies was 66% and 94% in ATTRwt-CM and ATTRv-CM, respectively. Multivariate analysis reveals that ATTRv was the only significant predictor of amyloid deposition in the subcutaneous tissue. CONCLUSIONS: Subcutaneous tissue and gastrointestinal tract biopsy sensitivity are inadequate, especially in patients with ATTRwt; however, the combination of these extracardiac biopsies contributes to increased sensitivity in patients with positive 99 mTc-PYP scintigraphy findings.

Radiation dose optimization potential of deep learning-based reconstruction for multiphase hepatic CT: A clinical and phantom study.

PURPOSE: This clinical and phantom study aimed to evaluate the impact of deep learning-based reconstruction (DLR) on image quality and its radiation dose optimization capability for multiphase hepatic CT relative to hybrid iterative reconstruction (HIR). METHODS: Task-based image quality was assessed with a physical evaluation phantom; the high- and low-contrast detectability of HIR and DLR images were computed from the noise power spectrum and task-based transfer function at five different size-specific dose estimate (SSDE) values in the range 5.3 to 18.0-mGy. For the clinical study, images of 73 patients who had undergone multiphase hepatic CT under both standard-dose (STD) and lower-dose (LD) examination protocols within a time interval of about four-months on average, were retrospectively examined. STD images were reconstructed with HIR, while LD with HIR (LD-HIR) and DLR (LD-DLR). SSDE, quantitative image noise, and contrast-to-noise ratio (CNR) were compared between protocols. The noise magnitude, noise texture, streak artifact, image sharpness, interface smoothness, and overall image quality were subjectively rated by two independent radiologists. RESULTS: In phantom study, the high- and low-contrast detectability of DLR images obtained at 5.3-mGy and 7.3-mGy, respectively, were slightly higher than those obtained with HIR at the STD protocol dose (18.0-mGy). In clinical study, LD-DLR yielded lower image noise, higher CNR, and higher subjective scores for all evaluation criteria than STD (all, p ≤ 0.05), despite having 52.8% lower SSDE (8.0 ± 2.5 vs. 16.8 ± 3.4-mGy). CONCLUSIONS: DLR improved the subjective and objective image quality of multiphase hepatic CT compared with HIR techniques, even at approximately half the radiation dose.

Cardiac computed tomography-derived myocardial tissue characterization after anthracycline treatment.

AIMS: Understanding cardiac function after anthracycline administration is very important from the perspective of preventing the onset of heart failure. Although cardiac magnetic resonance and echocardiography are recognized as the 'gold standard' for detecting cardiotoxicity, they have many shortcomings. We aimed to investigate whether cardiac computed tomography (CCT) could replace these techniques, assessing serial changes in cardiac tissue characteristics as determined by CCT after anthracycline administration. METHODS AND RESULTS: We prospectively investigated 15 consecutive breast cancer patients who were scheduled to receive anthracycline therapy. We performed echocardiography and CCT before and 3, 6, and 12 months after anthracycline treatment. The mean cumulative administered anthracycline dose was 269.9 ± 14.6 mg/m2 (doxorubicin-converted dose). Of the 15 enrolled patients who received anthracycline treatment for breast cancer, none met the definition of cardiotoxicity. The CCT-derived extracellular volume fraction tended to continue to increase after anthracycline treatment and had relatively similar dynamics to the left ventricular ejection fraction and global longitudinal strain as determined by echocardiography. CONCLUSIONS: Our findings indicated that CCT could provide adequate information about the characteristics of myocardial tissue after anthracycline administration. CCT may improve the understanding of cardiotoxicity by compensating for the weaknesses of echocardiography. This technique could be useful for understanding cardiac tissue characterization as a 'one-stop shop' evaluation, providing new insight into cardiooncology.

Comparison of the effects of varying tube voltage and iodinated concentration on increasing the iodinated radiation dose in computed tomography.

PURPOSE: To compare the effects of tube voltage and iodinated concentration on increasing the iodinated radiation dose in computed tomography (CT). MATERIAL AND METHODS: Water and iodinated materials were inserted in an anthropomorphic thorax phantom. Helical CT scans were performed with tube voltages of 80 and 120 kV. Monte Carlo simulation of radiation doses in CT images was used to study the radiation dose profiles. The radiation doses at different iodine to water ratios in images were calculated from cumulative radiation doses for iodine and water at each iodine concentration, tube voltage, and peripheral/central location. A radiation dose ratio from 80 to 120 kV was calculated from cumulative radiation doses at the same iodine concentration. RESULTS: The iodinated radiation doses with small and large phantoms were 1.56-2.04 and 1.61-1.82 times higher at 80 kV and 1.55-2.23 and 1.22-1.79 times higher at 120 kV than those in water. In the central portion, the iodinated radiation dose ratio decreased by 1.14-0.75 and 1.20-0.93 times at 80 kV and 1.29-1.23 and 1.17-1.23 times at 120 kV with increasing iodinated concentrations. In the peripheral portion, the iodinated radiation dose was slightly higher for 80 kV than for 120 kV. In the central portion, the ratio decreased with increasing iodinated concentration. CONCLUSION: The increase in iodinated radiation dose caused by photoelectric absorption was greater with increased iodine load than with lower tube voltage.