Coronary computed tomography angiographic detection of in-stent restenosis via deep learning reconstruction: a feasibility study.

OBJECTIVES: Evaluation of in-stent restenosis (ISR), especially for small stents, remains challenging during computed tomography (CT) angiography. We used deep learning reconstruction to quantify stent strut thickness and lumen vessel diameter at the stent and compared it with values obtained using conventional reconstruction strategies. METHODS: We examined 166 stents in 85 consecutive patients who underwent CT and invasive coronary angiography (ICA) within 3 months of each other from 2019-2021 after percutaneous coronary intervention with coronary stent placement. The presence of ISR was defined as percent diameter stenosis ≥ 50% on ICA. We compared a super-resolution deep learning reconstruction, Precise IQ Engine (PIQE), and a model-based iterative reconstruction, Forward projected model-based Iterative Reconstruction SoluTion (FIRST). All images were reconstructed using PIQE and FIRST and assessed by two blinded cardiovascular radiographers. RESULTS: PIQE had a larger full width at half maximum of the lumen and smaller strut than FIRST. The image quality score in PIQE was higher than that in FIRST (4.2 ± 1.1 versus 2.7 ± 1.2, p < 0.05). In addition, the specificity and accuracy of ISR detection were better in PIQE than in FIRST (p < 0.05 for both), with particularly pronounced differences for stent diameters < 3.0 mm. CONCLUSION: PIQE provides superior image quality and diagnostic accuracy for ISR, even with stents measuring < 3.0 mm in diameter. CLINICAL RELEVANCE STATEMENT: With improvements in the diagnostic accuracy of in-stent stenosis, CT angiography could become a gatekeeper for ICA in post-stenting cases, obviating ICA in many patients after recent stenting with infrequent ISR and allowing non-invasive ISR detection in the late phase. KEY POINTS: • Despite CT technology advancements, evaluating in-stent stenosis severity, especially in small-diameter stents, remains challenging. • Compared with conventional methods, the Precise IQ Engine uses deep learning to improve spatial resolution. • Improved diagnostic accuracy of CT angiography helps avoid invasive coronary angiography after coronary artery stenting.

Pulmonary MRI with ultra-short TE using single- and dual-echo methods: comparison of capability for quantitative differentiation of non- or minimally invasive adenocarcinomas from other lung cancers with that of standard-dose thin-section CT.

OBJECTIVE: The purpose of this study was thus to compare capabilities for quantitative differentiation of non- and minimally invasive adenocarcinomas from other of pulmonary MRIs with ultra-short TE (UTE) obtained with single- and dual-echo techniques (UTE-MRISingle and UTE-MRIDual) and thin-section CT for stage IA lung cancer patients. METHODS: Ninety pathologically diagnosed stage IA lung cancer patients who underwent thin-section standard-dose CT, UTE-MRISingle, and UTE-MRIDual, surgical treatment and pathological examinations were included in this retrospective study. The largest dimension (Dlong), solid portion (solid Dlong), and consolidation/tumor (C/T) ratio of each nodule were assessed. Two-tailed Student's t-tests were performed to compare all indexes obtained with each method between non- and minimally invasive adenocarcinomas and other lung cancers. Receiver operating characteristic (ROC)-based positive tests were performed to determine all feasible threshold values for distinguishing non- or minimally invasive adenocarcinoma (MIA) from other lung cancers. Sensitivity, specificity, and accuracy were then compared by means of McNemar's test. RESULTS: Each index showed significant differences between the two groups (p < 0.0001). Specificities and accuracies of solid Dlong for UTE-MRIDual2nd echo and CTMediastinal were significantly higher than those of solid Dlong for UTE-MRISingle and UTE-MRIDual1st echo and all C/T ratios except CTMediastinal (p < 0.05). Moreover, the specificities and accuracies of solid Dlong and C/T ratio were significantly higher than those of Dlong for each method (p < 0.05). CONCLUSION: Pulmonary MRI with UTE is considered at least as valuable as thin-section CT for quantitative differentiation of non- and minimally invasive adenocarcinomas from other stage IA lung cancers. CLINICAL RELEVANCE STATEMENT: Pulmonary MRI with UTE's capability for quantitative differentiation of non- and minimally invasive adenocarcinomas from other lung cancers in stage IA lung cancer patients is equal or superior to that of thin-section CT. KEY POINTS: • Correlations were excellent for pathologically examined nodules with the largest dimensions (Dlong) and a solid component (solid Dlong) for all indexes (0.95 ≤ r ≤ 0.99, p < 0.0001). • Pathologically examined Dlong and solid Dlong obtained with all methods showed significant differences between non- and minimally invasive adenocarcinomas and other lung cancers (p < 0.0001). • Solid tumor components are most accurately measured by UTE-MRIDual2nd echo and CTMediastinal, whereas the ground-glass component is imaged by UTE-MRIDual1st echo and CTlung with high accuracy. UTE-MRIDual predicts tumor invasiveness with 100% sensitivity and 87.5% specificity at a C/T threshold of 0.5.

Chemical Exchange Saturation Transfer MRI: Capability for Predicting Therapeutic Effect of Chemoradiotherapy on Non-Small Cell Lung Cancer Patients.

BACKGROUND: Amide proton transfer (APT) weighted chemical exchange saturation transfer CEST (APTw/CEST) magnetic resonance imaging (MRI) has been suggested as having the potential for assessing the therapeutic effect of brain tumors or rectal cancer. Moreover, diffusion-weighted imaging (DWI) and positron emission tomography fused with computed tomography by means of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG-PET/CT) have been suggested as useful in same setting. PURPOSE: To compare the capability of APTw/CEST imaging, DWI, and FDG-PET/CT for predicting therapeutic effect of chemoradiotherapy (CRT) on stage III non-small cell lung cancer (NSCLC) patients. STUDY TYPE: Prospective. POPULATION: Eighty-four consecutive patients with Stage III NSCLC, 45 men (age range, 62-75 years; mean age, 71 years) and 39 women (age range, 57-75 years; mean age, 70 years). All patients were then divided into two groups (Response Evaluation Criteria in Solid Tumors [RECIST] responders, consisting of the complete response and partial response groups, and RECIST non-responders, consisting of the stable disease and progressive disease groups). FIELD STRENGTH/SEQUENCE: 3 T, echo planar imaging or fast advanced spin-echo (FASE) sequences for DWI and 2D half Fourier FASE sequences with magnetization transfer pulses for CEST imaging. ASSESSMENT: Magnetization transfer ratio asymmetry (MTRasym ) at 3.5 ppm, apparent diffusion coefficient (ADC), and maximum standard uptake value (SUVmax, ) on PET/CT were assessed by means of region of interest (ROI) measurements at primary tumor. STATISTICAL TESTS: Kaplan-Meier method followed by log-rank test and Cox proportional hazards regression analysis with multivariate analysis. A P value <0.05 was considered statistically significant. RESULTS: Progression-free survival (PFS) and overall survival (OS) had significant difference between two groups. MTRasym at 3.5 ppm (hazard ratio [HR] = 0.70) and SUVmax (HR = 1.41) were identified as significant predictors for PFS. Tumor staging (HR = 0.57) was also significant predictors for OS. DATA CONCLUSION: APTw/CEST imaging showed potential performance as DWI and FDG-PET/CT for predicting the therapeutic effect of CRT on stage III NSCLC patients. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Computed DWI MRI Results in Superior Capability for N-Stage Assessment of Non-Small Cell Lung Cancer Than That of Actual DWI, STIR Imaging, and FDG-PET/CT.

BACKGROUND: Computed diffusion-weighted imaging (cDWI) is a mathematical computation technique that generates DWIs for any b-value by using actual DWI (aDWI) data with at least two different b-values and may improve differentiation of metastatic from nonmetastatic lymph nodes. PURPOSE: To determine the appropriate b-value for cDWI to achieve a better diagnostic capability for lymph node staging (N-staging) in non-small cell lung cancer (NSCLC) patients compared to aDWI, short inversion time (TI) inversion recovery (STIR) imaging, or positron emission tomography with 2-[fluorine-18] fluoro-2-deoxy-d-glucose combined with computed tomography (FDG-PET/CT). STUDY TYPE: Prospective. SUBJECTS: A total of 245 (127 males and 118 females; mean age 72 years) consecutive histopathologically confirmed NSCLC patients. FIELD STRENGTH/SEQUENCE: A 3 T, half-Fourier single-shot turbo spin-echo sequence, electrocardiogram (ECG)-triggered STIR fast advanced spin-echo (FASE) sequence with black blood and STIR acquisition and DWI obtained by FASE with b-values of 0 and 1000 sec/mm2 . ASSESSMENT: From aDWIs with b-values of 0 and 1000 (aDWI1000 ) sec/mm2 , cDWI using 400 (cDWI400 ), 600 (cDWI600 ), 800 (cDWI800 ), and 2000 (cDWI2000 ) sec/mm2 were generated. Then, 114 metastatic and 114 nonmetastatic nodes (mediastinal and hilar lymph nodes) were selected and evaluated with a contrast ratio (CR) for each cDWI and aDWI, apparent diffusion coefficient (ADC), lymph node-to-muscle ratio (LMR) on STIR, and maximum standard uptake value (SUVmax ). STATISTICAL TESTS: Receiver operating characteristic curve (ROC) analysis, Youden index, and McNemar's test. RESULTS: Area under the curve (AUC) of CR600 was significantly larger than the CR400 , CR800 , CR2000 , aCR1000 , and SUVmax . Comparison of N-staging accuracy showed that CR600 was significantly higher than CR400 , CR2000 , ADC, aCR1000 , and SUVmax , although there were no significant differences with CR800 (P = 0.99) and LMR (P = 0.99). DATA CONCLUSION: cDWI with b-value at 600 sec/mm2 may have potential to improve N-staging accuracy as compared with aDWI, STIR, and PET/CT. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study.

OBJECTIVE: Ultra-high-resolution CT (UHR-CT), which can be applied normal resolution (NR), high-resolution (HR), and super-high-resolution (SHR) modes, has become available as in conjunction with multi-detector CT (MDCT). Moreover, deep learning reconstruction (DLR) method, as well as filtered back projection (FBP), hybrid-type iterative reconstruction (IR), and model-based IR methods, has been clinically used. The purpose of this study was to directly compare lung CT number and airway dimension evaluation capabilities of UHR-CT using different scan modes with those of MDCT with different reconstruction methods as investigated in a lung density and airway phantom design recommended by QIBA. MATERIALS AND METHODS: Lung CT number, inner diameter (ID), inner area (IA), and wall thickness (WT) were measured, and mean differences between measured CT number, ID, IA, WT, and standard reference were compared by means of Tukey's HSD test between all UHR-CT data and MDCT reconstructed with FBP as 1.0-mm section thickness. RESULTS: For each reconstruction method, mean differences in lung CT numbers and all airway parameters on 0.5-mm and 1-mm section thickness CTs obtained with SHR and HR modes showed significant differences with those obtained with the NR mode on UHR-CT and MDCT (p < 0.05). Moreover, the mean differences on all UHR-CTs obtained with SHR, HR, or NR modes were significantly different from those of 1.0-mm section thickness MDCTs reconstructed with FBP (p < 0.05). CONCLUSION: Scan modes and reconstruction methods used for UHR-CT were found to significantly affect lung CT number and airway dimension evaluations as did reconstruction methods used for MDCT. KEY POINTS: • Scan and reconstruction methods used for UHR-CT showed significantly higher CT numbers and smaller airway dimension evaluations as did those for MDCT in a QIBA phantom study (p < 0.05). • Mean differences in lung CT number for 0.25-mm, 0.5-mm, and 1.0-mm section thickness CT images obtained with SHR and HR modes were significantly larger than those for CT images at 1.0-mm section thickness obtained with MDCT and reconstructed with FBP (p < 0.05). • Mean differences in inner diameter (ID), inner area (IA), and wall thickness (WT) measured with SHR and HR modes on 0.5- and 1.0-mm section thickness CT images were significantly smaller than those obtained with NR mode on UHR-CT and MDCT (p < 0.05).

A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging.

PURPOSE: Bayesian estimation with advanced noise reduction (BEANR) in CT perfusion (CTP) could deliver more reliable cerebral blood flow (CBF) measurements than the commonly used reformulated singular value decomposition (rSVD). We compared the efficacy of CBF measurement by CTP using BEANR and rSVD, evaluating both relative to N-isopropyl-p-[(123) I]- iodoamphetamine (123I-IMP) single-photon emission computed tomography (SPECT) as a reference standard, in patients with cerebrovascular disease. METHODS: Thirty-one patients with suspected cerebrovascular disease underwent both CTP on a 320 detector-row CT system and SPECT. We applied rSVD and BEANR in the ischemic and contralateral regions to create CBF maps and calculate CBF ratios from the ischemic side to the healthy contralateral side (CBF index). The analysis involved comparing the CBF index between CTP methods and SPECT using Pearson's correlation and limits of agreement determined with Bland-Altman analyses, before comparing the mean difference in the CBF index between each CTP method and SPECT using the Wilcoxon matched pairs signed-rank test. RESULTS: The CBF indices of BEANR and 123I-IMP SPECT were significantly and positively correlated (r = 0.55, p < 0.0001), but there was no significant correlation between the rSVD method and SPECT (r = 0.15, p > 0.05). BEANR produced smaller limits of agreement for CBF than rSVD. The mean difference in the CBF index between BEANR and SPECT differed significantly from that between rSVD and SPECT (p < 0.001). CONCLUSIONS: BEANR has a better potential utility for CBF measurement in CTP than rSVD compared to SPECT in patients with cerebrovascular disease.

Three-Dimensional Gradient-Echo-Based Amide Proton Transfer-Weighted Imaging of Brain Tumors: Comparison With Two-Dimensional Spin-Echo-Based Amide Proton Transfer-Weighted Imaging.

OBJECTIVE: Although amide proton transfer-weighted (APTw) imaging is reported by 2-dimensional (2D) spin-echo-based sequencing, 3-dimensional (3D) APTw imaging can be obtained by gradient-echo-based sequencing. The purpose of this study was to compare the efficacy of APTw imaging between 2D and 3D imaging in patients with various brain tumors. METHODS: A total of 49 patients who had undergone 53 examinations [5 low-grade gliomas (LGG), 16 high-grade gliomas (HGG), 6 malignant lymphomas, 4 metastases, and 22 meningiomas] underwent APTw imaging using 2D and 3D sequences. The magnetization transfer ratio asymmetry (MTR asym ) was assessed by means of region of interest measurements. Pearson correlation was performed to determine the relationship between MTR asym for the 2 methods, and Student's t test to compare MTR asym for LGG and HGG. The diagnostic accuracy to differentiate HGG from LGG of the 2 methods was compared by means of the McNemar test. RESULTS: Three-dimensional APTw imaging showed a significant correlation with 2D APTw imaging ( r = 0.79, P < 0.0001). The limits of agreement between the 2 methods were -0.021 ± 1.42%. The MTR asym of HGG (2D: 1.97 ± 0.96, 3D: 2.11 ± 0.95) was significantly higher than those of LGG (2D: 0.46 ± 0.89%, P < 0.01; 3D: 0.15 ± 1.09%, P < 0.001). The diagnostic performance of the 2 methods to differentiate HGG from LGG was not significantly different ( P = 1). CONCLUSIONS: The potential capability of 3D APTw imaging is equal to or greater than that of 2D APTw imaging and is considered at least as valuable in patients with brain tumors.

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging.

Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted MRI at b values ranging from 1000 sec/mm2 to 5000 sec/mm2 in patients with prostate cancer. Materials and Methods In this retrospective study, images of the prostate obtained at DWI with a b value of 0 sec/mm2, DWI with a b value of 1000 sec/mm2 (DWI1000), DWI with a b value of 3000 sec/mm2 (DWI3000), and DWI with a b value of 5000 sec/mm2 (DWI5000) from consecutive patients with biopsy-proven cancer from January to June 2020 were reconstructed with and without DLR. Image quality was assessed using signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) from region-of-interest analysis and qualitatively assessed using a five-point visual scoring system (1 [very poor] to 5 [excellent]) for each high-b-value DWI sequence with and without DLR. The SNR, CNR, and visual score for DWI with and without DLR were compared with the paired t test and the Wilcoxon signed rank test with Bonferroni correction, respectively. Apparent diffusion coefficients (ADCs) from DWI with and without DLR were also compared with the paired t test with Bonferroni correction. Results A total of 60 patients (mean age, 67 years; age range, 49-79 years) were analyzed. DWI with DLR showed significantly higher SNRs and CNRs than DWI without DLR (P < .001); for example, with DWI1000 the mean SNR was 38.7 ± 0.6 versus 17.8 ± 0.6, respectively (P < .001), and the mean CNR was 18.4 ± 5.6 versus 7.4 ± 5.6, respectively (P < .001). DWI with DLR also demonstrated higher qualitative image quality than DWI without DLR (mean score: 4.8 ± 0.4 vs 4.0 ± 0.7, respectively, with DWI1000 [P = .001], 3.8 ± 0.7 vs 3.0 ± 0.8 with DWI3000 [P = .002], and 3.1 ± 0.8 vs 2.0 ± 0.9 with DWI5000 [P < .001]). ADCs derived with and without DLR did not differ substantially (P > .99). Conclusion Deep learning reconstruction improves the image quality of diffusion-weighted MRI scans of prostate cancer with no impact on apparent diffusion coefficient quantitation with a 3.0-T MRI system. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Efficacy of Ultrashort Echo Time Pulmonary MRI for Lung Nodule Detection and Lung-RADS Classification.

Background Pulmonary MRI with ultrashort echo time (UTE) has been compared with chest CT for nodule detection and classification. However, direct comparisons of these methods' capabilities for Lung CT Screening Reporting and Data System (Lung-RADS) evaluation remain lacking. Purpose To compare the capabilities of pulmonary MRI with UTE with those of standard- or low-dose thin-section CT for Lung-RADS classification. Materials and Methods In this prospective study, standard- and low-dose chest CT (270 mA and 60 mA, respectively) and MRI with UTE were used to examine consecutive participants enrolled between January 2017 and December 2020 who met American College of Radiology Appropriateness Criteria for lung cancer screening with low-dose CT. Probability of nodule presence was assessed for all methods with a five-point visual scoring system by two board-certified radiologists. All nodules were then evaluated in terms of their Lung-RADS classification using each method. To compare nodule detection capability of the three methods, consensus for performances was rated by using jackknife free-response receiver operating characteristic analysis, and sensitivity was compared by means of the McNemar test. In addition, weighted κ statistics were used to determine the agreement between Lung-RADS classification obtained with each method and the reference standard generated from standard-dose CT evaluated by two radiologists who were not included in the image analysis session. Results A total of 205 participants (mean age: 64 years ± 7 [standard deviation], 106 men) with 1073 nodules were enrolled. Figure of merit (FOM) (P < .001) had significant differences among three modalities (standard-dose CT: FOM = 0.91, low-dose CT: FOM = 0.89, pulmonary MRI with UTE: FOM = 0.94), with no evidence of false-positive findings in participants with all modalities (P > .05). Agreements for Lung-RADS classification between all modalities and the reference standard were almost perfect (standard-dose CT: κ = 0.82, P < .001; low-dose CT: κ = 0.82, P < .001; pulmonary MRI with UTE: κ = 0.82, P < .001). Conclusion In a lung cancer screening population, ultrashort echo time pulmonary MRI was comparable to standard- or low-dose CT for Lung CT Screening Reporting and Data System classification. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Wielpütz in this issue.

Comparison of utility of deep learning reconstruction on 3D MRCPs obtained with three different k-space data acquisitions in patients with IPMN.

OBJECTIVE: To compare the utility of deep learning reconstruction (DLR) for improving acquisition time, image quality, and intraductal papillary mucinous neoplasm (IPMN) evaluation for 3D MRCP obtained with parallel imaging (PI), multiple k-space data acquisition for each repetition time (TR) technique (Fast 3D mode multiple: Fast 3Dm) and compressed sensing (CS) with PI. MATERIALS AND METHODS: A total of 32 IPMN patients who had undergone 3D MRCPs obtained with PI, Fast 3Dm, and CS with PI and reconstructed with and without DLR were retrospectively included in this study. Acquisition time, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) obtained with all protocols were compared using Tukey's HSD test. Results of endoscopic ultrasound, ERCP, surgery, or pathological examination were determined as standard reference, and distribution classifications were compared among all 3D MRCP protocols by McNemar's test. RESULTS: Acquisition times of Fast 3Dm and CS with PI with and without DLR were significantly shorter than those of PI with and without DLR (p < 0.05). Each MRCP sequence with DLR showed significantly higher SNRs and CNRs than those without DLR (p < 0.05). IPMN distribution accuracy of PI with and without DLR and Fast 3Dm with DLR was significantly higher than that of Fast 3Dm without DLR and CS with PI without DLR (p < 0.05). CONCLUSION: DLR is useful for improving image quality and IPMN evaluation capability on 3D MRCP obtained with PI, Fast 3Dm, or CS with PI. Moreover, Fast 3Dm and CS with PI may play as substitution to PI for MRCP in patients with IPMN. KEY POINTS: • Mean examination times of multiple k-space data acquisitions for each TR and compressed sensing with parallel imaging were significantly shorter than that of parallel imaging (p < 0.0001). • When comparing image quality of 3D MRCPs with and without deep learning reconstruction, deep learning reconstruction significantly improved signal-to-noise ratio and contrast-to-noise ratio (p < 0.05). • IPMN distribution accuracies of parallel imaging with and without deep learning reconstruction (with vs. without: 88.0% vs. 88.0%) and multiple k-space data acquisitions for each TR with deep learning reconstruction (86.0%) were significantly higher than those of others (p < 0.05).

Small Cell Lung Cancer Staging: Prospective Comparison of Conventional Staging Tests, FDG PET/CT, Whole-Body MRI, and Coregistered FDG PET/MRI.

BACKGROUND. Whole-body MRI and FDG PET/MRI have shown encouraging results for staging of thoracic malignancy but are poorly studied for staging of small cell lung cancer (SCLC). OBJECTIVE. The purpose of our study was to compare the performance of conventional staging tests, FDG PET/CT, whole-body MRI, and FDG PET/MRI for staging of SCLC. METHODS. This prospective study included 98 patients (64 men, 34 women; median age, 74 years) with SCLC who underwent conventional staging tests (brain MRI; neck, chest, and abdominopelvic CT; and bone scintigraphy), FDG PET/CT, and whole-body MRI within 2 weeks before treatment; coregistered FDG PET/MRI was generated. Two nuclear medicine physicians independently reviewed conventional tests and FDG PET/CT examinations in separate sessions, and two chest radiologists independently reviewed whole-body MRI and FDG PET/MRI examinations in separate sessions. Readers assessed T, N, and M categories; TNM stage; and Veterans Administration Lung Cancer Study Group (VALSG) stage. Reader pairs subsequently reached consensus. Stages determined clinically during tumor board sessions served as the reference standard. RESULTS. Accuracy for T category was higher (p < .05) for whole-body MRI (94.9%) and FDG PET/MRI (94.9%) than for FDG PET/CT (85.7%). Accuracy for N category was higher (p < .05) for whole-body MRI (84.7%), FDG PET/MRI (83.7%), and FDG PET/CT (81.6%) than for conventional staging tests (75.5%). Accuracy for M category was higher (p < .05) for whole-body MRI (94.9%), FDG PET/MRI (94.9%), and FDG PET/CT (94.9%) than for conventional staging tests (84.7%). Accuracy for TNM stage was higher (p < .05) for whole-body MRI (88.8%) and FDG PET/MRI (86.7%) than for FDG PET/CT (77.6%) and conventional staging tests (72.4%). Accuracy for VALSG stage was higher (p < .05) for whole-body MRI (95.9%), FDG PET/MRI (95.9%), and FDG PET/CT (98.0%) than for conventional staging tests (82.7%). Interobserver agreement, expressed as kappa coefficients, ranged from 0.81 to 0.94 across imaging tests and staging endpoints. CONCLUSION. FDG PET/CT, whole-body MRI, and coregistered FDG PET/MRI outperformed conventional tests for various staging endpoints in patients with SCLC. Whole-body MRI and FDG PET/MRI outperformed FDG PET/CT for T category and thus TNM stage, indicating the utility of MRI for assessing extent of local invasion in SCLC. CLINICAL IMPACT. Incorporation of either MRI approach may improve initial staging evaluation in SCLC.

Machine learning for lung texture analysis on thin-section CT: Capability for assessments of disease severity and therapeutic effect for connective tissue disease patients in comparison with expert panel evaluations.

BACKGROUND: The need for quantitative assessment of interstitial lung involvement on thin-section computed tomography (CT) has arisen in interstitial lung diseases including connective tissue disease (CTD). PURPOSE: To evaluate the capability of machine learning (ML)-based CT texture analysis for disease severity and treatment response assessments in comparison with qualitatively assessed thin-section CT for patients with CTD. MATERIAL AND METHODS: A total of 149 patients with CTD-related ILD (CTD-ILD) underwent initial and follow-up CT scans (total 364 paired serial CT examinations), pulmonary function tests, and serum KL-6 level tests. Based on all follow-up examination results, all paired serial CT examinations were assessed as "Stable" (n = 188), "Worse" (n = 98) and "Improved" (n = 78). Next, quantitative index changes were determined by software, and qualitative disease severity scores were assessed by consensus of two radiologists. To evaluate differences in each quantitative index as well as in disease severity score between paired serial CT examinations, Tukey's honestly significant difference (HSD) test was performed among the three statuses. Stepwise regression analyses were performed to determine changes in each pulmonary functional parameter and all quantitative indexes between paired serial CT scans. RESULTS: Δ% normal lung, Δ% consolidation, Δ% ground glass opacity, Δ% reticulation, and Δdisease severity score showed significant differences among the three statuses (P < 0.05). All differences in pulmonary functional parameters were significantly affected by Δ% normal lung, Δ% reticulation, and Δ% honeycomb (0.16 ≤r2 ≤0.42; P < 0.05). CONCLUSION: ML-based CT texture analysis has better potential than qualitatively assessed thin-section CT for disease severity assessment and treatment response evaluation for CTD-ILD.

Evaluation of Velopharyngeal Closure Function With 4-Dimensional Computed Tomography and Assessment of Radiation Exposure in Pediatric Patients: A Cross-Sectional Study.

OBJECTIVE: Some patients with cleft palate (CP) need secondary surgery to improve functionality. Although 4-dimensional assessment of velopharyngeal closure function (VPF) in patients with CP using computed tomography (CT) has been existed, the knowledge about quantitative evaluation and radiation exposure dose is limited. We performed a qualitative and quantitative assessment of VPF using CT and estimated the exposure doses. DESIGN: Cross-sectional. SETTING: Computed tomography images from 5 preoperative patients with submucous CP (SMCP) and 10 postoperative patients with a history of CP (8 boys and 7 girls, aged 4-7 years) were evaluated. PATIENTS: Five patients had undergone primary surgery for SMCP; 10 received secondary surgery for hypernasality. MAIN OUTCOME MEASURES: The presence of velopharyngeal insufficiency (VPI), patterns of velopharyngeal closure (VPC), and cross-sectional area (CSA) of VPI was evaluated via CT findings. Organ-absorbed radiation doses were estimated in 5 of 15 patients. The differences between cleft type and VPI, VPC patterns, and CSA of VPI were evaluated. RESULTS: All patients had VPI. The VPC patterns (SMCP/CP) were evaluated as coronal (1/4), sagittal (0/1), circular (1/2), and circular with Passavant's ridge (2/2); 2 patients (1/1) were unevaluable because of poor VPF. The CSA of VPI was statistically larger in the SMCP group (P = .0027). The organ-absorbed radiation doses were relatively lower than those previously reported. CONCLUSIONS: Four-dimensional CT can provide the detailed findings of VPF that are not possible with conventional CT, and the exposure dose was considered medically acceptable.

3D Oxygen-Enhanced MRI at 3T MR System: Comparison With Thin-Section CT of Quantitative Capability for Pulmonary Functional Loss Assessment and Clinical Stage Classification of COPD in Smokers.

BACKGROUND: Oxygen (O2 )-enhanced MRI is mainly performed by a 2D sequence using 1.5T MR systems but trying to be obtained by a 3D sequence using a 3T MR system. PURPOSE: To compare the capability of 3D O2 -enhanced MRI and that of thin-section computed tomography (CT) for pulmonary functional loss assessment and clinical stage classification of chronic obstructive pulmonary disease (COPD) in smokers. STUDY TYPE: Prospective study. POPULATION: Fifty six smokers were included. FIELD STRENGTH/ SEQUENCE: 3T, 3D O2 -enhanced MRIs were performed with a 3D T1 -weighted fast field echo pulse sequence using the multiple flip angles. ASSESSMENTS: Smokers were classified into four stages ("Without COPD," "Mild COPD," "Moderate COPD," "Severe or very severe COPD"). Maps of regional changes in T1 values were generated from O2 -enhanced MR data. Regions of interest (ROIs) were then placed over the lung on all slices and averaged to determine mean T1 value change (ΔT1 ). Quantitative CT used the percentage of low attenuation areas within the entire lung (LAA%). STATISTICAL TESTS: ΔT1 and LAA% were correlated with pulmonary functional parameters, and compared for four stages using Tukey's Honestly Significant Difference test. Discrimination analyses were performed and McNemar's test was used for a comparison of the accuracy of the indexes. RESULTS: There were significantly higher correlations between ΔT1 and pulmonary functional parameters (-0.83 ≤ r ≤ -0.71, P < 0.05) than between LAA% and the same pulmonary functional parameters (-0.76 ≤ r ≤ -0.69, P < 0.05). ΔT1 and LAA% of the "Mild COPD" and "Moderate COPD" groups were significantly different from those of the "Severe or Very Severe COPD" group (P < 0.05). Discriminatory accuracy of ΔT1 (62.5%) and ΔT1 with LAA% (67.9%) was significantly greater than that of LAA% (48.2%, P < 0.05). DATA CONCLUSION: Compared with thin-section CT, 3D O2 -enhanced MRI has a similar capability for pulmonary functional assessment but better potential for clinical stage classification in smokers. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Association of computed tomography-derived myocardial mass with fractional flow reserve-verified ischemia or subsequent therapeutic strategy.

The aim of the present study was to examine the association of myocardial mass verified by computed tomography (CT) and invasive fractional flow reserve (FFR)-verified myocardial ischemia, or subsequent therapeutic strategy for the targeted vessels after FFR examination. We examined 333 vessels with intermediate stenoses in 297 patients (mean age 69.0 ± 9.5, 228 men) undergoing both coronary CT angiography and invasive FFR, and reviewed the therapeutic strategy after FFR. Of 333 vessels, FFR ≤ 0.80 was documented in 130 (39.0%). Myocardial volume supplied by the target vessel (MVT) was larger in those with FFR-verified ischemia than those without (53.4 ± 19.5 vs. 42.9 ± 22.2 cm3, P < 0.001). Addition of MVT to a model including patient characteristics (age, gender), visual assessment (≥ 70% stenosis, high-risk appearance), and quantitative CT vessel parameters [minimal lumen area (MLA), plaque burden at MLA, percent aggregate plaque volume] improved C-index (from 0.745 to 0.778, P = 0.020). Furthermore, of 130 vessels with FFR ≤ 0.80, myocardial volume exposed to ischemia (MVI) was larger in the vessels with early revascularization after FFR examination than those without (37.2 ± 20.0 vs. 26.8 ± 15.0 cm3, P = 0.003), and was independently associated with early revascularization [OR = 1.03, 95% confidence interval (1.02-1.11), P < 0.001]. Using an on-site CT workstation, MVT identified coronary arteries with FFR-verified ischemia easily and non-invasively, and MVI was associated with subsequent therapeutic strategy after FFR examinations.

Predictors of Diagnostic Contributions and Spontaneous Remission of Symptoms Associated with Positron Emission Tomography with Fluorine-18-Fluorodeoxy Glucose Combined with Computed Tomography in Classic Fever or Inflammation of Unknown Origin: a Retrospective Study.

BACKGROUND: In patients with fever or inflammation of unknown origin (fever of unknown origin [FUO] or inflammation of unknown origin [IUO], respectively), expert consensus recommends the use of positron emission tomography with fluorine-18-fluorodeoxy glucose combined with computed tomography (FDG-PET/CT) when standard work-up fails to identify diagnostic clues. However, the clinical variables associated with successful localization of the cause by FDG-PET/CT remain uncertain. Moreover, the long-term outcomes of patients with unexplained FUO or IUO after negative FDG-PET/CT results are unknown. Therefore, we assessed predictors of successful diagnosis of FUO or IUO caused by FDG-PET/CT and associations of spontaneous remission of symptoms with FDG-PET/CT results. METHODS: All patients with FUO or IUO, who underwent FDG-PET/CT from 2013 to 2019 because diagnostic work-up failed to identify a cause, were retrospectively included. We calculated the diagnostic yield and performed multivariable logistic regression to assess characteristics previously proposed to be associated with successful localization of FUO or IUO causes. We also assessed whether the FDG-PET/CT results were associated with spontaneous remissions. RESULTS: In total, 50 patients with diagnostically challenging FUO or IUO (35 with FUO and 15 with IUO) were assessed. Other than one case of infection, all the identified causes were either malignancy or non-infectious inflammatory diseases (each with 18 patients), and FDG-PET/CT correctly localized the cause in 29 patients (diagnostic yield = 58%). None of the proposed variables was associated with successful localization. All 13 patients with sustained unexplained cause remained alive (median follow-up, 190 days). Spontaneous remission was observed in 4 of 5 patients with a negative FDG-PET/CT, and 1 of 8 with a positive result (P = 0.018). CONCLUSION: In the current cohort, the proposed variables were not predictive for successful localization by FDG-PET/CT. A negative FDG-PET/CT scan may be prognostic for spontaneous remission in patients with sustained FUO or IUO.

Decision Support System for Lung Cancer Using PET/CT and Microscopic Images.

Lung cancer is the most common cancer among men and the third most common among women in the world. Many diagnostic techniques have been introduced to diagnose lung cancer. Positron emission tomography (PET)/computed tomography (CT) examination is an image diagnostic method that performs automatic detection and distinction of lung lesions. In addition, pathological examination by biopsy is performed for lesions that are suspected of being malignant, and appropriate treatment methods are applied according to the diagnosis results. Currently, lung cancer diagnosis is performed through coordination between respiratory, radiation, and pathological diagnosis experts, but there are some tasks, such as image diagnosis, that require a large amount of time and effort to complete. Therefore, we developed a decision support system using PET/CT and microscopic images at the time of image diagnosis, which leads to appropriate treatment. In this chapter, we introduce the proposed system using deep learning and radiomic techniques.

Velopharyngeal closure analysis using four-dimensional computed tomography: a pilot study of healthy volunteers and adult patients with cleft palate.

BACKGROUND: Nasopharyngoscopy is a common method to evaluate velopharyngeal closure in patients with cleft palate. However, insertion of a fiberoptic nasopharyngoscope causes discomfort in patients. The aim of this study was to estimate the reliability of short-time exposure images obtained using 320-row area detector computed tomography (320-ADCT) as a novel evaluation method for the assessment of velopharyngeal function. METHODS: We evaluated five healthy adult volunteers and five postoperative adult patients with cleft palate. During a 3.3-s imaging exposure, the participants were asked to perform two tasks: nasal inspiration and subsequent oral expiration through a catheter into a water-filled cup. The movement of the velopharyngeal structures was recorded during each examination, and the presence of velopharyngeal insufficiency (VPI) and velopharyngeal closure (VPC) patterns were estimated. If VPI was detected, the cross-sectional area was also calculated. Cohen's kappa and weighted kappa coefficients were used to evaluate the concordance of nasopharyngoscopy and 320-ADCT evaluation. RESULTS: Speech pathology evaluation did not reveal hypernasality in any study participant. Micro-VPI was detected by nasopharyngoscopy in one healthy volunteer and two patients. 320-ADCT detected micro-VPI in two more patients. The cross-sectional area of the VPI in these subjects ranged from 2.53 to 16.28 mm2. Nasopharyngoscopy and 320-ADCT were concordant in detecting VPI in eight participants (κ = 0.6) and in assessing VPC patterns in nine (κ = 0.82). Moreover, images obtained using 320-ADCT allowed for reduced dead angle and, thus, easy detection of micro-VPI and Passavant's ridges. CONCLUSION: Although the radiation exposure cannot be ignored, our novel evaluation method using 320-ADCT enables more detailed evaluation of VPC than nasopharyngoscopy. Future studies should investigate the relationship between 320-ADCT findings and speech pathology evaluations.

Japanese multicenter database of healthy controls for [123I]FP-CIT SPECT.

PURPOSE: The aim of this multicenter trial was to generate a [123I]FP-CIT SPECT database of healthy controls from the common SPECT systems available in Japan. METHODS: This study included 510 sets of SPECT data from 256 healthy controls (116 men and 140 women; age range, 30-83 years) acquired from eight different centers. Images were reconstructed without attenuation or scatter correction (NOACNOSC), with only attenuation correction using the Chang method (ChangACNOSC) or X-ray CT (CTACNOSC), and with both scatter and attenuation correction using the Chang method (ChangACSC) or X-ray CT (CTACSC). These SPECT images were analyzed using the Southampton method. The outcome measure was the specific binding ratio (SBR) in the striatum. These striatal SBRs were calibrated from prior experiments using a striatal phantom. RESULTS: The original SBRs gradually decreased in the order of ChangACSC, CTACSC, ChangACNOSC, CTACNOSC, and NOACNOSC. The SBRs for NOACNOSC were 46% lower than those for ChangACSC. In contrast, the calibrated SBRs were almost equal under no scatter correction (NOSC) conditions. A significant effect of age was found, with an SBR decline rate of 6.3% per decade. In the 30-39 age group, SBRs were 12.2% higher in women than in men, but this increase declined with age and was absent in the 70-79 age group. CONCLUSIONS: This study provided a large-scale quantitative database of [123I]FP-CIT SPECT scans from different scanners in healthy controls across a wide age range and with balanced sex representation. The phantom calibration effectively harmonizes SPECT data from different SPECT systems under NOSC conditions. The data collected in this study may serve as a reference database.

Ultra-High-Resolution Computed Tomography Angiography for Assessment of Coronary Artery Stenosis.

BACKGROUND: Limitations of coronary computed tomography (CTA) include false-positive stenosis at calcified lesions and assessment of in-stent patency. A prototype of ultra-high resolution computed tomography (U-HRCT: 1,792 channels and 0.25-mm slice thickness×128 rows) with improved spatial resolution was developed. We assessed the diagnostic accuracy of coronary artery stenosis using U-HRCT.Methods and Results:Seventy-nine consecutive patients who underwent CTA using U-HRCT were prospectively included. Coronary artery stenosis was graded from 0 (no plaque) to 5 (occlusion). Stenosis grading at 102 calcified lesions was compared between U-HRCT and conventional-resolution CT (CRCT: 896 channels and 0.5-mm slice thickness×320 rows). Median stenosis grading at calcified plaque was significantly improved on U-HRCT compared with CRCT (1; IQR, 1-2 vs. 2; IQR, 1-3, P<0.0001). Assessability of in-stent lumen was evaluated on U-HRCT in 79 stents. Stent strut thickness and luminal diameter were quantitatively compared between U-HRCT and CRCT. Of 79 stents, 83.5% were assessable on U-HRCT; 80% of stents with diameter 2.5 mm were regarded as assessable. On U-HRCT, stent struts were significantly thinner (median, 0.78 mm; IQR, 0.7-0.83 mm vs. 0.83 mm; IQR, 0.75-0.92 mm, P=0.0036), and in-stent lumens were significantly larger (median, 2.08 mm; IQR, 1.55-2.51 mm vs. 1.74 mm; IQR, 1.31-2.06 mm, P<0.0001) than on CRCT. CONCLUSIONS: U-HRCT with improved spatial resolution visualized calcified lesions with fewer artifacts. The in-stent lumen of stents with diameter ≥2.5 mm was assessable on U-HRCT.