Predicting postoperative systolic dysfunction in mitral regurgitation: CT vs. echocardiography

Introduction

Volume overload from mitral regurgitation can result in left ventricular systolic dysfunction. To prevent this, it is essential to operate before irreversible dysfunction occurs, but the optimal timing of intervention remains unclear. Current echocardiographic guidelines are based on 2D linear measurement thresholds only. We compared volumetric CT-based and 2D echocardiographic indices of LV size and function as predictors of post-operative systolic dysfunction following mitral repair.

Methods

We retrospectively identified patients with primary mitral valve regurgitation who underwent repair between 2005 and 2021. Several indices of LV size and function measured on preoperative cardiac CT were compared with 2D echocardiography in predicting post-operative LV systolic dysfunction (LVEFecho <50%). Area under the curve (AUC) was the primary metric of predictive performance.

Results

A total of 243 patients were included (mean age 57 ± 12 years; 65 females). The most effective CT-based predictors of post-operative LV systolic dysfunction were ejection fraction [LVEFCT; AUC 0.84 (95% CI: 0.77-0.92)] and LV end systolic volume indexed to body surface area [LVESViCT; AUC 0.88 (0.82-0.95)]. The best echocardiographic predictors were LVEFecho [AUC 0.70 (0.58-0.82)] and LVESDecho [AUC 0.79 (0.70-0.89)]. LVEFCT was a significantly better predictor of post-operative LV systolic dysfunction than LVEFecho (p = 0.02) and LVESViCT was a significantly better predictor than LVESDecho (p = 0.03). Ejection fraction measured by CT demonstrated significantly greater reproducibility than echocardiography.

Discussion

CT-based volumetric measurements may be superior to established 2D echocardiographic parameters for predicting LV systolic dysfunction following mitral valve repair. Validation with prospective study is warranted.

Motion artifact correction in cardiac CT using cross-phase temporospatial information and synergistic attention gate and spatial transformer sub-networks

Objectives.To improve quality of coronary CT angiography (CCTA) images using a generalizable motion-correction algorithm.Approach. A neural network with attention gate and spatial transformer (ATOM) was developed to correct coronary motion. Phantom and patient CCTA images (39 males, 32 females, age range 19-92, scan date 02/2020 to 10/2021) retrospectively collected from dual-source CT were used to create training, development, and testing sets corresponding to 140- and 75 ms temporal resolution, with 75 ms images as labels. To test generalizability, ATOM was deployed for locally adaptive motion-correction in both 140- and 75 ms patient images. Objective metrics were used to assess motion-corrupted and corrected phantom and patient images, including structural-similarity-index (SSIM), dice-similarity-coefficient (DSC), peak-signal-noise-ratio (PSNR), and normalized root-mean-square-error (NRMSE). In objective quality assessment, ATOM was compared with several baseline networks, including U-net, U-net plus attention gate, U-net plus spatial transformer, VDSR, and ResNet. Two cardiac radiologists independently interpreted motion-corrupted and -corrected images at 75 and 140 ms in a blinded fashion and ranked diagnostic image quality (worst to best: 1-4, no ties).Main results. ATOM improved quality metrics (p< 0.05) before/after correction: in phantom, SSIM 0.87/0.95, DSC 0.85/0.93, PSNR 19.4/22.5, NRMSE 0.38/0.27; in patient images, SSIM 0.82/0.88, DSC 0.88/0.90, PSNR 30.0/32.0, NRMSE 0.16/0.12. ATOM provided more consistent improvement of objective image quality, compared to the presented baseline networks. The motion-corrected images received better ranks than un-corrected at the same temporal resolution (p< 0.05): 140 ms images 1.65/2.25, and 75 ms images 3.1/3.2. The motion-corrected 75 ms images received the best rank in 65% of testing cases. A fair-to-good inter-reader agreement was observed (Kappa score 0.58).Significance. ATOM reduces motion artifacts, improving visualization of coronary arteries. This algorithm can be used to virtually improve temporal resolution in both single- and dual-source CT.

Comparison of Photon-counting Detector and Energy-integrating Detector CT for Visual Estimation of Coronary Percent Luminal Stenosis

Background Compared with energy-integrating detector (EID) CT, the improved resolution of photon-counting detector (PCD) CT coupled with high-energy virtual monoenergetic images (VMIs) has been shown to decrease calcium blooming on images in phantoms and cadaveric specimens. Purpose To determine the impact of dual-source PCD CT on visual and quantitative estimation of percent diameter luminal stenosis compared with dual-source EID CT in patients. Materials and Methods This prospective study recruited consecutive adult patients from an outpatient facility between January and March 2022. Study participants underwent clinical dual-source EID coronary CT angiography followed by a research dual-source PCD CT examination. For PCD CT, multienergy data were used to create VMIs at 50 and 100 keV. Two readers independently reviewed EID CT images followed by PCD CT images after a washout period. Readers visually graded the most severe stenosis in terms of percent diameter luminal stenosis for the left main, left anterior descending, right, and circumflex coronary arteries, unblinded to scanner type. Quantitative measures of percent stenosis were made using commercial software. Visual and quantitative estimates of percent stenosis were compared between EID CT and PCD CT using the Wilcoxon signed-rank test. Results A total of 25 participants (median age, 59 years [range, 18-78 years]; 16 male participants) were enrolled. On EID CT images, readers 1 and 2 identified 39 and 32 luminal stenoses, respectively, with a percent diameter luminal stenosis greater than 0%. Visual estimates of percent stenosis were lower on PCD CT images than EID CT images (reader 1: median 20.6% [IQR, 8.8%-61.2%] vs 31.8% [IQR, 12.9%-69.7%], P < .001; reader 2: 6.5% [IQR, 0.4%-54.1%] vs 22.9% [IQR, 1.8%-67.4%], P = .002). No difference was observed between EID CT and PCD CT for quantitative measures of percent stenosis (median difference, -1.5% [95% CI: -3.0%, 2.5%]; P = .51). Conclusion Relative to using EID CT, using PCD CT led to decreases in visual estimates of percent stenosis. © RSNA, 2023 See also the editorial by Murphy and Donnelly in this issue.

ACR Appropriateness Criteria® Preprocedural Planning for Transcatheter Aortic Valve Replacement: 2023 Update

This document discusses preprocedural planning for transcatheter aortic valve replacement, evaluating the imaging modalities used in initial imaging for preprocedure planning under two variants 1) Preintervention planning for transcatheter aortic valve replacement: assessment of aortic root; and 2) Preintervention planning for transcatheter aortic valve replacement: assessment of supravalvular aorta and vascular access. US echocardiography transesophageal, MRI heart function and morphology without and with IV contrast, MRI heart function and morphology without IV contrast and CT heart function and morphology with IV contrast are usually appropriate for assessment of aortic root. CTA chest with IV contrast, CTA abdomen and pelvis with IV contrast, CTA chest abdomen pelvis with IV contrast are usually appropriate for assessment of supravalvular aorta and vascular access. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Detection of Low Blood Hemoglobin Levels on Pulmonary CT Angiography: A Feasibility Study Combining Dual-Energy CT and Machine Learning

OBJECTIVES

To evaluate if dual-energy CT (DECT) pulmonary angiography (CTPA) can detect anemia with the aid of machine learning.

METHODS

Inclusion of 100 patients (mean age ± SD, 51.3 ± 14.8 years; male-to-female ratio, 42/58) who underwent DECT CTPA and hemoglobin (Hb) analysis within 24 h, including 50 cases with Hb below and 50 controls with Hb ≥ 12 g/dL. Blood pool attenuation was assessed on virtual noncontrast (VNC) images at eight locations. A classification model using extreme gradient-boosted trees was developed on a training set (n = 76) for differentiating cases from controls. The best model was evaluated in a separate test set (n = 24).

RESULTS

Blood pool attenuation was significantly lower in cases than controls (p-values < 0.01), except in the right atrium (p = 0.06). The machine learning model had sensitivity, specificity, and accuracy of 83%, 92%, and 88%, respectively. Measurements at the descending aorta had the highest relative importance among all features; a threshold of 43 HU yielded sensitivity, specificity, and accuracy of 68%, 76%, and 72%, respectively.

CONCLUSION

VNC imaging and machine learning shows good diagnostic performance for detecting anemia on DECT CTPA.

Optimal Virtual Monoenergetic Photon Energy (keV) for Photon-Counting-Detector Computed Tomography Angiography

OBJECTIVE

This study aimed to determine the optimal photon energy for virtual monoenergetic images (VMI) in computed tomography angiography (CTA) using photon-counting-detector (PCD) CT.

METHODS

Under institutional review board approval, 10 patients (abdominal, n = 4; lower extremity, n = 3; head and neck, n = 3) were scanned on an investigational PCD-CT (Count Plus, Siemens Healthcare) at 120 or 140 kV. All images were iteratively reconstructed with Bv48 kernel and 2-mm slice thickness. Axial and coronal VMI maximum-intensity projections were created in the range 40 to 65 keV (5-keV steps). Contrast-to-noise ratio (CNR) was calculated for major arteries in each VMI series. Two radiologists blindly ranked each VMI series for overall image quality and visualization of small vessels and pathology. The median and SD of scores for each photon energy were calculated. In addition, readers identified any VMIs that distinguished itself from others in terms of vessel/pathology visualization or artifacts.

RESULTS

Mean iodine CNR was highest in 40-keV VMIs for all evaluated arteries. Across readers, the 50-keV VMI had the highest combined score (2.00 ± 1.11). Among different body parts, the 45-keV VMI was ranked highest for the head-and-neck (1.75 ± 0.68) and lower extremity (2.00 ± 1.41) CTA. Meanwhile, 50- and 55-keV VMIs were ranked highest for abdominal (2.50 ± 1.35 and 2.50 ± 1.56) CTA. The 40-keV VMI received the highest score for iodine visualization in vessels, and the 65-keV VMI for reduced metal/calcium-blooming artifacts.

CONCLUSIONS

Quantitatively, VMIs at 40 keV had the highest CNR in major arterial vasculature using PCD-CTA. Based on radiologists' preference, the 45- and 50-keV VMIs were optimal for small body parts (eg, head and neck and lower extremity) and large body parts (eg, abdomen), respectively.

High-pitch, high temporal resolution, multi-energy cardiac imaging on a dual-source photon-counting-detector CT

OBJECTIVE

To measure the accuracy of material decomposition using a dual-source photon-counting-detector (DS-PCD) CT operated in the high-pitch helical scanning mode and compare the results against dual-source energy-integrating-detector (DS-EID) CT, which requires use of a low-pitch value in dual-energy mode.

METHODS

A DS-PCD CT and a DS-EID CT were used to scan a cardiac motion phantom consisting of a 3-mm diameter iodine cylinder. Iodine maps were reconstructed using DS-PCD in high-pitch mode and DS-EID in low-pitch mode. Image-based circularity, diameter, and iodine concentration of the iodine cylinder were calculated and compared between the two scanners. With institutional review board approval, in vivo exams were performed with the DS-PCD CT in high-pitch mode. Images were qualitatively compared against patients with similar heart rates that were scanned with DS-EID CT in low-pitch dual-energy mode.

RESULTS

On iodine maps, the mean circularity was 0.97 ± 0.02 with DS-PCD in high-pitch mode and 0.95 ± 0.06 with DS-EID in low-pitch mode. The mean diameter was 2.9 ± 0.2 mm with DS-PCD and 3.1 ± 0.2 mm with DS-EID, both of which are close to the 3 mm ground truth. For DS-PCD, the mean iodine concentration was 9.6 ± 0.8 mg/ml and this was consistent with the 9.4 ± 0.6 mg/ml value obtained with the cardiac motion disabled. For DS-EID, the concentration was 12.7 ± 1.2 mg/ml with motion enabled and 11.7 ± 0.5 mg/ml disabled. The background noise in the iodine maps was 15.1 HU with DS-PCD and 14.4 HU with DS-EID, whereas the volume CT dose index (CTDIvol ) was 3 mGy with DS-PCD and 11 mGy with DS-EID. On comparison of six patients (three on PCD, three on EID) with similar heart rates, DS-PCD provided iodine maps with well-defined coronaries even at a high heart rate of 86 beats per minute. Meanwhile, there were substantial motion artifacts in iodine maps obtained with DS-EID for patients with similar heart rates.

CONCLUSION

In a cardiac motion phantom, DS-PCD CT can perform accurate material decomposition in high-pitch mode, providing iodine maps with excellent geometric accuracy and robustness to motion at approximately 38% of the dose for similar noise as DS-EID CT.

Optimizing low contrast volume thoracic CT angiography: From the basics to the advanced

Contrast-enhanced CT angiography (CTA) is a widely used, noninvasive imaging technique for evaluating cardiovascular structures. Contrast-induced nephrotoxicity is a concern in renal disease; however, the true nephrotoxic potential of iodinated contrast media (CM) is unknown. If a renal impaired patient requires CTA, it is important to protect the kidneys from further harm by reducing total iodinated CM volume while still obtaining diagnostic quality imaging. These same reduced volume CM techniques can also be applied to nonrenal impaired patients in times of CM shortage. This educational review discusses several modifications to CTA that can be adapted to both conventional 64-slice and the newer generation CT scanners which enable subsecond acquisition with a reduced CM volume technique. Such modifications include hardware and software adjustments and changes to both the volume and flow rate of administered CM, with the goal to reduce the dose of CM without compromising diagnostic yield.

First Clinical Photon-counting Detector CT System: Technical Evaluation

Background The first clinical CT system to use photon-counting detector (PCD) technology has become available for patient care. Purpose To assess the technical performance of the PCD CT system with use of phantoms and representative participant examinations. Materials and Methods Institutional review board approval and written informed consent from four participants were obtained. Technical performance of a dual-source PCD CT system was measured for standard and high-spatial-resolution (HR) collimations. Noise power spectrum, modulation transfer function, section sensitivity profile, iodine CT number accuracy in virtual monoenergetic images (VMIs), and iodine concentration accuracy were measured. Four participants were enrolled (between May 2021 and August 2021) in this prospective study and scanned using similar or lower radiation doses as their respective clinical examinations performed on the same day using energy-integrating detector (EID) CT. Image quality and findings from the participants' PCD CT and EID CT examinations were compared. Results All standard technical performance measures met accreditation and regulatory requirements. Relative to filtered back-projection reconstructions, images from iterative reconstruction had lower noise magnitude but preserved noise power spectrum shape and peak frequency. Maximum in-plane spatial resolutions of 125 and 208 µm were measured for HR and standard PCD CT scans, respectively. Minimum values for section sensitivity profile full width at half maximum measurements were 0.34 mm (0.2-mm nominal section thickness) and 0.64 mm (0.4-mm nominal section thickness) for HR and standard PCD CT scans, respectively. In a 120-kV standard PCD CT scan of a 40-cm phantom, VMI iodine CT numbers had a mean percentage error of 5.7%, and iodine concentration had root mean squared error of 0.5 mg/cm³, similar to previously reported values for EID CT. VMIs, iodine maps, and virtual noncontrast images were created for a coronary CT angiogram acquired with 66-msec temporal resolution. Participant PCD CT images showed up to 47% lower noise and/or improved spatial resolution compared with EID CT. Conclusion Technical performance of clinical photon-counting detector (PCD) CT is improved relative to that of a current state-of-the-art CT system. The dual-source PCD geometry facilitated 66-msec temporal resolution multienergy cardiac imaging. Study participant images illustrated the effect of the improved technical performance. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Willemink and Grist in this issue.

Novel imaging biomarkers predict outcomes in stage III unresectable non-small cell lung cancer treated with chemoradiation and durvalumab

Background

The landmark study of durvalumab as consolidation therapy in NSCLC patients (PACIFIC trial) demonstrated significantly longer progression-free survival (PFS) in patients with locally advanced, unresectable non-small cell lung cancer (NSCLC) treated with durvalumab (immunotherapy, IO) therapy after chemoradiotherapy (CRT). In clinical practice in the USA, durvalumab continues to be used in patients across all levels of programmed cell death ligand-1 (PD-L1) expression. While immune therapies have shown promise in several cancers, some patients either do not respond to the therapy or have cancer recurrence after an initial response. It is not clear so far who will benefit of this therapy or what the mechanisms behind treatment failure are.

Methods

A total of 133 patients with unresectable stage III NSCLC who underwent durvalumab after CRT or CRT alone were included. Patients treated with durvalumab IO after CRT were randomly split into training (D1=59) and test (D2=59) sets and the remaining 15 patients treated with CRT alone were grouped in D3. Radiomic textural patterns from within and around the target nodules were extracted. A radiomic risk score (RRS) was built and was used to predict PFS and overall survival (OS). Patients were divided into high-risk and low-risk groups based on median RRS.

Results

RRS was found to be significantly associated with PFS in D1 (HR=2.67, 95% CI 1.85 to 4.13, p<0.05, C-index=0.78) and D2 (HR=2.56, 95% CI 1.63 to 4, p<0.05, C-index=0.73). Similarly, RRS was associated with OS in D1 (HR=1.89, 95% CI 1.3 to 2.75, p<0.05, C-index=0.67) and D2 (HR=2.14, 95% CI 1.28 to 3.6, p<0.05, C-index=0.69), respectively. RRS was found to be significantly associated with PFS in high PD-L1 (HR=3.01, 95% CI 1.41 to 6.45, p=0.0044) and low PD-L1 (HR=2.74, 95% CI 1.8 to 4.14, p=1.77e-06) groups. Moreover, RRS was not significantly associated with OS in the high PD-L1 group (HR=2.08, 95% CI 0.98 to 4.4, p=0.054) but was significantly associated with OS in the low PD-L1 group (HR=1.61, 95% CI 1.14 to 2.28, p=0.0062). In addition, RRS was significantly associated with PFS (HR=2.77, 95% CI 1.17 to 6.52, p=0.019, C-index=0.77) and OS (HR=2.62, 95% CI 1.25 to 5.51, p=0.01, C-index=0.77) in D3, respectively.

Conclusions

Tumor radiomics of pretreatment CT images from patients with stage III unresectable NSCLC were prognostic of PFS and OS to CRT followed by durvalumab IO and CRT alone.

CT Fractional Flow Reserve: A Practical Guide to Application, Interpretation, and Problem Solving

CT fractional flow reserve (FFR_CT) is a physiologic simulation technique that models coronary flow from routine coronary CT angiography (CTA). To evaluate lesion-specific ischemia, FFR_CT is measured 2 cm distal to a stenotic lesion. FFR_CT greater than 0.8 is normal, 0.76-0.8 is borderline, and 0.75 or less is abnormal. FFR_CT should always be interpreted in correlation with clinical and anatomic coronary CTA findings. FFR_CT increases the specificity of coronary CTA in the evaluation of coronary artery disease, decreases the prevalence of nonobstructive disease in invasive coronary angiography (ICA), and helps with revascularization decisions and planning. Patients with intermediate-risk coronary anatomy at CTA and abnormal FFR_CT can undergo ICA and revascularization, whereas those with normal FFR_CT can be safely deferred from ICA. In borderline FFR_CT values, management is decided in the context of the clinical scenario, but many cases could be safely managed with medical treatment. There are some limitations and pitfalls of FFR_CT. Abnormal FFR_CT values can be seen in mild stenosis, and normal FFR_CTvalues can be seen in severe stenosis. Gradually decreasing or abnormal low FFR_CT values at the distal vessel without a proximal focal lesion could be due to diffuse atherosclerosis. Coronary stents, bypass grafts, coronary anomalies, coronary dissection, transcatheter aortic valve replacement, unstable angina, and acute or recent myocardial infarction are situations in which FFR_CT has not been validated and should not be used at this time. The authors provide a practical guide to the applications and interpretation of FFR_CT, focusing on common pitfalls and challenges. Online supplemental material is available for this article. ^©RSNA, 2022.

First Clinical Photon-counting Detector CT System: Technical Evaluation

Background The first clinical CT system to use photon-counting-detector (PCD) technology has become available for patient care. Purpose To assess the technical performance of the PCD-CT system using phantoms and representative participant exams. Materials and Methods Institutional review board approval and written informed consent from four participants were obtained. Technical performance of a dual-source PCD-CT system was measured for standard and high resolution (HR) collimations. Noise power spectrum (NPS), modulation transfer function (MTF), section sensitivity profile (SSP), iodine CT number accuracy in virtual monoenergetic images (VMI), and iodine concentration accuracy were measured. Four participants were enrolled (between May 2021 and August 2021) in this prospective study and scanned using similar or lower radiation doses compared to same-day exams performed using energy-integrating-detector (EID) CT. Results All standard technical performance measures met accreditation requirements. Relative to filtered-back-projection reconstructions, images from iterative reconstruction had lower noise magnitude but preserved NPS shape and peak-frequency. Maximum in-plane spatial resolutions of 125 and 208 microns were measured for PCD-HR and PCD-standard scans, respectively. Minimum values for SSP full-width-half-maximum measurements were 0.34-mm (0.2 mm nominal section thickness) and 0.64 mm (0.4-mm nominal section thickness) for PCD-HR and PCD-standard scans, respectively. In a PCD-CT 120-kV standard scan of a 40-cm phantom, VMI iodine CT numbers had a mean percent error of 5.7% and iodine concentration had root-mean-squared-error of 0.5 mg/cc, comparable to previously reported values for EID-CT. VMI, iodine map, and virtual non-contrast images were created for a coronary CT angiogram acquired with 66-ms temporal resolution. Participant PCD-CT images showed up to 47% lower noise and/or improved spatial resolution compared to EID-CT. Conclusions Technical performance of a new clinical photon-counting-detector CT is improved relative to current state-of-the-art CT system. The dual-source photon-counting-detector geometry facilitated 66-ms-temporal-resolution multi-energy cardiac imaging. Study-participant images illustrated the impact of the improved technical performance.

Novel Non-Invasive Radiomic Signature on CT Scans Predicts Response to Platinum-Based Chemotherapy and Is Prognostic of Overall Survival in Small Cell Lung Cancer

BACKGROUND

Small cell lung cancer (SCLC) is an aggressive malignancy characterized by initial chemosensitivity followed by resistance and rapid progression. Presently, there are no predictive biomarkers that can accurately guide the use of systemic therapy in SCLC patients. This study explores the role of radiomic features from both within and around the tumor lesion on pretreatment CT scans to a) prognosticate overall survival (OS) and b) predict response to chemotherapy.

METHODS

One hundred fifty-three SCLC patients who had received chemotherapy were included. Lung tumors were contoured by an expert reader. The patients were divided randomly into approximately equally sized training (Str = 77) and test sets (Ste = 76). Textural descriptors were extracted from the nodule (intratumoral) and parenchymal regions surrounding the nodule (peritumoral). The clinical endpoints of this study were OS, progression-free survival (PFS), and best objective response to chemotherapy. Patients with complete or partial response were defined as "responders," and those with stable or progression of disease were defined as "non-responders." The radiomic risk score (RRS) was generated by using the least absolute shrinkage and selection operator (LASSO) with the Cox regression model. Patients were classified into the high-risk or low-risk groups based on the median of RRS. Association of the radiomic signature with OS was evaluated on Str and then tested on Ste. The features identified by LASSO were then used to train a linear discriminant analysis (LDA) classifier (MRad) to predict response to chemotherapy. A prognostic nomogram (NRad+Clin) was also developed on Str by combining clinical and prognostic radiomic features and validated on Ste. The Kaplan-Meier survival analysis and log-rank statistical tests were performed to assess the discriminative ability of the features. The discrimination performance of the NRad+Clin was assessed by Harrell's C-index. To estimate the clinical utility of the nomogram, decision curve analysis (DCA) was performed by calculating the net benefits for a range of threshold probabilities in predicting which high-risk patients should receive more aggressive treatment as compared with the low-risk patients.

RESULTS

A univariable Cox regression analysis indicated that RRS was significantly associated with OS in Str (HR: 1.53; 95% CI, [1.1-2.2; p = 0.021]; C-index = 0.72) and Ste (HR: 1.4, [1.1-1.82], p = 0.0127; C-index = 0.69). The RRS was also significantly associated with PFS in Str (HR: 1.89, [1.4-4.61], p = 0.047; C-index = 0.7) and Ste (HR: 1.641, [1.1-2.77], p = 0.04; C-index = 0.67). MRad was able to predict response to chemotherapy with an area under the receiver operating characteristic curve (AUC) of 0.76 ± 0.03 within Str and 0.72 within Ste. Predictors, including the RRS, gender, age, stage, and smoking status, were used in the prognostic nomogram. The discrimination ability of the NRad+Clin model on Str and Ste was C-index [95% CI]: 0.68 [0.66-0.71] and 0.67 [0.63-0.69], respectively. DCA indicated that the NRad+Clin model was clinically useful.

CONCLUSIONS

Radiomic features extracted within and around the lung tumor on CT images were both prognostic of OS and predictive of response to chemotherapy in SCLC patients.

Noninterpretive Uses of Artificial Intelligence in Radiology

We deem a computer to exhibit artificial intelligence (AI) when it performs a task that would normally require intelligent action by a human. Much of the recent excitement about AI in the medical literature has revolved around the ability of AI models to recognize anatomy and detect pathology on medical images, sometimes at the level of expert physicians. However, AI can also be used to solve a wide range of noninterpretive problems that are relevant to radiologists and their patients. This review summarizes some of the newer noninterpretive uses of AI in radiology.

Collaborative Writing Projects: Set Yourself up for Success

ABSTRACT

This article will review critical components for the successful completion of a multi-institution, multiauthor collaborative paper. Best practices for the creation and publication of a collaborative paper will be addressed.

CT for Pre- and Postprocedural Evaluation of Transcatheter Mitral Valve Replacement

Transcatheter mitral valve replacement (TMVR) is a catheter-based interventional technique for treating mitral valve disease in patients who are at high risk for open mitral valve surgery and with unfavorable anatomy for minimally invasive edge-to-edge transcatheter mitral valve repair. There are several TMVR devices with different anchoring mechanisms, delivered by either transapical or transseptal approaches. Transthoracic echocardiography is the first-line imaging modality used for characterization and quantification of mitral valve disorders. CT is complementary to echocardiography and has several advantages, including high isotropic spatial resolution, good temporal resolution, large field of view, multiplanar reconstruction capabilities, and rapid turnaround time. CT is essential for multiple aspects of preprocedural planning. Accurate and reproducible techniques to prescribe the mitral annulus at CT have been described from which important measurements such as the area, perimeter, trigone-trigone distance, intercommissural distance, and septolateral distance are obtained. The neo-left ventricular outflow tract (LVOT) can be simulated by placing a virtual prosthesis in the CT data to predict the risk of TMVR-induced LVOT obstruction. The anatomy of the landing zone and subvalvular apparatus as well as the relationship of the virtual device to adjacent structures such as the coronary sinus and left circumflex coronary artery can be evaluated. CT also stimulates procedural fluoroscopic angles. CT can be used to evaluate the chest wall for transapical access and the atrial septum for transseptal access. Follow-up CT is useful in identifying complications such as LVOT obstruction, paravalvular leak, pseudoaneurysm, and valve embolization. Online supplemental material is available for this article. ^©RSNA, 2020.

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement

Imaging-based measurements form the basis of surgical decision making in patients with aortic aneurysm. Unfortunately, manual measurement suffer from suboptimal temporal reproducibility, which can lead to delayed or unnecessary intervention. We tested the hypothesis that deep learning could improve upon the temporal reproducibility of CT angiography-derived thoracic aortic measurements in the setting of imperfect ground-truth training data. To this end, we trained a standard deep learning segmentation model from which measurements of aortic volume and diameter could be extracted. First, three blinded cardiothoracic radiologists visually confirmed non-inferiority of deep learning segmentation maps with respect to manual segmentation on a 50-patient hold-out test cohort, demonstrating a slight preference for the deep learning method (p < 1e-5). Next, reproducibility was assessed by evaluating measured change (coefficient of reproducibility and standard deviation) in volume and diameter values extracted from segmentation maps in patients for whom multiple scans were available and whose aortas had been deemed stable over time by visual assessment (n = 57 patients, 206 scans). Deep learning temporal reproducibility was superior for measures of both volume (p < 0.008) and diameter (p < 1e-5) and reproducibility metrics compared favorably with previously reported values of manual inter-rater variability. Our work motivates future efforts to apply deep learning to aortic evaluation.

Novel imaging biomarkers predict progression-free survival in stage 3 NSCLC treated with chemoradiation and durvalumab

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Background: The current management of stage III non-small cell lung cancer (NSCLC) is chemoradiation followed by durvalumab consolidation. There are no robust biomarkers that predict benefit from this regimen. We evaluated the utility of novel imaging biomarkers (radiomics) to distinguish patients with stage III NSCLC who will benefit from treatment from those likely to progress despite therapy. Methods: Patients with stage III NSCLC treated at our center with chemoradiation and durvalumab from July 2017 - July 2019 were identified. We collected patient clinical outcomes, subtype of NSCLC, and PD-L1 expression as well as pre-treatment CT images. Images were split into training and test sets. Lung tumors were contoured on 3D-Slicer software and 1542 radiomic features capturing both intra- and peritumoral texture patterns were extracted. The primary endpoint of this study was progression-free survival (PFS), and the secondary objective was difference in PFS within high PD-L1 (≥50%) and low PDL1 (<50%) groups. We used the least absolute shrinkage and selection operator (LASSO) Cox regression model to build the radiomic signature for PFS. A risk score was computed according to a linear combination of selected features and their corresponding coefficients. High- and low-risk groups were defined based on median radiomics risk score. Multivariable Cox regression analysis was performed to evaluate the effect of each factor on PFS. We performed Kaplan–Meier survival analysis and log-rank tests to assess prognostic ability of the features. Results: We identified 118 patients who fit our criteria with available CT images and randomly divided them into a training (n=59) and a test set (n=59). The radiomic risk score was calculated using a linear combination of the top six selected features with corresponding coefficients. In a multivariable analysis using clinicopathologic and radiomic signatures, the radiomics risk-score and PD-L1 expression were found to be significantly associated with PFS in training (risk-score: HR = 2.3, 95% CI: [1.46 – 3.63], P = 0.0003; PD-L1: HR = 0.31, 95% CI: [0.081 – 0.96], P = 0.038) and test sets (risk-score: HR= 2.56, 95% CI: [1.75 – 4], P = 8.7e-05; PD-L1: HR = 0.27, 95% CI: [0.048 – 0.58], P = 0.005). Kaplan-Meier analyses showed a significantly shorter PFS in the high-risk radiomics group versus the low-risk group (P < 0.0001). The radiomics risk scores were also predictive of significant differences in PFS within both the low (p=0.0005) and high (p=0.0007) PD-L1 groups. Conclusions: Radiomic biomarkers from pre-treatment CT images in stage III NSCLC patients were predictive of PFS to chemoradiation followed by durvalumab and could predict outcomes regardless of PD-L1 level. Pre-treatment radiomics may allow early prediction of benefit and expedite more aggressive treatment for high-risk patients. Additional validation of these imaging biomarkers is warranted.

ACR Appropriateness Criteria® Nonischemic Myocardial Disease with Clinical Manifestations (Ischemic Cardiomyopathy Already Excluded)

Nonischemic cardiomyopathies encompass a broad spectrum of myocardial disorders with mechanical or electrical dysfunction without evidence of ischemia. There are five broad variants of nonischemic cardiomyopathies; hypertrophic cardiomyopathy (Variant 1), restrictive or infiltrative cardiomyopathy (Variant 2), dilated or unclassified cardiomyopathy (Variant 3), arrhythmogenic cardiomyopathy (Variant 4), and inflammatory cardiomyopathy (Variant 5). For variants 1, 3, and 4, resting transthoracic echocardiography, MRI heart function and morphology without and with contrast, and MRI heart function and morphology without contrast are the usually appropriate imaging modalities. For variants 2 and 5, resting transthoracic echocardiography and MRI heart function and morphology without and with contrast are the usually appropriate imaging modalities. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Pre- and Postprocedural CT of Transcatheter Left Atrial Appendage Closure Devices

Transcatheter left atrial appendage (LAA) closure is an alternative to long-term anticoagulation therapy in selected patients with nonvalvular atrial fibrillation who have an increased risk for stroke. LAA closure devices can be implanted by means of either an endocardial or a combined endocardial and epicardial approach. Preprocedural imaging is key to identifying contraindications, accurately sizing the device, and minimizing complications. Transesophageal echocardiography (TEE) has been the reference standard imaging modality to assess the anatomy for LAA closure and to provide intraprocedural guidance. However, CT has emerged as a less-invasive alternative to TEE for pre- and postprocedural imaging. CT is comparable to TEE for exclusion of thrombus but is superior to TEE for the delineation of complex LAA anatomy, measurement for device sizing, and evaluation of pulmonary venous and extracardiac structures. CT provides accurate measurements of the LAA ostial diameter, landing zone diameter, and LAA length, which are vital for accurate sizing of the device. CT allows evaluation of the relationship with the pulmonary veins and other adjacent structures that can be injured during the procedure. CT also simulates procedural fluoroscopic angles and provides evaluation of the interatrial septum, which is punctured during LAA closure. CT also provides a more convenient method for the evaluation of postprocedural complications such as incomplete closure, peridevice leaking, device-related thrombus, and device dislodgement. Online supplemental material is available for this article. ^©RSNA, 2021.

Imaging Features of Complications after Coronary Interventions and Surgical Procedures

Coronary artery interventions and surgical procedures are used in the treatment of coronary artery disease and some congenital heart diseases. Cardiac and noncardiac complications can occur at variable times after these procedures, with the clinical presentation ranging from asymptomatic to devastating symptoms. Invasive coronary angiography is the reference standard modality used in the evaluation of coronary arteries, with intravascular US and optical coherence tomography providing high-resolution information regarding the vessel wall. CT is the mostly commonly used noninvasive imaging modality in the evaluation of coronary artery intervention complications and allows assessment of the stent, lumen of the stent, lumen of the coronary arteries, and extracoronary structures. MRI is limited to the evaluation of the proximal coronary arteries but allows comprehensive evaluation of the myocardium, including ischemia and infarction. The authors review the clinical symptoms and pathophysiologic and imaging features of various complications of coronary artery interventions and surgical procedures. Complications of percutaneous coronary interventions are discussed, including restenosis, thrombosis, dissection of coronary arteries or the aorta, coronary wall rupture or perforation, stent deployment failure, stent fracture, stent infection, stent migration or embolism, and reperfusion injury. Complications of several surgical procedures are reviewed, including coronary artery bypass grafting, coronary artery reimplantation procedure (for anomalous origin from opposite sinuses or the pulmonary artery or as part of surgical procedures such as arterial switching surgery and the Bentall and Cabrol procedures), coronary artery unroofing, and the Takeuchi procedure. Online supplemental material is available for this article. ^©RSNA, 2021.

The Role of Imaging in Health Screening: Screening for Specific Conditions

There are well-established and emerging screening examinations aimed at identifying malignant and nonmalignant conditions at early, treatable stages. The Radiology Research Alliance's "Role of Imaging in Health Screening" Task Force provides a comprehensive review of specific imaging-based screening examinations. This work reviews and serves as a reference for screening examinations for breast and colon cancer in a healthy population along with screening for lung cancer, hepatocellular carcinoma, and the use of whole body magnetic resonance imaging in at-risk individuals. American College of Radiology scoring systems, along with case-based examples, are included to illustrate the different disease entities. The future of screening is discussed, particularly in the context of artificial intelligence.

The RSNA International COVID-19 Open Radiology Database (RICORD)

The coronavirus disease 2019 (COVID-19) pandemic is a global health care emergency. Although reverse-transcription polymerase chain reaction testing is the reference standard method to identify patients with COVID-19 infection, chest radiography and CT play a vital role in the detection and management of these patients. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making. However, inadequate availability of a diverse annotated data set has limited the performance and generalizability of existing models. To address this unmet need, the RSNA and Society of Thoracic Radiology collaborated to develop the RSNA International COVID-19 Open Radiology Database (RICORD). This database is the first multi-institutional, multinational, expert-annotated COVID-19 imaging data set. It is made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. Pixel-level volumetric segmentation with clinical annotations was performed by thoracic radiology subspecialists for all COVID-19-positive thoracic CT scans. The labeling schema was coordinated with other international consensus panels and COVID-19 data annotation efforts, the European Society of Medical Imaging Informatics, the American College of Radiology, and the American Association of Physicists in Medicine. Study-level COVID-19 classification labels for chest radiographs were annotated by three radiologists, with majority vote adjudication by board-certified radiologists. RICORD consists of 240 thoracic CT scans and 1000 chest radiographs contributed from four international sites. It is anticipated that RICORD will ideally lead to prediction models that can demonstrate sustained performance across populations and health care systems.

The RSNA International COVID-19 Open Radiology Database (RICORD)

The coronavirus disease 2019 (COVID-19) pandemic is a global health care emergency. Although reverse-transcription polymerase chain reaction testing is the reference standard method to identify patients with COVID-19 infection, chest radiography and CT play a vital role in the detection and management of these patients. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making. However, inadequate availability of a diverse annotated data set has limited the performance and generalizability of existing models. To address this unmet need, the RSNA and Society of Thoracic Radiology collaborated to develop the RSNA International COVID-19 Open Radiology Database (RICORD). This database is the first multi-institutional, multinational, expert-annotated COVID-19 imaging data set. It is made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. Pixel-level volumetric segmentation with clinical annotations was performed by thoracic radiology subspecialists for all COVID-19-positive thoracic CT scans. The labeling schema was coordinated with other international consensus panels and COVID-19 data annotation efforts, the European Society of Medical Imaging Informatics, the American College of Radiology, and the American Association of Physicists in Medicine. Study-level COVID-19 classification labels for chest radiographs were annotated by three radiologists, with majority vote adjudication by board-certified radiologists. RICORD consists of 240 thoracic CT scans and 1000 chest radiographs contributed from four international sites. It is anticipated that RICORD will ideally lead to prediction models that can demonstrate sustained performance across populations and health care systems.

The Role of Imaging in Health Screening: Overview, Rationale of Screening, and Screening Economics

Imaging screening examinations are growing in their indications and volume to identify conditions at an early, treatable stage. The Radiology Research Alliance's 'Role of Imaging in Health Screening' Task Force provides a review of imaging-based screening rationale, economics, and describes established guidelines by various organizations. Various imaging modalities can be employed in screening, and are often chosen based on the specific pathology and patient characteristics. Prevalent disease processes with identifiable progression patterns that benefit from early potentially curative interventions are ideal for screening. Two such examples include colonic precancerous polyp progression to adenocarcinoma in colon cancer formation and atypical ductal hyperplasia progression to ductal carcinoma in situ and invasive ductal carcinoma in breast cancer. Economic factors in imaging-based screening are reviewed, including in the context of value-based reimbursements. Global differences in screening are outlined, along with the role of various organizational guidelines, including the American Cancer Society, the US Preventive Services Task Force, and the American College of Radiology.

Distinguishing granulomas from adenocarcinomas by integrating stable and discriminating radiomic features on non-contrast computed tomography scans

OBJECTIVE

To identify stable and discriminating radiomic features on non-contrast CT scans to develop more generalisable radiomic classifiers for distinguishing granulomas from adenocarcinomas.

METHODS

In total, 412 patients with adenocarcinomas and granulomas from three institutions were retrospectively included. Segmentations of the lung nodules were performed manually by an expert radiologist in a 2D axial view. Radiomic features were extracted from intra- and perinodular regions. A total of 145 patients were used as part of the training set (S_tr), whereas 205 patients were used as part of test set I (S_te¹) and 62 patients were used as part of independent test set II (S_te²). To mitigate the variation of CT acquisition parameters, we defined 'stable' radiomic features as those for which the feature expression remains relatively unchanged between different sites, as assessed using a Wilcoxon rank-sum test. These stable features were used to develop more generalisable radiomic classifiers that were more resilient to variations in lung CT scans. Features were ranked based on two criteria, firstly based on discriminability (i.e. maximising AUC) alone and subsequently based on maximising both feature stability and discriminability. Different machine-learning classifiers (Linear discriminant analysis, Quadratic discriminant analysis, Support vector machines and random forest) were trained with features selected using the two different criteria and then compared on the two independent test sets for distinguishing granulomas from adenocarcinomas, in terms of area under the receiver operating characteristic curve.

RESULTS

In the test sets, classifiers constructed using the criteria involving maximising feature stability and discriminability simultaneously achieved higher AUC compared with the discriminating alone criteria (S_te¹ [n = 205]: maximum AUCs of 0.85versus . 0.80; p-value = 0.047 and S_te² [n = 62]: maximum AUCs of 0.87 versus. 0.79; p-value = 0.021). These differences held for features extracted from scans with <3 mm slice thickness (AUC = 0.88 versus. 0.80; p-value = 0.039, n = 100) and for the ≥3 mm cases (AUC = 0.81 versus. 0.76; p-value = 0.034, n = 105). In both experiments, shape and peritumoural texture features had a higher stability compared with intratumoural texture features.

CONCLUSIONS

Our study suggests that explicitly accounting for both stability and discriminability results in more generalisable radiomic classifiers to distinguish adenocarcinomas from granulomas on non-contrast CT scans. Our results also showed that peritumoural texture and shape features were less affected by the scanner parameters compared with intratumoural texture features; however, they were also less discriminating compared with intratumoural features.

Recognizing and Minimizing Artifacts at Dual-Energy CT

Dual-energy CT (DECT) is an exciting innovation in CT technology with profound capabilities to improve diagnosis and add value to patient care. Significant advances in this technology over the past decade have improved our ability to successfully adopt DECT into the clinical routine. To enable effective use of DECT, one must be aware of the pitfalls and artifacts related to this technology. Understanding the underlying technical basis of artifacts and the strategies to mitigate them requires optimization of scan protocols and parameters. The ability of radiologists and technologists to anticipate their occurrence and provide recommendations for proper selection of patients, intravenous and oral contrast media, and scan acquisition parameters is key to obtaining good-quality DECT images. In addition, choosing appropriate reconstruction algorithms such as image kernel, postprocessing parameters, and appropriate display settings is critical for preventing quantitative and qualitative interpretive errors. Therefore, knowledge of the appearances of these artifacts is essential to prevent errors and allows maximization of the potential of DECT. In this review article, the authors aim to provide a comprehensive and practical overview of possible artifacts that may be encountered at DECT across all currently available commercial clinical platforms. They also provide a pictorial overview of the diagnostic pitfalls and outline strategies for mitigating or preventing the occurrence of artifacts, when possible. The broadening scope of DECT applications necessitates up-to-date familiarity with these technologies to realize their full diagnostic potential.

Multimodality Imaging of Transposition of the Great Arteries

Transposition of the great arteries (TGA) is a congenital conotruncal abnormality characterized by discordant connections between the ventricles and great arteries, with the aorta originating from the right ventricle (RV), and the pulmonary artery (PA) originating from the left ventricle (LV). The two main types of TGA are complete transposition or dextro-transposition of the great arteries (D-TGA), commonly referred to as d-loop, and congenitally corrected transposition (CCTGA), commonly referred to as l-loop or L-TGA. In D-TGA, the connections between the ventricles and atria are concordant, whereas in CCTGA they are discordant, with the left atrium connected to the RV, and the right atrium connected to the LV. D-TGA manifests during the neonatal period and can be surgically managed by atrial switch operation (AtrSO), arterial switch operation (ASO), Rastelli procedure, or Nikaidoh procedure. Arrhythmia, systemic ventricular dysfunction, baffle stenosis, and baffle leak are the common complications of AtrSO, whereas supravalvular pulmonary or branch PA stenosis, neoaortic dilatation, and coronary artery narrowing are the common complications of ASO. CCTGA may manifest late in life, even in adulthood. Surgeries for associated lesions such as tricuspid regurgitation, subpulmonic stenosis, and ventricular septal defect may be performed. A double-switch operation that includes both the atrial and arterial switch operations constitutes anatomic correction for CCTGA. Imaging plays an important role in the evaluation of TGA, both before and after surgery, for helping define the anatomy, quantify hemodynamics, and evaluate complications. Transthoracic echocardiography is the first-line imaging modality for presurgical planning in children with TGA. MRI provides comprehensive morphologic and functional information, particularly in adults after surgery. CT is performed when MRI is contraindicated or expected to generate artifacts. The authors review the imaging appearances of TGA, with a focus on pre- and postsurgical imaging. Online supplemental material is available for this article. ^©RSNA, 2021.

Bilateral meandering pulmonary vein complex and unusual associated cardiovascular anomalies and shunt: Extremely rare entity

Meandering pulmonary vein (MPV) is a rare entity that can be associated with an additional cardiac and pulmonary venous variations, including left-to-right shunts. Clinicians should consider further workup with dedicated cardiac imaging to evaluate for associated cardiovascular abnormalities after an abnormal pulmonary vein draining is initially identified on routine computed tomography or echocardiogram. Pulmonary venous variations in MPV represent a spectrum of disorders, and no consistent nomenclature has been established.

Dual-Energy CT Images: Pearls and Pitfalls

Dual-energy CT (DECT) is a tremendous innovation in CT technology that allows creation of numerous imaging datasets by enabling discrete acquisitions at more than one energy level. The wide range of images generated from a single DECT acquisition provides several benefits such as improved lesion detection and characterization, superior determination of material composition, reduction in the dose of iodine, and more robust quantification. Technological advances and the proliferation of various processing methods have led to the availability of diverse vendor-based DECT approaches, each with a different acquisition and image reconstruction process. The images generated from various DECT scanners differ from those from conventional single-energy CT because of differences in their acquisition techniques, material decomposition methods, image reconstruction algorithms, and postprocessing methods. DECT images such as virtual monochromatic images, material density images, and virtual unenhanced images have different imaging appearances, texture features, and quantitative capabilities. This heterogeneity creates challenges in their routine interpretation and has certain associated pitfalls. Some artifacts such as residual iodine on virtual unenhanced images and an appearance of pseudopneumatosis in a gas-distended bowel loop on material-density iodine images are specific to DECT, while others such as pseudoenhancement seen on virtual monochromatic images are also observed at single-energy CT. Recognizing the potential pitfalls associated with DECT is necessary for appropriate and accurate interpretation of the results of this increasingly important imaging tool. Online supplemental material is available for this article. ©RSNA, 2021.

Radiation doses and image quality of abdominal CT scans at different patient sizes using spectral detector CT scanner: a phantom and clinical study

PURPOSE

To compare radiation dose and image quality for abdominal CTs performed on a spectral detector CT (SDCT) and a comparable single-energy conventional CT scanner for patients of different sizes.

METHODS

Four semi-anthropomorphic phantoms were scanned on an SDCT (IQon, Philips Healthcare) and a comparable single-energy CT (iCT 256, Philips Healthcare) under matched scan parameters. Image noise and radiation dose were compared. For the HIPAA-compliant, IRB-approved retrospective cohort patient study, radiation dose was compared after adjusting for patient water equivalent diameter. Difference in subjective and objective image quality was assessed on a subset of 50 patients scanned on both scanners by two readers.

RESULTS

CTDIvol and noise from SDCT were higher than conventional CT for all phantoms, with a relative difference of 7.8% (range 5.3-14%) for radiation dose and average difference of 9.0% (range 5.5-11%) for noise. 718 SDCT and 937 conventional CT patients were included in the patient study. CTDIvol for SDCT patients tends to be lower for smaller patients (- 2%, 95% confidence interval (- 5%, - 0.2%) for 200 mm water equivalent diameter) and higher for larger patients compared to conventional CT (8%, (6%, 11%) for 400 mm). No difference was seen for subjective image quality, SNR, CNR, or image noise between the two scanners, except for higher image noise in the portal vein and higher signal in the aorta on SDCT.

CONCLUSION

Radiation dose for abdominal CT performed on SDCT is similar to the dose on a conventional CT for average size patients, lower for smaller patients, and slightly higher for larger patients. Image quality is similar between the two scanners.

A Comprehensive CT Radiation Dose Reduction and Protocol Standardization Program in a Complex, Tertiary Hospital System

PURPOSE

To present our experience in reducing CT radiation doses in a complex tertiary health system through CT protocol standardization and optimization.

METHODS

A CT radiation task force was created to reduce CT protocol heterogeneity and radiation doses. Redundant protocols were eliminated. By an iterative process, protocols with least radiation dose were identified. Radiation dose tracking software was used to store and analyze radiation doses. CT protocols were published in an intranet site after training of technologists. SOPs were established for maintaining and changing protocols. The radiation doses for each CT protocol before and after optimization were compared using geometric means.

RESULTS

A total of 222 CT protocols were reviewed, with elimination of 86 protocols. One-year follow-up showed homogeneous protocols with lower radiation doses. The improvement in radiation doses ranged from 23% to 58% (P< 0.001).

CONCLUSION

CT radiation dose reduction of up to 58% can be achieved by homogenizing and optimizing CT protocols through a comprehensive CT operations program.

Updates in Vascular Computed Tomography

Computed tomography angiography (CTA) has become a mainstay for the imaging of vascular diseases, because of high accuracy, availability, and rapid turnaround time. High-quality CTA images can now be routinely obtained with high isotropic spatial resolution and temporal resolution. Advances in CTA have focused on improving the image quality, increasing the acquisition speed, eliminating artifacts, and reducing the doses of radiation and iodinated contrast media. Dual-energy computed tomography provides material composition capabilities that can be used for characterizing lesions, optimizing contrast, decreasing artifact, and reducing radiation dose. Deep learning techniques can be used for classification, segmentation, quantification, and image enhancement.

Computed tomographic evaluation of myocardial ischemia

Myocardial ischemia is caused by a mismatch between myocardial oxygen consumption and oxygen delivery in coronary artery disease (CAD). Stratification and decision-making based on ischemia improves the prognosis in patients with CAD. Non-invasive tests used to evaluate myocardial ischemia include stress electrocardiography, echocardiography, single-photon emission computed tomography, and magnetic resonance imaging. Invasive fractional flow reserve is considered the reference standard for assessment of the hemodynamic significance of CAD. Computed tomography (CT) angiography has emerged as a first-line imaging modality for evaluation of CAD, particularly in the population at low to intermediate risk, because of its high negative predictive value; however, CT angiography does not provide information on the hemodynamic significance of stenosis, which lowers its specificity. Emerging techniques, e.g., CT perfusion and CT-fractional flow reserve, help to address this limitation of CT, by determining the hemodynamic significance of coronary artery stenosis. CT perfusion involves acquisition during the first pass of contrast medium through the myocardium following pharmacological stress. CT-fractional flow reserve uses computational fluid dynamics to model coronary flow, pressure, and resistance. In this article, we review these two functional CT techniques in the evaluation of myocardial ischemia, including their principles, technology, advantages, limitations, pitfalls, and the current evidence.

ACR Appropriateness Criteria® Chest Pain-Possible Acute Coronary Syndrome

Chest pain is a frequent cause for emergency department visits and inpatient evaluation, with particular concern for acute coronary syndrome as an etiology, since cardiovascular disease is the leading cause of death in the United States. Although history-based, electrocardiographic, and laboratory evaluations have shown promise in identifying coronary artery disease, early accurate diagnosis is paramount and there is an important role for imaging examinations to determine the presence and extent of anatomic coronary abnormality and ischemic physiology, to guide management with regard to optimal medical therapy or revascularization, and ultimately to thereby improve patient outcomes. A summary of the various methods for initial imaging evaluation of suspected acute coronary syndrome is outlined in this document. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

CAD-RADS: Pushing the Limits

Coronary CT angiography is now established as the first-line diagnostic imaging test to exclude coronary artery disease (CAD) in the population at low to intermediate risk. Wide variability exists in both the reporting of coronary CT angiography and the interpretation of these reports by referring physicians. The CAD Reporting and Data System (CAD-RADS) is sponsored by multiple societies and is a collaborative effort to provide standard classification of CAD, which is then integrated into patient clinical care. The main goals of the CAD-RADS are to decrease variability among readers; enhance communication between interpreting and referring clinicians, allowing collaborative determination of the best course of patient care; and generate consistent data for auditing, data mining, quality improvement, research, and education. There are several scenarios in which the CAD-RADS guidelines are ambiguous or do not provide definite recommendations for further management of CAD. The authors discuss the CAD-RADS categories and modifiers, highlight a variety of complex or ambiguous scenarios, and provide recommendations for managing these scenarios. Online supplemental material is available for this article. ^©RSNA, 2020 See discussion on this article by Aviram and Wolak.

Mediastinal hemangiomas: Spectrum of CT and MRI findings - retrospective case series study and systematic review of the literature

PURPOSE

To analyze the imaging manifestations of mediastinal hemangioma (MH) by CT and MRI to aid in its successful diagnosis and preoperative evaluation.

METHODS

Seventeen cases of MH diagnosed by histopathology combined with CT and MRI were retrospectively collected; and their CT and MRI features, including the lesions' site and range, shape, size, margin, density or signal, enhancement pattern, mass-cardiovascular interface, mass-pulmonary interface, and other characteristics were evaluated.

RESULTS

The anterior, middle, and posterior mediastinum were involved in 13, 13, and 8 cases, respectively. The masses size varied from 20 to 233 mm. Irregular, dumbbell-like, and oval masses were found in 13, 2, and 2 cases, respectively, while with pampiniform growth in 16 cases and expansive growth in 1 case. Mixed density, homogeneous density solid masses, and heterogeneous density masses with dominant fat were found in 9, 5, and 3 cases, respectively, showing mild or significant enhancement in aortic phase while no or mild enhancement in pulmonary artery phase. Draining veins were found in 16 cases and feeding arteries in 10 cases. Phleboliths were detected in 10 cases, splenic hemangiomas in 6 cases, and left lateral-chest-wall hemangioma in 1 case. In MRI sequences, mixed signal was found on T₁WI and heterogeneous hypersignal with nodular or linear hyposignal on T₂WI in 5 cases, mild or significant enhancement in 4 cases, draining veins in 2 cases, and no feeding arteries or phleboliths were seen.

CONCLUSION

Presence of phleboliths, pampiniform growth pattern, and aberrant draining veins are relatively specific characteristics in diagnosing MH.

Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study

OBJECTIVES

To evaluate whether combining stability and discriminability criteria in building radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small cell lung cancer on non-contrast computer tomography (CT).

MATERIALS AND METHODS

CT scans of 610 patients with early stage (IA, IB, IIA) NSCLC from four independent cohorts were evaluated. A total of 350 patients from Cleveland Clinic Foundation and University of Pennsylvania were divided into two equal sets for training (D₁) and validation set (D₂). 80 patients from The Cancer Genome Atlas Lung Adenocarcinoma and Squamous Cell Carcinoma and 195 patients from The Cancer Imaging Archive, were used as independent second (D₃) and third (D₄) validation sets. A linear discriminant analysis (LDA) classifier was built based on the most stable and discriminate features. In addition, a radiomic risk score (RRS) was generated by using least absolute shrinkage and selection operator, Cox regression model to predict time to progression (TTP) following surgery.

RESULTS

A feature selection strategy focusing on both feature discriminability and stability resulted in the classifier having a higher discriminability on validation datasets compared to the discriminability alone criteria in discriminating cancer recurrence (D₂, AUC of 0.75 vs. 0.65; D₃, 0.74 vs. 0.62; D₄, 0.76 vs. 0.63). The RRS generated by most stable-discriminating features was significantly associated with TTP compared to discriminating alone criteria (HR = 1.66, C-index of 0.72 vs. HR = 1.04, C-index of 0.62).

CONCLUSION

Accounting for both stability and discriminability yielded a more generalizable classifier for predicting cancer recurrence and TTP in early stage NSCLC.

CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction

BACKGROUND

Use of adjuvant chemotherapy in patients with early-stage lung cancer is controversial because no definite biomarker exists to identify patients who would receive added benefit from it. We aimed to develop and validate a quantitative radiomic risk score (QuRiS) and associated nomogram (QuRNom) for early-stage non-small cell lung cancer (NSCLC) that is prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy following surgery.

METHODS

We did a retrospective multicohort study of individuals with early-stage NSCLC (stage I and II) who either received surgery alone or surgery plus adjuvant chemotherapy. We selected patients for whom we had available pre-treatment diagnostic CT scans and corresponding survival information. We used radiomic texture features derived from within and outside the primary lung nodule on chest CT scans of patients from the Cleveland Clinic Foundation (Cleveland, OH, USA; cohort D₁) to develop QuRiS. A least absolute shrinkage and selection operator-Cox regularisation model was used for data dimension reduction, feature selection, and QuRiS construction. QuRiS was independently validated on a cohort of patients from the University of Pennsylvania (Philadephia, PA, USA; cohort D₂) and a cohort of patients whose CT scans were derived from The Cancer Imaging Archive (cohort D₃). QuRNom was constructed by integrating QuRiS with tumour and node descriptors (according to the tumour, node, metastasis staging system) and lymphovascular invasion. The primary endpoint of the study was the assessment of the performance of QuRiS and QuRNom in predicting disease-free survival. The added benefit of adjuvant chemotherapy estimated using QuRiS and QuRNom was validated by comparing patients who received adjuvant chemotherapy versus patients who underwent surgery alone in cohorts D₁-D₃.

FINDINGS

We included: 329 patients in cohort D₁ (73 [22%] had surgery plus adjuvant chemotherapy and 256 (78%) had surgery alone); 114 patients in cohort D₂ (33 [29%] had surgery plus adjuvant chemotherapy and 81 (71%) had surgery alone); and 82 patients in cohort D₃ (24 [29%] had surgery plus adjuvant chemotherapy and 58 (71%) had surgery alone). QuRiS comprised three intratumoral and 10 peritumoral CT-radiomic features and was found to be significantly associated with disease-free survival (ie, prognostic validation of QuRiS; hazard ratio for predicted high-risk vs predicted low-risk groups 1·56, 95% CI 1·08-2·23, p=0·016 for cohort D₁; 2·66, 1·24-5·68, p=0·011 for cohort D₂; and 2·67, 1·39-5·11, p=0·0029 for cohort D₃). To validate the predictive performance of QuRiS, patients were partitioned into three risk groups (high, intermediate, and low risk) on the basis of their corresponding QuRiS. Patients in the high-risk group were observed to have significantly longer survival with adjuvant chemotherapy than patients who underwent surgery alone (0·27, 0·08-0·95, p=0·042, for cohort D₁; 0·08, 0·01-0·42, p=0·0029, for cohorts D₂ and D₃ combined). As concerns QuRNom, the nomogram-estimated survival benefit was predictive of the actual efficacy of adjuvant chemotherapy (0·25, 0·12-0·55, p<0·0001, for cohort D₁; 0·13, <0·01-0·99, p=0·0019 for cohort D₃).

INTERPRETATION

QuRiS and QuRNom were validated as being prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy, especially in clinically defined low-risk groups. Since QuRiS is based on routine chest CT imaging, with additional multisite independent validation it could potentially be employed for decision management in non-invasive treatment of resectable lung cancer.

FUNDING

National Cancer Institute of the US National Institutes of Health, National Center for Research Resources, US Department of Veterans Affairs Biomedical Laboratory Research and Development Service, Department of Defence, National Institute of Diabetes and Digestive and Kidney Diseases, Wallace H Coulter Foundation, Case Western Reserve University, and Dana Foundation.

Ultra-low dose contrast CT pulmonary angiography in oncology patients using a high-pitch helical dual-source technology

PURPOSE

We aimed to determine if the image quality and vascular enhancement are preserved in computed tomography pulmonary angiography (CTPA) studies performed with ultra-low contrast and optimized radiation dose using high-pitch helical mode of a second generation dual source scanner.

METHODS

We retrospectively evaluated oncology patients who had CTPA on a 128-slice dual-source scanner, with a high-pitch helical mode (3.0), following injection of 30 mL of Ioversal at 4 mL/s with body mass index (BMI) dependent tube potential (80-120 kVp) and current (130-150 mAs). Attenuation, noise, and signal-to-noise ratio (SNR) were measured in multiple pulmonary arteries. Three independent readers graded the images on a 5-point Likert scale for central vascular enhancement (CVE), peripheral vascular enhancement (PVE), and overall quality.

RESULTS

There were 50 males and 101 females in our study. BMI ranged from 13 to 38 kg/m2 (22.8±4.4 kg/m2). Pulmonary embolism was present in 29 patients (18.9%). Contrast enhancement and SNR were excellent in all the pulmonary arteries (395.3±131.1 and 18.3±5.7, respectively). Image quality was considered excellent by all the readers, with average reader scores near the highest possible score of 5.0 (CVE, 4.83±0.48; PVE, 4.68±0.65; noise/quality, 4.78±0.47). The average radiation dose length product (DLP) was 161±60 mGy.cm.

CONCLUSION

Using a helical high-pitch acquisition technique, CTPA images of excellent diagnostic quality, including visualization of peripheral segmental/sub-segmental branches can be obtained using an ultra-low dose of iodinated contrast and low radiation dose.