Selective Use of CT Fractional Flow at a Large Academic Medical Center: Insights from Clinical Implementation after 1 Year of Practice.

Purpose This special report outlines a retrospective observational study of CT fractional flow reserve (CT-FFR) analysis using dual-source coronary CT angiography (CTA) scans performed without heart rate control and its impact on clinical outcomes. Materials and Methods All patients who underwent clinically indicated coronary CTA between August 2020 and August 2021 were included in this retrospective observational study. Scans were performed in the late systolic to early diastolic period without heart rate control and analyzed at the interpreting physician's discretion. Demographics, coronary CTA features, and rates of invasive coronary angiography (ICA), percutaneous coronary intervention (PCI), myocardial infarction, and all-cause death at 3 months were assessed by chart review. Results During the study period, 3098 patients underwent coronary CTA, of whom 113 with coronary bypass grafting were excluded. Of the remaining 2985 patients, 292 (9.7%) were referred for CT-FFR analysis. Two studies (0.7%) were rejected from CT-FFR analysis, and six (2.1%) analyses did not evaluate the lesion of concern. A total of 160 patients (56.3%) had CT-FFR greater than 0.80. Among patients with significant stenosis at coronary CTA, patients who underwent CT-FFR analysis presented with lower rates of ICA (74.5% vs 25.5%, P = .04) and PCI (78.9% vs 21.1%, P = .05). Conclusion CT-FFR was implemented in patients not requiring heart rate control by using dual-source coronary CTA acquisition and showed the potential to decrease rates of ICA and PCI without compromising safety in patients with significant stenosis and an average heart rate of 65 beats per minute. Keywords: Angiography, CT, CT-Angiography, Fractional Flow Reserve, Cardiac, Heart, Arteriosclerosis Supplemental material is available for this article. © RSNA, 2024.

Role of Computed Tomography in Cardiac Electrophysiology.

With the increasing prevalence of arrhythmias, the use of electrophysiology (EP) procedures has increased. Recent advancements in computed tomography (CT) technology have expanded its use in pre-assessments and post-assessments of EP procedures. CT provides high-resolution images, is noninvasive, and is widely available. This article highlights the strengths and weaknesses of cardiac CT in EP.

Does CT overestimate extra-pancreatic perineural invasion in patients with pancreatic ductal adenocarcinoma following neoadjuvant chemoradiation therapy?

OBJECTIVES: To evaluate the diagnostic performance of CT in the assessment of extra-pancreatic perineural invasion (EPNI) in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: This retrospective study included 123 patients (66 men; median age, 66 years) with PDAC who underwent radical surgery and pancreatic protocol CT for assessing surgical resectability between September 2011 and March 2019. Among the 123 patients, 97 patients had received neoadjuvant chemoradiation therapy (CRT). Two radiologists reviewed the CT images for evidence of EPNI using a 5-point scale (5 = definitely present, 4 = probably present, 3 = equivocally present, 2 = probably absent, and 1 = definitely absent). Diagnostic performance for assessing EPNI was evaluated with receiver operating characteristic (ROC) curve analysis. RESULTS: The sensitivity, specificity, and area under the ROC curve for assessing EPNI were 98%, 30%, and 0.62 in all patients; 97%, 22%, and 0.59 in patients with neoadjuvant CRT; and 100%, 100%, and 1.00 in patients without neoadjuvant CRT, respectively. False-positive assessment of EPNI occurred in 23% of patients (n = 28/123), and 100% of these (n = 28/28) had received neoadjuvant CRT. There was moderate to substantial agreement between the readers (ĸ = 0.49-0.62). CONCLUSION: Pancreatic protocol CT has better diagnostic performance for determination of EPNI in treatment naïve patients with PDAC and overestimation of EPNI is likely in patients who have received preoperative CRT. ADVANCES IN KNOWLEDGE: Pancreatic protocol CT has better diagnostic performance for the detection of EPNI in treatment naïve patients compared to patients receiving neoadjuvant CRT.

Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques.

OBJECTIVES: To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches. METHODS: Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NICPV:portal vein; NICAA:abdominal aorta; NICALL:overall iodine load) were compared between the three DECT scanners for each patient. A longitudinal mixed effects analysis was conducted to elucidate the effect of the scanner type, scan order, inter-scan time, and contrast media amount on normalized iodine concentration. RESULTS: Variability of IC was highest in the liver (dsDECT vs. dlDECT 28.96 (14.28-46.87) %, dsDECT vs. rsDECT 29.08 (16.59-62.55) %, rsDECT vs. dlDECT 22.85 (7.52-33.49) %), and lowest in the kidneys (dsDECT vs. dlDECT 15.76 (7.03-26.1) %, dsDECT vs. rsDECT 15.67 (8.86-25.56) %, rsDECT vs. dlDECT 10.92 (4.92-22.79) %). NICALL yielded the best reduction of IC variability throughout all tissues and inter-scanner comparisons, yet did not reduce the variability between dsDECT vs. dlDECT and rsDECT, respectively, in the liver. The scanner type remained a significant determinant for NICALL in the pancreas and the liver (F-values, 12.26 and 23.78; both, p < 0.0001). CONCLUSIONS: We found tissue-specific intra-patient variability of IC across different DECT scanner types. Normalization mitigated variability by reducing physiological fluctuations in iodine distribution. After normalization, the scanner type still had a significant effect on iodine variability in the pancreas and liver. CLINICAL RELEVANCE STATEMENT: Differences in iodine quantification between dual-energy CT scanners can partly be mitigated by normalization, yet remain relevant for specific tissues and inter-scanner comparisons, which should be taken into account at clinical routine imaging. KEY POINTS: • Iodine concentration showed the least variability between scanner types in the kidneys (range 10.92-15.76%) and highest variability in the liver (range 22.85-29.08%). • Normalizing tissue-specific iodine concentrations against the overall iodine load yielded the greatest reduction of variability between scanner types for 2/3 inter-scanner comparisons in the liver and for all (3/3) inter-scanner comparisons in the kidneys and pancreas, respectively. • However, even after normalization, the dual-energy CT scanner type was found to be the factor significantly influencing variability of iodine concentration in the liver and pancreas.

Diagnostic performance and feasibility of dual-layer detector dual-energy CT for characterization of urinary stones in patients of different sizes.

BACKGROUND: Urinary stones are frequently encountered in urology and are typically identified using non-contrast CT scans. Dual-energy CT (DECT) is a valuable imaging technique that produces material-specific images and allows for precise assessment of stone composition by estimating the effective atomic number (Zeff), a capability not achievable with the conventional single-energy CT's attenuation measurement method. PURPOSE: To investigate the diagnostic performance and image quality of dual-layer detector DECT (dlDECT) in characterizing urinary stones in patients of different sizes. METHODS: All consecutive dlDECT examinations with stone protocol and presence of urinary stones between July 2018 and November 2019 were retrospectively evaluated. Two radiologists independently reviewed 120 kVp and color-overlay Zeff images to determine stone composition (reference standard = crystallography) and image quality. The objective analysis included image noise and Zeff values measurement. RESULTS: A total of 739 urinary stones (median size 3.7 mm, range 1-35 mm) were identified on 177 CT examinations from 155 adults (mean age, 57 ± 15 years, 80 men, median weight 82.6 kg, range 42.6-186.9 kg). Using color-overlay Zeff images, the radiologists could subjectively interpret the composition in all stones ≥ 3 mm (n = 491). For stones with available reference standards (n = 74), dlDECT yielded a sensitivity of 80% (95%CI 44-98%) and a specificity of 98% (95%CI 92-100%) in visually discriminating uric acid from non-uric acid stones. Patients weighing > 90 kg and ≤ 90 kg had similar stone characterizability (p = 0.20), with 86% of stones characterized in the > 90 kg group and 87% in the ≤ 90 kg group. All examinations throughout various patients' weights revealed acceptable image quality. A Zeff cutoff of 7.66 accurately distinguished uric acid from non-uric acid stones (AUC = 1.00). Zeff analysis revealed AUCs of 0.78 and 0.91 for differentiating calcium-based stones from other non-uric stones and all stone types, respectively. CONCLUSION: dlDECT allowed accurate differentiation of uric acid and non-uric acid stones among patients with different body sizes with acceptable image quality. CLINICAL IMPACT: The ability to accurately differentiate uric acid stones from non-uric acid stones using color-overlay Zeff images allows for better tailored treatment strategies, helping to choose appropriate interventions and prevent potential complications related to urinary stones in patient care.

Optimal Abdominal CT Image Quality in Non-Lean Patients: Customization of CM Injection Protocols and Low-Energy Acquisitions.

We compared the image quality of abdominopelvic single-energy CT with 100 kVp (SECT-100 kVp) and dual-energy CT with 65 keV (DECT-65 keV) obtained with customized injection protocols to standard abdominopelvic CT scans (SECT-120 kVp) with fixed volumes of contrast media (CM). We retrospectively included 91 patients (mean age, 60.7 ± 15.8 years) with SECT-100 kVp and 83 (mean age, 60.3 ± 11.7 years) patients with DECT-65 keV in portovenous phase. Total body weight-based customized injection protocols were generated by a software using the following formula: patient weight (kg) × 0.40/contrast concentration (mgI/mL) × 1000. Patients had a prior abdominopelvic SECT-120 kVp with fixed injection. Iopamidol-370 was administered for all examinations. Quantitative and qualitative image quality comparisons were made between customized and fixed injection protocols. Compared to SECT-120 kVp, customized injection yielded a significant reduction in CM volume (mean difference = 9-12 mL; p ≤ 0.001) and injection rate (mean differences = 0.2-0.4 mL/s; p ≤ 0.001) in all weight categories. Improvements in attenuation, noise, signal-to-noise and contrast-to-noise ratios were observed for both SECT-100 kVp and DECT-65 keV compared to SECT-120 kVp in all weight categories (e.g., pancreas DECT-65 keV, 1.2-attenuation-fold increase vs. SECT-120 kVp; p < 0.001). Qualitative scores were ≥4 in 172 cases (98.8.4%) with customized injections and in all cases with fixed injections (100%). These findings suggest that customized CM injection protocols may substantially reduce iodine dose while yielding higher image quality in SECT-100 kVp and DECT-65 keV abdominopelvic scans compared to SECT-120 kVp using fixed CM volumes.

Can 1.25 mm thin-section images generated with Deep Learning Image Reconstruction technique replace standard-of-care 5 mm images in abdominal CT?

BACKGROUND: CT image reconstruction has evolved from filtered back projection to hybrid- and model-based iterative reconstruction. Deep learning-based image reconstruction is a relatively new technique that uses deep convolutional neural networks to improve image quality. OBJECTIVE: To evaluate and compare 1.25 mm thin-section abdominal CT images reconstructed with deep learning image reconstruction (DLIR) with 5 mm thick images reconstructed with adaptive statistical iterative reconstruction (ASIR-V). METHODS: This retrospective study included 52 patients (31 F; 56.9±16.9 years) who underwent abdominal CT scans between August-October 2019. Image reconstruction was performed to generate 5 mm images at 40% ASIR-V and 1.25 mm DLIR images at three strengths (low [DLIR-L], medium [DLIR-M], and high [DLIR-H]). Qualitative assessment was performed to determine image noise, contrast, visibility of small structures, sharpness, and artifact based on a 5-point-scale. Image preference determination was based on a 3-point-scale. Quantitative assessment included measurement of attenuation, image noise, and contrast-to-noise ratios (CNR). RESULTS: Thin-section images reconstructed with DLIR-M and DLIR-H yielded better image quality scores than 5 mm ASIR-V reconstructed images. Mean qualitative scores of DLIR-H for noise (1.77 ± 0.71), contrast (1.6 ± 0.68), small structure visibility (1.42 ± 0.66), sharpness (1.34 ± 0.55), and image preference (1.11 ± 0.34) were the best (p<0.05). DLIR-M yielded intermediate scores. All DLIR reconstructions showed superior ratings for artifacts compared to ASIR-V (p<0.05), whereas each DLIR group performed comparably (p>0.05, 0.405-0.763). In the quantitative assessment, there were no significant differences in attenuation values between all reconstructions (p>0.05). However, DLIR-H demonstrated the lowest noise (9.17 ± 3.11) and the highest CNR (CNRliver = 26.88 ± 6.54 and CNRportal vein = 7.92 ± 3.85) (all p<0.001). CONCLUSION: DLIR allows generation of thin-section (1.25 mm) abdominal CT images, which provide improved image quality with higher inter-reader agreement compared to 5 mm thick images reconstructed with ASIR-V. CLINICAL IMPACT: Improved image quality of thin-section CT images reconstructed with DLIR has several benefits in clinical practice, such as improved diagnostic performance without radiation dose penalties.

The why, who, how, and what of communicating CT radiation risks to patients and healthcare providers.

Computed tomography (CT) has witnessed tremendous growth in utilization. Despite its immense benefits, there is a growing concern from the general public and the medical community about the detrimental consequences of ionizing radiation from CT. Anxiety from the perceived risks associated with CT can deter referring physicians from ordering clinically indicated CT scans and patients from undergoing medically necessary exams. This article discusses various strategies for educating patients and healthcare providers on the benefits and risks of CT scanning and salient techniques for effective communication.

Multimodality Imaging in the Detection of Ischemic Heart Disease in Women.

Women with coronary artery disease tend to have a worse short and long-term prognosis relative to men and the incidence of atherosclerotic cardiovascular disease is increasing. Women are less likely to present with classic anginal symptoms when compared with men and more likely to be misdiagnosed. Several non-invasive imaging modalities are available for diagnosing ischemic heart disease in women and many of these modalities can also assist with prognostication and help to guide management. Selection of the optimal imaging modality to evaluate women with possible ischemic heart disease is a scenario which clinicians often encounter. Earlier modalities such as exercise treadmill testing demonstrate significant performance variation in men and women, while newer modalities such as coronary CT angiography, myocardial perfusion imaging and cardiac magnetic resonance imaging are highly specific and sensitive for the detection of ischemia and coronary artery disease with greater parity between sexes. Individual factors, availability, diagnostic performance, and female-specific considerations such as pregnancy status may influence the decision to select one modality over another. Emerging techniques such as strain rate imaging, CT-myocardial perfusion imaging and cardiac magnetic resonance imaging present additional options for diagnosing ischemia and coronary microvascular dysfunction.

Acute Deep Vein Thrombosis in a Cyclist With Iliac Vein Compression From Psoas Muscle Hypertrophy.

A 22-year-old avid cyclist presented with 1 month of right lower extremity pain and associated swelling. Subsequent imaging demonstrated an extensive acute deep vein thrombosis (DVT) in the setting of right iliac vein compression from psoas muscle hypertrophy. We present an unusual risk factor for DVT among cyclists. (Level of Difficulty: Intermediate.).

Comparison of Four Dual-Energy CT Scanner Technologies for Determining Renal Stone Composition: A Phantom Approach.

Background Studies have investigated the value of various dual-energy CT (DECT) technologies for determining renal stone composition. However, sparse multivendor comparison data exist. Purpose To compare the performance of four DECT technologies in determining renal stone composition at standard- and low-dose acquisitions. Materials and Methods This was an in vitro phantom study. Seventy-one urinary stones (size: 2.7-14.1 mm) of known chemical composition (51 calcium, four struvite, four cystine, and 12 urate) were placed in a custom-made cylindrical phantom. Consecutive scans with manufacturer-recommended protocols and dose-optimized institutional protocols (up to 80% reduction in volumetric CT dose index) were obtained with rapid kilovolt peak switching DECT (rsDECT) (n = 2), dual-source DECT (n = 2), twin-beam DECT (tbDECT) (n = 1), and dual-layer detector-based CT (dlDECT) (n = 1) scanners. The image data sets were analyzed using effective atomic number and dual-energy ratio indexes of maximally available and comparable spectra. The performance of each combination of scanner technology, method, and acquisition was assessed. Logistic regression models were used to calculate the area under the receiver operating characteristic curve (AUC). Results After image analysis, all scanners except tbDECT had an AUC greater than 0.95 in at least one acquisition in distinguishing urate from other stones. All DECT techniques were able to help differentiate calcium oxalate monohydrate stones with moderate accuracy (AUC: 0.70-0.83), and brushite was differentiated from urate with AUC greater than 0.99. There was no correlation between performance and acquisition with dose-optimized and/or vendor-recommended settings. Conclusion All four dual-energy CT (DECT) technologies enabled accurate determination of stone composition at standard- and low-dose acquisitions; however, performance varied based on the scanner parameters, DECT technique, and stone type. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Ringl and Apfaltrer in this issue.

Renal Lesion Characterization by Dual-Layer Dual-Energy CT: Comparison of Virtual and True Unenhanced Images.

BACKGROUND. Prior studies have provided mixed results for the ability to replace true unenhanced (TUE) images with virtual unenhanced (VUE) images when characterizing renal lesions by dual-energy CT (DECT). Detector-based dual-layer DECT (dlDECT) systems may optimize performance of VUE images for this purpose. OBJECTIVE. The purpose of this article was to compare dual-phase dlDECT examinations evaluated using VUE and TUE images in differentiating cystic and solid renal masses. METHODS. This retrospective study included 110 patients (mean age, 64.3 ± 11.8 years; 46 women, 64 men) who underwent renal-mass protocol dlDECT between July 2018 and February 2022. TUE, VUE, and nephrographic phase image sets were reconstructed. Lesions were diagnosed as solid masses by histopathology or MRI. Lesions were diagnosed as cysts by composite criteria reflecting findings from MRI, ultrasound, and the TUE and nephrographic phase images of the dlDECT examinations. One radiologist measured lesions' attenuation on all dlDECT image sets. Lesion characterization was compared between use of VUE and TUE images, including when considering enhancement of 20 HU or greater to indicate presence of a solid mass. RESULTS. The analysis included 219 lesions (33 solid masses; 186 cysts [132 simple, 20 septate, 34 hyperattenuating]). TUE and VUE attenuation were significantly different for solid masses (33.4 ± 7.1 HU vs 35.4 ± 8.6 HU, p = .002), simple cysts (10.8 ± 5.6 HU vs 7.1 ± 8.1 HU, p < .001), and hyperattenuating cysts (56.3 ± 21.0 HU vs 47.6 ± 16.3 HU, p < .001), but not septate cysts (13.6 ± 8.1 HU vs 14.0 ± 6.8 HU, p = .79). Frequency of enhancement 20 HU or greater when using TUE and VUE images was 90.9% and 90.9% in solid masses, 0.0% and 9.1% in simple cysts, 15.0% and 10.0% in septate cysts, and 11.8% and 38.2% in hyperattenuating cysts. All solid lesions were concordant in terms of enhancement 20 HU or greater when using TUE and VUE images. Twelve simple cysts and nine hyperattenuating cysts showed enhancement of 20 HU or greater when using VUE but not TUE images. CONCLUSION. Use of VUE images reliably detected enhancement in solid masses. However, VUE images underestimated attenuation of simple and hyperattenuating cysts, leading to false-positive findings of enhancement by such lesions. CLINICAL IMPACT. The findings do not support replacement of TUE acquisitions with VUE images when characterizing renal lesions by dlDECT.

Arterial involvement and resectability scoring system to predict R0 resection in patients with pancreatic ductal adenocarcinoma treated with neoadjuvant chemoradiation therapy.

OBJECTIVES: To derive a CT-based scoring system incorporating arterial involvement and resectability status to predict R0 resection in patients with pancreatic ductal adenocarcinoma (PDAC) undergoing neoadjuvant chemoradiation therapy (CRT). METHODS: This retrospective study included 112 patients with PDAC who underwent dynamic contrast-enhanced CT before and after neoadjuvant CRT. A 5-point score was used to determine arterial involvement (A score; 1 = no involvement, 2 = haziness, 3 = abutment, 4 = encasement, 5 = deformity) and 4-point score evaluating resectability status (R score; 1 = resectable, 2 = borderline resectable [BR] with venous involvement, 3 = BR with arterial involvement, 4 = locally advanced [LA]). A score before and after CRT were summed with R score before and after CRT to compute the AR score (ARtotal). The associations between ARtotal, R0 resection, overall survival (OS), and disease-free survival (DFS) were assessed. RESULTS: The ARtotal was associated with R0 resection (p < .001) and showed area under the ROC curve of 0.79 for differentiating R0 and R1 resections. Median OS was significantly lower for patients with ARtotal  > 9 (median: 35.2 months) compared to patients with ARtotal ≤ 9 (median: not estimable) (p < .001). Similar results were observed for DFS (median, 16.8 months in > 9 vs median, not estimable in ≤ 9; p < .001). CONCLUSIONS: A composite score which incorporates degree of arterial involvement and resectability status before and after neoadjuvant CRT is associated with R0 resection and discriminates between R0 and R1 resections in PDAC. KEY POINTS: • A scoring system incorporating arterial involvement and resectability status was associated with R0 resection. • ARtotal > 9 could predict patients' overall and disease-free survival.

A Method for Reducing Variability Across Dual-Energy CT Manufacturers in Quantification of Low Iodine Content Levels.

BACKGROUND. Clinical use of the dual-energy CT (DECT) iodine quantification technique is hindered by between-platform (i.e., across different manufacturers) variability in iodine concentration (IC) values, particularly at low iodine levels. OBJECTIVE. The purpose of this study was to develop in an anthropomorphic phantom a method for reducing between-platform variability in quantification of low iodine content levels using DECT and to evaluate the method's performance in patients undergoing serial clinical DECT examinations on different platforms. METHODS. An anthropomorphic phantom in three body sizes, incorporating varied lesion types and scanning conditions, was imaged with three distinct DECT implementations from different manufacturers at varying radiation exposures. A cross-platform iodine quantification model for correcting between-platform variability at low iodine content was developed using the phantom data. The model was tested in a retrospective series of 30 patients (20 men, 10 women; median age, 62 years) who each underwent three serial contrast-enhanced DECT examinations of the abdomen and pelvis (90 scans total) for routine oncology surveillance using the same three DECT platforms as in the phantom. Estimated accuracy of phantom IC values was summarized using root-mean-square error (RMSE) relative to known IC. Between-platform variability in patients was summarized using root-mean-square deviation (RMSD). RMSE and RMSD were compared between platform-based IC (ICPB) and cross-platform IC (ICCP). ICPB was normalized to aorta and portal vein. RESULTS. In the phantom study, mean RMSE of ICPB across platforms and other experimental conditions was 0.65 ± 0.18 mg I/mL compared with 0.40 ± 0.08 mg I/mL for ICCP (38% decrease in mean RMSE; p < .05). Intrapatient between-platform variability across serial DECT examinations was higher for ICPB than ICCP (RMSD, 97% vs 88%; p < .001). Between-platform variability was not reduced by normalization of ICPB to aorta (RMSD, 97% vs 101%; p = .12) or portal vein (RMSD, 97% vs 97%; p = .81). CONCLUSION. The developed cross-platform method significantly decreased between-platform variability occurring at low iodine content with platform-based DECT iodine quantification. CLINICAL IMPACT. With further validation, the cross-platform method, which has been implemented as a web-based app, may expand clinical use of DECT iodine quantification, yielding meaningful IC values that reflect tissue biologic viability or treatment response in patients who undergo serial examinations on different platforms.

Robustness of dual-energy CT-derived radiomic features across three different scanner types.

OBJECTIVES: To investigate the robustness of radiomic features between three dual-energy CT (DECT) systems. METHODS: An anthropomorphic body phantom was scanned on three different DECT scanners, a dual-source (dsDECT), a rapid kV-switching (rsDECT), and a dual-layer detector DECT (dlDECT). Twenty-four patients who underwent abdominal DECT examinations on each of the scanner types during clinical follow-up were retrospectively included (n = 72 examinations). Radiomic features were extracted after standardized image processing, following ROI placement in phantom tissues and healthy appearing hepatic, splenic and muscular tissue of patients using virtual monoenergetic images at 65 keV (VMI65keV) and virtual unenhanced images (VUE). In total, 774 radiomic features were extracted including 86 original features and 8 wavelet transformations hereof. Concordance correlation coefficients (CCC) and analysis of variances (ANOVA) were calculated to determine inter-scanner robustness of radiomic features with a CCC of ≥ 0.9 deeming a feature robust. RESULTS: None of the phantom-derived features attained the threshold for high feature robustness for any inter-scanner comparison. The proportion of robust features obtained from patients scanned on all three scanners was low both in VMI65keV (dsDECT vs. rsDECT:16.1% (125/774), dlDECT vs. rsDECT:2.5% (19/774), dsDECT vs. dlDECT:2.6% (20/774)) and VUE (dsDECT vs. rsDECT:11.1% (86/774), dlDECT vs. rsDECT:2.8% (22/774), dsDECT vs. dlDECT:2.7% (21/774)). The proportion of features without significant differences as per ANOVA was higher both in patients (51.4-71.1%) and in the phantom (60.6-73.4%). CONCLUSIONS: The robustness of radiomic features across different DECT scanners in patients was low and the few robust patient-derived features were not reflected in the phantom experiment. Future efforts should aim to improve the cross-platform generalizability of DECT-derived radiomics. KEY POINTS: • Inter-scanner robustness of dual-energy CT-derived radiomic features was on a low level in patients who underwent clinical examinations on three DECT platforms. • The few robust patient-derived features were not confirmed in our phantom experiment. • Limited inter-scanner robustness of dual-energy CT derived radiomic features may impact the generalizability of models built with features from one particular dual-energy CT scanner type.

Virtual Unenhanced Images: Qualitative and Quantitative Comparison Between Different Dual-Energy CT Scanners in a Patient and Phantom Study.

MATERIALS AND METHODS: Forty-four patients with clinical contrast-enhanced abdominal examinations on each of the 3 DECT scanner types and a phantom scanned with the same protocols were included in this retrospective study. Qualitative and quantitative assessment was performed on VUE images. Quantitative evaluation included measurement of attenuation and image noise for various tissues and the phantom. Virtual unenhanced image attenuation and noise were compared between scanner types, and intrapatient interscanner reproducibility of virtual unenhanced image attenuation was calculated as the percentage of measurement pairs with an interscanner difference ≤ 10 HU. Image quality, noise, sharpness, and iodine elimination were assessed qualitatively by 2 radiologists. RESULTS: Significant interscanner differences in VUE attenuation and noise were found in all tissues. dlDECT and rsDECT showed significantly higher VUE attenuation than dsDECT in the aorta, portal vein, and kidneys (P < 0.05). Conversely, VUE attenuation in dsDECT was significantly higher than in dlDECT/rsDECT for subcutaneous and retroperitoneal fat (both P < 0.05). A total of 91.9% (385/419) of measurements were reproducible between rsDECT and dlDECT, 70.9% (297/419) between dsDECT and rsDECT, and 66.8% (280/419) between dsDECT and dlDECT. Virtual unenhanced image attenuation in the contrast media-filled phantom cavity was 12.7 ± 4.7 HU in dlDECT, -5.3 ± 4.2 HU in rsDECT, and -4.0 ± 10.7 HU in dsDECT with significant differences between dlDECT and rsDECT/dsDECT, respectively (P < 0.05), between which attenuation was comparable in the unenhanced extraluminal phantom component (P = 0.11-0.62). Qualitatively, dsDECT yielded best iodine elimination, whereas sharpness, image noise, and overall image quality were rated higher in dlDECT and rsDECT. CONCLUSIONS: There are significant interscanner differences in the attenuation measurements and qualitative assessment of VUE images, which should be acknowledged when using these images in patients that are being scanned on different DECT scanner types during imaging follow-up.

Attenuation values on virtual unenhanced images obtained with detector-based dual-energy computed tomography: observations on single- and split-bolus contrast protocols.

PURPOSE: To compare virtual unenhanced (VUE) attenuation values and their agreement with true unenhanced (TUE) images in patients who underwent dual-layer detector-based dual-energy computed tomography (dlDECT) with single- vs. split-bolus contrast media protocol. METHODS: In this HIPAA-compliant, IRB-approved retrospective analysis, a total of 105 patients who underwent nephrographic phase (NP) dlDECT between 07/2018 and 11/2019 were included: 55 patients received single bolus and 50 patients split-bolus examinations. Both scan protocols comprised a TUE and 120-kVp NP acquisition from which VUE images were reconstructed. A radiologist performed ROI-based attenuation measurements of liver parenchyma, main portal vein, aorta, spleen, renal parenchyma, and pelvis on TUE and VUE images. Agreement between TUE and VUE images was determined and compared for both protocols and each anatomic region. RESULTS: VUE attenuation was significantly higher than TUE attenuation in both cohorts in the liver, portal vein, spleen, and renal parenchyma (p < 0.05), while it was similar in the abdominal aorta in both cohorts (p = 0.05, 0.7522, respectively). VUE attenuation was significantly higher than TUE attenuation in the renal pelvis of the split-bolus cohort (p < 0.05). When comparing VUE images between single- and split-bolus protocols, the renal parenchyma yielded a significantly higher VUE attenuation in the single-bolus cohort (single bolus: 38.8 ± 3.3 HU vs. split bolus: 36.8 ± 3.6 HU; p < 0.05), whereas the split-bolus cohort revealed markedly higher VUE attenuation in the renal pelvis (single bolus: 2.3 ± 10.8 HU vs. split bolus: 92.3 ± 76.8; p < 0.05). Mean intra-patient differences between TUE and VUE images were comparable between single- and split-bolus cohorts (p-range 0.09-0.35) except for the renal parenchyma and pelvis: in the first, the single-bolus cohort yielded a higher VUE attenuation, while in the second, attenuation was significantly higher in the split-bolus cohort (p < 0.05). CONCLUSION: VUE attenuation overestimated TUE attenuation and differed between split- and single-bolus protocols for the renal parenchyma and pelvis, while all other tissues showed comparable VUE attenuation.

Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysis.

OBJECTIVES: There are individual variations in neo-adjuvant chemoradiation therapy (nCRT) in patients with locally advanced rectal cancer (LARC). No reliable modality currently exists that can predict the efficacy of nCRT. The purpose of this study is to assess if CT-based fractal dimension and filtration-histogram texture analysis can predict therapeutic response to nCRT in patients with LARC. METHODS: In this retrospective study, 215 patients (average age: 57 years (18-87 years)) who received nCRT for LARC between June 2005 and December 2016 and underwent a staging diagnostic portal venous phase CT were identified. The patients were randomly divided into two datasets: a training set (n = 170), and a validation set (n = 45). Tumor heterogeneity was assessed on the CT images using fractal dimension (FD) and filtration-histogram texture analysis. In the training set, the patients with pCR and non-pCR were compared in univariate analysis. Logistic regression analysis was applied to identify the predictive value of efficacy of nCRT and receiver operating characteristic analysis determined optimal cutoff value. Subsequently, the most significant parameter was assessed in the validation set. RESULTS: Out of the 215 patients evaluated, pCR was reached in 20.9% (n = 45/215) patients. In the training set, 7 out of 37 texture parameters showed significant difference comparing between the pCR and non-pCR groups and logistic multivariable regression analysis incorporating clinical and 7 texture parameters showed that only FD was associated with pCR (p = 0.001). The area under the curve of FD was 0.76. In the validation set, we applied FD for predicting pCR and sensitivity, specificity, and accuracy were 60%, 89%, and 82%, respectively. CONCLUSION: FD on pretreatment CT is a promising parameter for predicting pCR to nCRT in patients with LARC and could be used to help make treatment decisions. KEY POINTS: • Fractal dimension analysis on pretreatment CT was associated with response to neo-adjuvant chemoradiation in patients with locally advanced rectal cancer. • Fractal dimension is a promising biomarker for predicting pCR to nCRT and may potentially select patients for individualized therapy.