Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses.

ABSTRACT: Neuroendocrine neoplasms are a heterogeneous group of gastrointestinal and lung tumors. Their diverse clinical manifestations, variable locations, and heterogeneity present notable diagnostic challenges. This article delves into the imaging modalities vital for their detection and characterization. Computed tomography is essential for initial assessment and staging. At the same time, magnetic resonance imaging (MRI) is particularly adept for liver, pancreatic, osseous, and rectal imaging, offering superior soft tissue contrast. The article also highlights the limitations of these imaging techniques, such as MRI's inability to effectively evaluate the cortical bone and the questioned cost-effectiveness of computed tomography and MRI for detecting specific gastric lesions. By emphasizing the strengths and weaknesses of these imaging techniques, the review offers insights into optimizing their utilization for improved diagnosis, staging, and therapeutic management of neuroendocrine neoplasms.

Pancreatic cancer detection with dual-energy CT: diagnostic performance of 40 keV and 70 keV virtual monoenergetic images.

PURPOSE: To compare the diagnostic performance of 40 keV and 70 keV virtual monoenergetic images (VMIs) generated from dual-energy CT in the detection of pancreatic cancer. METHODS: This retrospective study included patients who underwent pancreatic protocol dual-energy CT from January 2019 to August 2022. Four radiologists (1-11 years of experience), who were blinded to the final diagnosis, independently and randomly interpreted 40 keV and 70 keV VMIs and graded the presence or absence of pancreatic cancer. For each image set (40 keV and 70 keV VMIs), the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. The diagnostic performance of each image set was compared using generalized estimating equations. RESULTS: Overall, 137 patients (median age, 71 years; interquartile range, 63-78 years; 77 men) were included. Among them, 62 patients (45%) had pathologically proven pancreatic cancer. The 40 keV VMIs had higher specificity (75% vs. 67%; P < .001), PPV (76% vs. 71%; P < .001), and accuracy (85% vs. 81%; P = .001) than the 70 keV VMIs. On the contrary, 40 keV VMIs had lower sensitivity (96% vs. 98%; P = .02) and NPV (96% vs. 98%; P = .004) than 70 keV VMIs. However, the diagnostic confidence in patients with (P < .001) and without (P = .001) pancreatic cancer was improved in 40 keV VMIs than in 70 keV VMIs. CONCLUSIONS: The 40 keV VMIs showed better diagnostic performance in diagnosing pancreatic cancer than the 70 keV VMIs, along with higher reader confidence.

Determination of arterial invasion in pancreatic ductal adenocarcinoma: what is the best diagnostic criterion on CT?

OBJECTIVES: To investigate the diagnostic performance and interobserver variability in the determination of arterial invasion in pancreatic ductal adenocarcinoma (PDAC) and determine the best CT imaging criterion. METHODS: We retrospectively evaluated 128 patients with PDAC (73 men and 55 women) who underwent preoperative contrast-enhanced CT. Five board-certified radiologists (expert) and four fellows (non-expert]) independently assessed the arterial invasion (celiac, superior mesenteric, splenic, and common hepatic arteries) using a 6-point score: 1, no tumor contact; 2, hazy attenuation ≤ 180°; 3, hazy attenuation > 180°; 4, solid soft tissue contact ≤ 180°; 5, solid soft tissue contact > 180°; and 6, contour irregularity. ROC analysis was performed to evaluate the diagnostic performance and determine the best diagnostic criterion for arterial invasion, with pathological or surgical findings as references. Interobserver variability was assessed using Fleiss's ĸ statistics. RESULTS: Among the 128 patients, 35.2% (n = 45/128) received neoadjuvant treatment (NTx). Solid soft tissue contact ≤ 180° was the best diagnostic criterion for arterial invasion as defined by the Youden Index both in patients who did and did not receive NTx (sensitivity, 100% vs. 100%; specificity, 90% vs. 93%; and AUC, 0.96 vs. 0.98, respectively). Interobserver variability among the non-expert was not inferior to that among the expert (ĸ = 0.61 vs 0.61; p = .39 and ĸ = 0.59 vs 0.51; p < .001 in patients treated with and without NTx, respectively). CONCLUSIONS: Solid soft tissue contact ≤ 180° was the best diagnostic criterion for the determination of arterial invasion in PDAC. Considerable interobserver variability was seen among the radiologists. KEY POINTS: • Solid soft tissue contact ≤ 180° was the best diagnostic criterion for the determination of arterial invasion in pancreatic ductal adenocarcinoma. • Interobserver agreement among non-expert radiologists was almost comparable to that among expert radiologists.

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.

Prediction of overall survival in patients with pancreatic ductal adenocarcinoma: histogram analysis of ADC value and correlation with pathological intratumoral necrosis.

BACKGROUND: To evaluate the utility of histogram analysis (HA) of apparent diffusion coefficient (ADC) values to predict the overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDAC) and to correlate with pathologically evaluated massive intratumoral necrosis (MITN). MATERIALS AND METHODS: Thirty-nine patients were included in this retrospective study with surgically resected PDAC who underwent preoperative magnetic resonance imaging. Twelve patients received neoadjuvant chemotherapy. HA on the ADC maps were performed to obtain the tumor HA parameters. Using Cox proportional regression analysis adjusted for age, time-dependent receiver-operating-characteristic (ROC) curve analysis, and Kaplan-Meier estimation, we evaluated the association between HA parameters and OS. The association between prognostic factors and pathologically confirmed MITN was assessed by logistic regression analysis. RESULTS: The median OS was 19.9 months. The kurtosis (P < 0.001), entropy (P = 0.013), and energy (P = 0.04) were significantly associated with OS. The kurtosis had the highest area under the ROC curve (AUC) for predicting 3-year survival (AUC 0.824) among these three parameters. Between the kurtosis and MITN, the logistic regression model revealed a positive correlation (P = 0.045). Lower survival rates occurred in patients with high kurtosis (cutoff value > 2.45) than those with low kurtosis (≤ 2.45) (P < 0.001: 1-year survival rate, 75.2% versus 100%: 3-year survival rate, 14.7% versus 100%). CONCLUSIONS: HA derived kurtosis obtained from tumor ADC maps might be a potential imaging biomarker for predicting the presence of MITN and OS in patients with PDAC.

Optimized Bolus Threshold for Dual-Energy CT Angiography with Monoenergetic Images: A Randomized Clinical Trial.

Background The bolus-tracking technique from single-energy CT has been applied to dual-energy CT (DECT) without optimization or validation. Further optimization is imperative because of a paucity of literature and differences in the attenuation profile of virtual monoenergetic images (VMIs). Purpose To determine the optimal trigger threshold with bolus-tracking technique for DECT angiography (DECTA) in a phantom study and assess the feasibility of an optimized threshold for bolus-tracking technique in DECTA at 40 keV with a 50% reduced iodine dose in human participants. Materials and Methods A phantom study with rapid kilovoltage-switching DECT was performed to determine the optimal threshold for each kiloelectron-volt VMI. In a prospective study, consecutive participants who underwent whole-body CT angiography (CTA) from August 2018 to July 2019 were randomized into three groups: single-energy CTA (SECTA) with standard iodine dose (600 mg of iodine per kilogram), DECTA with 50% reduced iodine dose (300 mg of iodine per kilogram) by using a conventional threshold, and DECTA with 300 mg of iodine per kilogram by using an optimized threshold. A trigger threshold of 100 HU at 120 kVp was used as a reference for comparison. Injected iodine doses and aortic CT numbers were compared among the three groups using Kruskal-Wallis test. Results Ninety-six participants (mean age ± standard deviation, 72 years ± 9; 80 men) were evaluated (32 participants in each group). The optimized threshold for VMIs at 40 keV was 30 HU. The median iodine dose was lower in the optimized DECTA group (13 g) compared with conventional DECTA (19 g) and SECTA (26 g) groups (P < .017 for each comparison). The median aortic CT numbers were higher in the order corresponding to conventional DECTA (655-769 HU), optimized DECTA (543-610 HU), and SECTA (343-359 HU) groups (P < .001). Conclusion The optimized trigger threshold of 30 HU for bolus-tracking technique during dual-energy CT angiography at 40 keV achieved lower iodine load while maintaining aortic enhancement. ©RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Malayeri in this issue.

Sinogram-based deep learning image reconstruction technique in abdominal CT: image quality considerations.

OBJECTIVES: To investigate the image quality and perception of a sinogram-based deep learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared to standard-of-care strength of ASIR-V. METHODS: In this retrospective study, 50 patients (62% F; 56.74 ± 17.05 years) underwent portal venous phase. Four reconstructions (ASIR-V at 40%, and DLIR at three strengths: low (DLIR-L), medium (DLIR-M), and high (DLIR-H)) were generated. Qualitative and quantitative image quality analysis was performed on the 200 image datasets. Qualitative scores were obtained for image noise, contrast, small structure visibility, sharpness, and artifact by three blinded radiologists on a 5-point scale (1, excellent; 5, very poor). Radiologists also indicated image preference on a 3-point scale (1, most preferred; 3, least preferred). Quantitative assessment was performed by measuring image noise and contrast-to-noise ratio (CNR). RESULTS: DLIR had better image quality scores compared to ASIR-V. Scores on DLIR-H for noise (1.40 ± 0.53), contrast (1.41 ± 0.55), small structure visibility (1.51 ± 0.61), and sharpness (1.60 ± 0.54) were the best (p < 0.05) followed by DLIR-M (1.85 ± 0.52, 1.66 ± 0.57, 1.69 ± 0.59, 1.68 ± 0.46), DLIR-L (2.29 ± 0.58, 1.96 ± 0.61, 1.90 ± 0.65, 1.86 ± 0.46), and ASIR-V (2.86 ± 0.67, 2.55 ± 0.58, 2.34 ± 0.66, 2.01 ± 0.36). Ratings for artifacts were similar for all reconstructions (p > 0.05). DLIRs did not influence subjective textural perceptions and were preferred over ASIR-V from the beginning. All DLIRs had a higher CNR (26.38-102.30%) and lower noise (20.64-48.77%) than ASIR-V. DLIR-H had the best objective scores. CONCLUSION: Sinogram-based deep learning image reconstructions were preferred over iterative reconstruction subjectively and objectively due to improved image quality and lower noise, even in large patients. Use in clinical routine may allow for radiation dose reduction. KEY POINTS: • Deep learning image reconstructions (DLIRs) have a higher contrast-to-noise ratio compared to medium-strength hybrid iterative reconstruction techniques. • DLIR may be advantageous in patients with large body habitus due to a lower image noise. • DLIR can enable further optimization of radiation doses used in abdominal CT.

Clinical Implementation of Dual-Energy CT for Gastrointestinal Imaging.

Dual-energy CT (DECT) overcomes several limitations of conventional single-energy CT (SECT) for the evaluation of gastrointestinal diseases. This article provides an overview of practical aspects of the DECT technology and acquisition protocols, reviews existing clinical applications, discusses current challenges, and describes future directions, with a focus on gastrointestinal imaging. A head-to-head comparison of technical specifications among DECT scanner implementations is provided. Energy- and material-specific DECT image reconstructions enable retrospective (i.e., after examination acquisition) image quality adjustments that are not possible using SECT. Such adjustments may, for example, correct insufficient contrast bolus or metal artifacts, thereby potentially avoiding patient recalls. A combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can be included in protocols to improve lesion detection and disease characterization. Relevant literature is reviewed regarding use of DECT for evaluation of the liver, gallbladder, pancreas, and bowel. Challenges involving cost, workflow, body habitus, and variability in DECT measurements are considered. Artificial intelligence and machine-learning image reconstruction algorithms, PACS integration, photon-counting hardware, and novel contrast agents are expected to expand the multienergy capability of DECT and further augment its value.

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.

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.

Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT.

OBJECTIVE. The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterative reconstruction (IR) images of submillisievert chest and abdominopelvic CT. MATERIALS AND METHODS. Our prospective multiinstitutional study included 59 adult patients (33 women, 26 men; mean age ± SD, 65 ± 12 years old; mean body mass index [weight in kilograms divided by the square of height in meters] = 27 ± 5) who underwent routine chest (n = 22; 16 women, six men) and abdominopelvic (n = 37; 17 women, 20 men) CT on a 640-MDCT scanner (Aquilion ONE, Canon Medical Systems). All patients gave written informed consent for the acquisition of low-dose (LD) CT (LDCT) after a clinically indicated standard-dose (SD) CT (SDCT). The SDCT series (120 kVp, 164-644 mA) were reconstructed with interactive reconstruction (IR) (adaptive iterative dose reduction [AIDR] 3D, Canon Medical Systems), and the LDCT (100 kVp, 120 kVp; 30-50 mA) were reconstructed with filtered back-projection (FBP), IR (AIDR 3D and forward-projected model-based iterative reconstruction solution [FIRST], Canon Medical Systems), and deep learning reconstruction (DLR) (Advanced Intelligent Clear-IQ Engine [AiCE], Canon Medical Systems). Four subspecialty-trained radiologists first read all LD image sets and then compared them side-by-side with SD AIDR 3D images in an independent, randomized, and blinded fashion. Subspecialty radiologists assessed image quality of LDCT images on a 3-point scale (1 = unacceptable, 2 = suboptimal, 3 = optimal). Descriptive statistics were obtained, and the Wilcoxon sign rank test was performed. RESULTS. Mean volume CT dose index and dose-length product for LDCT (2.1 ± 0.8 mGy, 49 ± 13mGy·cm) were lower than those for SDCT (13 ± 4.4 mGy, 567 ± 249 mGy·cm) (p < 0.0001). All 31 clinically significant abdominal lesions were seen on SD AIDR 3D and LD DLR images. Twenty-five, 18, and seven lesions were detected on LD AIDR 3D, LD FIRST, and LD FBP images, respectively. All 39 pulmonary nodules detected on SD AIDR 3D images were also noted on LD DLR images. LD DLR images were deemed acceptable for interpretation in 97% (35/37) of abdominal and 95-100% (21-22/22) of chest LDCT studies (p = 0.2-0.99). The LD FIRST, LD AIDR 3D, and LD FBP images had inferior image quality compared with SD AIDR 3D images (p < 0.0001). CONCLUSION. At submillisievert chest and abdominopelvic CT doses, DLR enables image quality and lesion detection superior to commercial IR and FBP images.

Update on Multienergy CT: Physics, Principles, and Applications.

Multienergy CT involves acquisition of two or more CT measurements with distinct energy spectra. Using the differential attenuation of tissues and materials at different x-ray energies, multienergy CT allows distinction of tissues and materials beyond that possible with conventional CT. Multienergy CT technologies can operate at the source or detector level. Dual-source, rapid tube-voltage switching, and dual-layer detector CT are the most commonly used multienergy CT technologies. Most of the currently available technologies typically use two energy levels, commonly referred to as dual-energy CT. With use of two or more energy bins, photon-counting detector CT can perform multienergy CT beyond current dual-energy CT technologies. Multienergy CT postprocessing can be performed in the projection or image domain using two-material or multimaterial decomposition. The most commonly used multienergy CT images are virtual monoenergetic images (VMIs), iodine maps, virtual noncontrast (VNC) images, and uric acid images. Low-energy VMIs are used to boost contrast signal and enhance lesion conspicuity. High-energy VMIs are used to decrease some artifacts. Iodine maps are used to evaluate perfusion, characterize lesions, and evaluate response to therapy. VNC images are used to characterize lesions and save radiation dose by eliminating true noncontrast images from multiphasic acquisitions. Uric acid images are used for characterization of renal calculi and gout. Online supplemental material is available for this article. ©RSNA, 2020.

Virtual Monochromatic Dual-Energy Aortoiliac CT Angiography With Reduced Iodine Dose: A Prospective Randomized Study.

OBJECTIVE: The purpose of this study was to assess the feasibility of performing abdominopelvic aortoiliac CT angiography (CTA) with 16.0 g of iodine contrast medium acquired with low-energy (40 and 50 keV) virtual monochromatic (VMC) images with rapid-kilovoltage-switching dual-energy CT. SUBJECTS AND METHODS: A total of 52 adults with abdominal aortoiliac aneurysm and prior 120-kVp single-energy CTA (SECTA) with 33 g iodine (standard dose) underwent follow-up dual-energy CTA (DECTA) with a 52% reduced iodine dose. Subjects were randomly assigned to a contrast medium protocol for DECTA examinations: one group (n = 26) received 16.2 g (270 mg I/mL) and the other (n = 26) received 16.0 g (320 mg I/mL). Two readers independently assessed SECTA and VMC DECTA datasets for image quality using a 5-point scale. Aortoiliac intravascular attenuation was measured, and ANOVA was used to compare measurements between VMC DECTA and SECTA images. In a subset of patients with DECTA after endovascular aortic repair, endoleak detection was evaluated on VMC images. Volume CT dose index, dose-length product, and size-specific dose estimate were compared between DECTA and SECTA. RESULTS: All DECTA examinations (n = 52) were rated diagnostic with image quality scores comparable to those of 120-kVp single-energy CTA (40 keV, 4.2-4.4; 50 keV, 4.6-4.8; SECTA, 4.4-4.5). Intravascular attenuation was uniform in all reduced-iodine DECTA examinations and was significantly higher on 40- and 50-keV images than on standard-iodine-dose SECTA images (720 ± 125 HU and 482 ± 82 HU vs 303 ± 65 HU) (p < 0.01). There was no difference in intravascular attenuation between the 16.2-g and the 16.0-g doses (p = 0.82). Sensitivity and specificity for endoleak detection were 78.9-94.7% and 100%. Total dose-length product was lower for DECTA (788 ± 166 mGy · cm) than for SECTA (1114 ± 468 mGy · cm). CONCLUSION: Low-energy VMC DECTA images (40 and 50 keV) acquired with two contrast protocols at approximately 50% reduced iodine dose (16.0 and 16.2 g) provide adequate intravascular attenuation and diagnostic quality for aortoiliac evaluation.

Dual-Source Dual-Energy CT in Detection and Characterization of Urinary Stones in Patients With Large Body Habitus: Observations in a Large Cohort.

OBJECTIVE: The objective of our study was to investigate the impact of large body habitus on dual-energy CT (DECT) image quality and stone characterization. MATERIALS AND METHODS: We retrospectively included 105 consecutive patients with large body habitus (> 90 kg) who underwent stone protocol DECT between 2015 and 2017. The evaluation of DECT datasets was performed for image quality assessment based on European Guidelines on Quality Criteria for Computed Tomography and for determination of stone composition (i.e., uric acid vs non-uric acid). Correlation between DECT characterization and crystallography results was performed when available. The cohort was divided into two groups on the basis of body weight (≤ 104 kg and > 104 kg), and comparisons were made for image quality and stone characterization. RESULTS: One hundred ninety-seven urinary tract calculi (size: mean ± SD, 5.7 ± 5.3 mm; range, 1.4-56 mm) were detected in 73% (79/108) of examinations in 105 patients (weight: mean ± SD, 104.0 ± 12.7 kg; range, 91-163 kg). The overall mean image quality score of blended images and color maps was 3.7 and 3.9, respectively, and the effective dual-energy FOV limitation did not hamper stone characterization. The diagnostic acceptability scores of blended images and color maps were slightly lower in patients weighing > 104 kg than in patients ≤ 104 kg (mean scores [highest score, 4 points]: blended images, 3.62 vs 3.82 [p = 0.0314]; color maps, 3.75 vs 3.98 [p = 0.0034]), but the scores were within acceptable range. Stone characterization as uric acid versus non-uric acid was achieved in 80% (158/197) of calculi (size: mean ± SD, 6.4 ± 5.7 mm; range, 1.6-56 mm), and DECT stone characterization was (95.6%) accurate with reference to crystallography. Twenty percent (39/197) of calculi could not be characterized on DECT, and these calculi were significantly smaller in size (size: mean ± SD, 2.8 ± 1.4 mm; range, 1.4-8.2 mm; p < 0.001) than those that could be characterized. The mean size of uncharacterized calculi was slightly larger in patients weighing > 104 kg (3.3 ± 1.6 mm) than in those weighing ≤ 104 kg (2.2 ± 0.6 mm). CONCLUSION: In patients with large body habitus, dual-source DECT provides acceptable image quality and allows characterization of almost all clinically significant calculi.

Experience With Iterative Reconstruction Techniques for Abdominopelvic Computed Tomography in Morbidly and Super Obese Patients.

OBJECTIVE: The aim of this study was to investigate the diagnostic performance of abdominopelvic computed tomography (CT) images reconstructed using filtered back projection (FBP) and iterative reconstruction (IR) algorithms in morbidly and super obese patients. MATERIALS AND METHODS: One hundred eighty-seven abdominopelvic CT examinations in portal venous phase were performed between February 2015 and February 2016 in 182 patients (mean age = 52 years, mean body mass index = 45.5). One hundred fourteen of 187 examinations were reconstructed using IR and 73 examinations were processed using FBP. Patients were further stratified based on body mass index. Sixty CT scans were reviewed by a single reader for image quality, image noise, and artifacts. Objective noise and attenuation were also determined. Size-specific dose estimate and CT dose index volume were compared and statistically analyzed. RESULTS: A diagnostic interpretation was rendered for all 187 examinations. A single-reader review of 60 cases showed greater diagnostic acceptability for IR when compared with FBP (image quality = 4.2 and 3.8 [P = 0.035], noise = 1.5 and 1.6 [P = 0.692], artifact = 1.4 and 1.5 [P = 0.759], respectively). For all examinations, the IR group had lower objective image noise (IR = 9.3 and FBP = 14.3; P < 0.001) and higher contrast-to-noise ratio (IR = 17.2 and FBP = 11.7; P < 0.001) without increase in radiation dose (size-specific dose estimate [IR = 15.1, FBP = 16.5 mGy; P = 0.045] and CT dose index volume [IR = 17.6, FBP = 18 mGy; P = 0.62]). CONCLUSIONS: In morbidly and super obese patients, diagnostic quality images could be reliably generated with minimal artifacts and noise using newer generation scanners integrated with IR without increasing radiation dose.

Dual-Source Dual-Energy CT Portal Venous Phase Abdominal CT Scans in Large Body Habitus Patients: Preliminary Observations on Image Quality and Material Decomposition.

PURPOSE: Our objective was to evaluate image quality (IQ) and material decomposition in patients with large body habitus undergoing portal venous phase abdominal computed tomography (CT) scans on dual-source dual-energy CT (dsDECT) scanners. METHODS: This retrospective analysis included 30 scans from consecutive patients (19 males/11 females, mean ± SD age = 55.3 ± 17.5 years, range = 27-87 years) with large body habitus (≥90 kg, mean ± SD weight = 105.4 ± 12.35, range = 91-145 kg) who underwent portal venous phase abdominal DECT examinations on dsDECT scanner between Jan 2015 and Dec 2015. Qualitative and quantitative evaluation of IQ of DECT data sets (blended, iodine, and virtual noncontrast images) was performed. The patients were categorized into 2 groups (group A, ≤104 kg; group B, >104 kg). RESULTS: The mean ± SD patient body weight in group A was 97.2 ± 4.5 kg (range = 91-104 kg) and 114.8 ± 11.7 kg (range = 104.3-145.2 kg) for patients in group B. The diagnostic acceptability of the blended images in patients > 104 kg was lower (3.6 vs 4, <3 in 4/14 vs 0/16, P = 0.03). The extension of visceral anatomy beyond DE field of view (DEFOV) was seen in 60% (28 organs in 18 patients), the most common organs being liver and spleen. The incidence of visceral organs outside DEFOV was significantly higher in patients > 104 kg (18 vs 10, P = 0.03). Outside the DEFOV, blended images demonstrated higher image noise (mean: 14.48, range = 10.09-26.83 vs mean: 9.5, range = 7.3-15.8) P < 0.001) and lower signal-to-noise ratio (mean: 4.15, range = 1.5-7.6 vs mean: 7.5, range = 4.2-9.9) P < 0.001), and material-specific information was not available in this region. Within the DEFOV, the IQ of iodine maps and virtual non-contrast images were diagnostically acceptable with diagnostic acceptability of 3 or greater in nearly all patients. A 40-cm transverse diameter cut-off provided a good predictor of extension of visceral anatomy outside the effective DEFOV. CONCLUSIONS: Dual-source DECT allows diagnostically acceptable IQ and material separation in patients with large body habitus with the major limitation of exclusion of patient anatomy and organs outside the effective dual-energy field of view.

Imaging for Oncologic Response Assessment in Lymphoma.

OBJECTIVE: The purpose of this article is to examine the role of different imaging biomarkers, focusing in particular on the use of updated CT and PET response criteria for the assessment of oncologic treatment effectiveness in patients with lymphoma but also discussing other potential functional imaging methods and their limitations. CONCLUSION: Lymph nodes are commonly involved by metastatic solid tumors as well as by lymphoma. Evolving changes in cancer therapy for lymphoma and metastases have led to improved clinical outcomes. Imaging is a recognized surrogate endpoint that uses established criteria based on changes in tumor bulk to monitor the effects of treatment. With the introduction of targeted therapies and novel antiangiogenic drugs, the oncologic expectations from imaging assessment are changing to move beyond simple morphologic methods. Molecular and functional imaging methods (e.g., PET, perfusion, DWI, and dual-energy CT) are therefore being investigated as imaging biomarkers of response and prognosis. The role of these advanced imaging biomarkers extends beyond measuring tumor burden and therefore might offer insight into early predictors of therapeutic response. Despite the potential benefits of these exciting imaging biomarkers, several challenges currently exist.

A quantitative comparison of noise reduction across five commercial (hybrid and model-based) iterative reconstruction techniques: an anthropomorphic phantom study.

OBJECTIVE. The objective of our study was to compare the performance of three hybrid iterative reconstruction techniques (IRTs) (ASiR, iDose4, SAFIRE) and their respective strengths for image noise reduction on low-dose CT examinations using filtered back projection (FBP) as the standard reference. Also, we compared the performance of these three hybrid IRTs with two model-based IRTs (Veo and IMR) for image noise reduction on low-dose examinations. MATERIALS AND METHODS. An anthropomorphic abdomen phantom was scanned at 100 and 120 kVp and different tube current-exposure time products (25-100 mAs) on three CT systems (for ASiR and Veo, Discovery CT750 HD; for iDose4 and IMR, Brilliance iCT; and for SAFIRE, Somatom Definition Flash). Images were reconstructed using FBP and using IRTs at various strengths. Nine noise measurements (mean ROI size, 423 mm(2)) on extracolonic fat for the different strengths of IRTs were recorded and compared with FBP using ANOVA. Radiation dose, which was measured as the volume CT dose index and dose-length product, was also compared. RESULTS. There were no significant differences in radiation dose and image noise among the scanners when FBP was used (p > 0.05). Gradual image noise reduction was observed with each increasing increment of hybrid IRT strength, with a maximum noise suppression of approximately 50% (48.2-53.9%). Similar noise reduction was achieved on the scanners by applying specific hybrid IRT strengths. Maximum noise reduction was higher on model-based IRTs (68.3-81.1%) than hybrid IRTs (48.2-53.9%) (p < 0.05). CONCLUSION. When constant scanning parameters are used, radiation dose and image noise on FBP are similar for CT scanners made by different manufacturers. Significant image noise reduction is achieved on low-dose CT examinations rendered with IRTs. The image noise on various scanners can be matched by applying specific hybrid IRT strengths. Model-based IRTs attain substantially higher noise reduction than hybrid IRTs irrespective of the radiation dose.