Detectability of Hypoattenuating Liver Lesions with Deep Learning CT Reconstruction: A Phantom and Patient Study.

Background CT deep learning image reconstruction (DLIR) improves image quality by reducing noise compared with adaptive statistical iterative reconstruction-V (ASIR-V). However, objective assessment of low-contrast lesion detectability is lacking. Purpose To investigate low-contrast detectability of hypoattenuating liver lesions on CT scans reconstructed with DLIR compared with CT scans reconstructed with ASIR-V in a patient and a phantom study. Materials and Methods This single-center retrospective study included patients undergoing portal venous phase abdominal CT between February and May 2021 and a low-contrast-resolution phantom scanned with the same protocol. Four reconstructions (ASIR-V at 40% strength [ASIR-V 40] and DLIR at three strengths) were generated. Five radiologists qualitatively assessed the images using the five-point Likert scale for image quality, lesion diagnostic confidence, conspicuity, and small lesion (≤1 cm) visibility. Up to two key lesions per patient, confirmed at histopathologic testing or at prior or follow-up imaging studies, were included. Lesion-to-background contrast-to-noise ratio was calculated. Interreader variability was analyzed. Intergroup qualitative and quantitative metrics were compared between DLIR and ASIR-V 40 using proportional odds logistic regression models. Results Eighty-six liver lesions (mean size, 15 mm ± 9.5 [SD]) in 50 patients (median age, 62 years [IQR, 57-73 years]; 27 [54%] female patients) were included. Differences were not detected for various qualitative low-contrast detectability metrics between ASIR-V 40 and DLIR (P > .05). Quantitatively, medium-strength DLIR and high-strength DLIR yielded higher lesion-to-background contrast-to-noise ratios than ASIR-V 40 (medium-strength DLIR vs ASIR-V 40: odds ratio [OR], 1.96 [95% CI: 1.65, 2.33]; high-strength DLIR vs ASIR-V 40: OR, 5.36 [95% CI: 3.68, 7.82]; P < .001). Low-contrast lesion attenuation was reduced by 2.8-3.6 HU with DLIR. Interreader agreement was moderate to very good for the qualitative metrics. Subgroup analysis based on lesion size of larger than 1 cm and 1 cm or smaller yielded similar results (P > .05). Qualitatively, phantom study results were similar to those in patients (P > .05). Conclusion The detectability of low-contrast liver lesions was similar on CT scans reconstructed with low-, medium-, and high-strength DLIR and ASIR-V 40 in both patient and phantom studies. Lesion-to-background contrast-to-noise ratios were higher for DLIR medium- and high-strength reconstructions compared with ASIR-V 40. © RSNA, 2024 Supplemental material is available for this article.

Multi-reader multiparametric DECT study evaluating different strengths of iterative and deep learning-based image reconstruction techniques.

OBJECTIVES: To perform a multi-reader comparison of multiparametric dual-energy computed tomography (DECT) images reconstructed with deep-learning image reconstruction (DLIR) and standard-of-care adaptive statistical iterative reconstruction-V (ASIR-V). METHODS: This retrospective study included 100 patients undergoing portal venous phase abdominal CT on a rapid kVp switching DECT scanner. Six reconstructed DECT sets (ASIR-V and DLIR, each at three strengths) were generated. Each DECT set included 65 keV monoenergetic, iodine, and virtual unenhanced (VUE) images. Using a Likert scale, three radiologists performed qualitative assessments for image noise, contrast, small structure visibility, sharpness, artifact, and image preference. Quantitative assessment was performed by measuring attenuation, image noise, and contrast-to-noise ratios (CNR). For the qualitative analysis, Gwet's AC2 estimates were used to assess agreement. RESULTS: DECT images reconstructed with DLIR yielded better qualitative scores than ASIR-V images except for artifacts, where both groups were comparable. DLIR-H images were rated higher than other reconstructions on all parameters (p-value < 0.05). On quantitative analysis, there was no significant difference in the attenuation values between ASIR-V and DLIR groups. DLIR images had higher CNR values for the liver and portal vein, and lower image noise, compared to ASIR-V images (p-value < 0.05). The subgroup analysis of patients with large body habitus (weight ≥ 90 kg) showed similar results to the study population. Inter-reader agreement was good-to-very good overall. CONCLUSION: Multiparametric post-processed DECT datasets reconstructed with DLIR were preferred over ASIR-V images with DLIR-H yielding the highest image quality scores. CLINICAL RELEVANCE STATEMENT: Deep-learning image reconstruction in dual-energy CT demonstrated significant benefits in qualitative and quantitative image metrics compared to adaptive statistical iterative reconstruction-V. KEY POINTS: Dual-energy CT (DECT) images reconstructed using deep-learning image reconstruction (DLIR) showed superior qualitative scores compared to adaptive statistical iterative reconstruction-V (ASIR-V) reconstructed images, except for artifacts where both reconstructions were rated comparable. While there was no significant difference in attenuation values between ASIR-V and DLIR groups, DLIR images showed higher contrast-to-noise ratios (CNR) for liver and portal vein, and lower image noise (p value < 0.05). Subgroup analysis of patients with large body habitus (weight ≥ 90 kg) yielded similar findings to the overall study population.

Society of Radiologists in Ultrasound Consensus Conference Recommendations for Incidental Gallbladder Polyp Management: Interreader Agreement Among 10 Radiologists.

BACKGROUND. The 2022 Society of Radiologists in Ultrasound (SRU) consensus conference recommendations for small gallbladder polyps support management that is less aggressive than earlier approaches and may help standardize evaluation of polyps by radiologists. OBJECTIVE. The purpose of the present study was to assess the interreader agreement of radiologists in applying SRU recommendations for management of incidental gallbladder polyps on ultrasound. METHODS. This retrospective study included 105 patients (75 women and 30 men; median age, 51 years) with a gallbladder polyp on ultrasound (without features highly suspicious for invasive or malignant tumor) who underwent cholecystectomy between January 1, 2003, and January 1, 2021. Ten abdominal radiologists independently reviewed ultrasound examinations and, using the SRU recommendations, assessed one polyp per patient to assign risk category (extremely low risk, low risk, or indeterminate risk) and make a possible recommendation for surgical consultation. Five radiologists were considered less experienced (< 5 years of experience), and five were considered more experienced (≥ 5 years of experience). Interreader agreement was evaluated. Polyps were classified pathologically as nonneoplastic or neoplastic. RESULTS. For risk category assignments, interreader agreement was substantial among all readers (k = 0.710), less-experienced readers (k = 0.705), and more-experienced readers (k = 0.692). For surgical consultation recommendations, inter-reader agreement was substantial among all readers (k = 0.795) and more-experienced readers (k = 0.740) and was almost perfect among less-experienced readers (k = 0.811). Of 10 readers, a median of 5.0 (IQR, 2.0-8.0), 4.0 (IQR, 2.0-7.0), and 0.0 (IQR, 0.0-0.0) readers classified polyps as extremely low risk, low risk, and indeterminate risk, respectively. Across readers, the percentage of polyps classified as extremely low risk ranged from 32% to 72%; as low risk, from 24% to 65%; and as indeterminate risk, from 0% to 8%. Of 10 readers, a median of zero change to 0 (IQR, 0.0-1.0) readers recommended surgical consultation; the percentage of polyps receiving a recommendation for surgical consultation ranged from 4% to 22%. Of a total of 105 polyps, 102 were nonneo-plastic and three were neoplastic (all benign). Based on readers' most common assessments for nonneoplastic polyps, the risk category was extremely low risk for 53 polyps, low risk for 48 polyps, and indeterminate risk for one polyp; surgical consultation was recommended for 16 polyps. CONCLUSION. Ten abdominal radiologists showed substantial agreement for polyp risk categorizations and surgical consultation recommendations, although areas of reader variability were identified. CLINICAL IMPACT. The findings support the overall reproducibility of the SRU recommendations, while indicating opportunity for improvement.

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.

Comprehensive review of imaging in pancreas transplantation: a primer for radiologists.

Pancreas transplantation is a complex surgical procedure performed to restore normoglycemia in patients with type 1 diabetes and includes whole/segmental organ transplant and islet cell transplantation (ICT). In the United States, simultaneous pancreas-kidney transplant (SPK) is most commonly performed due to the higher occurrence of end-stage renal disease in diabetic patients. Understanding the surgical technique and postoperative anatomy is imperative for effective and accurate surveillance following transplantation. Imaging plays an essential role in patients with pancreatic transplants and is often used to evaluate viability, vascular and parenchymal anatomy, and identify potential complications. Imaging techniques such as ultrasound, color and spectral Doppler, computed tomography (CT), magnetic resonance imaging (MRI), and angiography have a complementary role in the postoperative evaluation following a pancreas transplant. The common complications after a whole organ pancreas transplant include vascular thrombosis, graft rejection, pancreatitis, and infections. Complications can be classified into vascular (partial or complete venous thrombosis, arterial thrombosis, stenosis or pseudoaneurysm), parenchymal (pancreatitis, graft rejection), and bowel-related or miscellaneous causes (bowel obstruction, anastomotic leak, and peripancreatic fluid collections). Islet cell transplantation is an innovative therapy for patients with type 1 diabetes. It involves isolating insulin-producing islet cells from donor pancreas and transplanting into recipients, to provide long-term insulin independence or significantly reduce insulin requirements. In recent years, isolation techniques, immunosuppressive regimens, and post-transplant monitoring advancements have propelled ICT as a viable therapeutic option. This comprehensive review aims to provide insights into the current state-of-the-art imaging techniques discussing both normal and abnormal features following pancreas transplantation.

Cholangiocarcinoma imaging: from diagnosis to response assessment.

Cholangiocarcinoma (CCA), a highly aggressive primary liver cancer arising from the bile duct epithelium, represents a substantial proportion of hepatobiliary malignancies, posing formidable challenges in diagnosis and treatment. Notably, the global incidence of intrahepatic CCA has seen a rise, necessitating a critical examination of diagnostic and management strategies, especially due to presence of close imaging mimics such as hepatocellular carcinoma (HCC) and combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA). Hence, it is imperative to understand the role of various imaging modalities such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), elucidating their strengths, and limitations in diagnostic precision and staging accuracy. Beyond conventional approaches, there is emerging significance of functional imaging tools including positron emission tomography (PET)-CT and diffusion-weighted (DW)-MRI, providing pivotal insights into diagnosis, therapeutic assessment, and prognostic evaluation. This comprehensive review explores the risk factors, classification, clinical features, and role of imaging in the holistic spectrum of diagnosis, staging, management, and restaging for CCA, hence serving as a valuable resource for radiologists evaluating CCA.

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.

Additional occult cancers identified on staging breast MRI: imaging appearances and pathologic characteristics.

INTRODUCTION: Breast magnetic resonance imaging (MRI) is increasingly being used for staging of patients with breast cancer due to its high sensitivity in detecting additional cancers (ACs). However, the clinical impact of diagnosing and treating these cancers remains unclear. METHODS: A retrospective study was undertaken of patients with newly diagnosed breast cancer who underwent staging MRI at The American University of Beirut Medical Centre (AUBMC) between 2012 and 2020. Pathology reports and breast MRI examinations were reviewed. Eighteen breast cancer patients with 19 pathology-proven index cancers (ICs) and 19 pathology-proven MRI-detected ACs were included. Chi-square and Fisher's exact tests for categorical variables and Wilcoxon signed rank test for numerical variables were used to compare ICs to ACs. RESULTS: The ICs consisted of four ductal carcinoma in situ (DCIS), 13 invasive ductal carcinomas (IDC), of which five with associated DCIS, and two invasive lobular carcinomas, (ILC) of which one with associated DCIS. ACs comprised 12 DCIS, five IDC, two with associated DCIS and two ILC, one with associated DCIS. Interval cancers were more frequently invasive whereas ACs were more frequently in situ (P = 0.021). ACs were more frequently nuclear grade 2 (P = 0.009). There was no statistically significant difference between ICs and ACs in lesion type (P = 0.062), shape (P = 0.073), initial enhancement (P = 1), delayed enhancement (P = 0.732), hormonal receptor profile (P = 0.68) and Ki67 (P = 0.388). Among ACs, ten (53%) were larger than 10 mm of which five (26%) were invasive cancers, and five (26%) were larger than the ICs. CONCLUSIONS: ACs detected by breast MRI were more likely to be in situ and to show a nuclear grade 2. Although not reaching statistical significance, some ACs tend to be clinically significant by their type, size or nuclear grade. The impact on clinical management remains to be determined.

Role of Dual Energy Computed Tomography in Inflammatory Bowel Disease.

Dual-energy computed tomography (DECT), which allows material-based differential X-ray absorption behavior from near simultaneously acquired low- and high-kilovolt datasets is finding increasing applications in the evaluation of bowel diseases. In patients with inflammatory bowel disease, DECT techniques permit both qualitative and quantitative assessment. Particularly in patients with Crohn's disease, monoenergetic and iodine specific images have been explored. This article focuses on the principles and applications of DECT in inflammatory bowel disease along with review of its limitations and challenges.

Prevalence of Cosmetic Procedures among Lebanese Women.

Lebanese women have been portrayed as conceited and obsessed with physical appearance and its beautification through cosmetic procedures. Despite the pervasiveness of this notion, no formal studies have been conducted to assess the true prevalence of cosmetic procedures among Lebanese women. Additionally, no data exist to elucidate trends in popularity of cosmetic procedures over time. A cross-sectional study was conducted across Lebanese universities where surveys were distributed to women aged 18-31 years to estimate the prevalence of surgical, noninvasive, and dental cosmetic procedures in young Lebanese women. The collected survey data were analyzed using the Statistical Package for the Social Sciences (SPSS). In a sample of 877 women, 44% reported having undergone at least one cosmetic procedure in their lifetime. The most popular procedures performed were laser hair removal (32%), teeth whitening (14%), and rhinoplasty (9.3%). The obtained results revealed an increasing prevalence of cosmetic procedures, mirroring global trends. A variety of factors have contributed to the increasing popularity of cosmetic procedures, namely, higher availability, better affordability, and wider social acceptance over time. (SKINmed. 2022;20:422-427).