Clinical outcomes and future fertility after uterine artery embolization for postpartum and post-abortion hemorrhage.

BACKGROUND: Postpartum hemorrhage (PPH) and post-abortion hemorrhage (PAH) are life-threatening conditions. PURPOSE: To evaluate the efficacy and safety of uterine arterial embolization (UAE) for PPH and PAH and to investigate future fertility after UAE. MATERIAL AND METHODS: This study included 57 consecutive patients (mean age = 34 years) who underwent UAE for PPH (n = 46) and PAH (n = 11) at our institution between January 2011 and December 2022. Technical success, non-visualization of the peripheral portion of bilateral uterine arteries on angiography, and clinical success, complete hemostasis after UAE, were assessed. UAE-associated complications and factors related to clinical success were analyzed. Pregnancy outcomes after UAE and complications during subsequent pregnancy were investigated in 16 patients who desired fertility and were followed up for >1 year. RESULTS: The technical and clinical success rates were 100% and 84.2%, respectively. Sepsis (n = 1) and uterine empyema (n = 1) were observed as severe complications. Placental disorder, bleeding within 24 h after delivery or abortion, ≥1.5 shock index, ≥6 units of transfusion erythrocytes, and ≥8 obstetrical disseminated intravascular coagulation score were significantly associated with unfavorable clinical outcomes. In total, 16 pregnancies were observed in 12 patients after UAE, three of which were miscarriages and 13 were successful live births. During pregnancy, uterine rupture (n = 1) and accreta (n = 1) were observed. CONCLUSION: UAE is an effective treatment for PPH and PAH. Although UAE could preserve future fertility, careful attention should be paid to perinatal management for unusual complications.

Photon-counting CT in Thoracic Imaging: Early Clinical Evidence and Incorporation Into Clinical Practice.

Photon-counting CT (PCCT) is an emerging advanced CT technology that differs from conventional CT in its ability to directly convert incident x-ray photon energies into electrical signals. The detector design also permits substantial improvements in spatial resolution and radiation dose efficiency and allows for concurrent high-pitch and high-temporal-resolution multienergy imaging. This review summarizes (a) key differences in PCCT image acquisition and image reconstruction compared with conventional CT; (b) early evidence for the clinical benefit of PCCT for high-spatial-resolution diagnostic tasks in thoracic imaging, such as assessment of airway and parenchymal diseases, as well as benefits of high-pitch and multienergy scanning; (c) anticipated radiation dose reduction, depending on the diagnostic task, and increased utility for routine low-dose thoracic CT imaging; (d) adaptations for thoracic imaging in children; (e) potential for further quantitation of thoracic diseases; and (f) limitations and trade-offs. Moreover, important points for conducting and interpreting clinical studies examining the benefit of PCCT relative to conventional CT and integration of PCCT systems into multivendor, multispecialty radiology practices are discussed.

Imaging of Perirenal and Intrarenal Lymphatic Vessels: Anatomy-based Approach.

The lymphatic system (or lymphatics) consists of lymphoid organs and lymphatic vessels. Despite the numerous previously published studies describing conditions related to perirenal and intrarenal lymphoid organs in the radiology literature, the radiologic findings of conditions related to intrarenal and perirenal lymphatic vessels have been scarcely reported. In the renal cortex, interlobular lymphatic capillaries do not have valves; therefore, lymph can travel along the primary route toward the hilum, as well as toward the capsular lymphatic plexus. These two lymphatic pathways can be opacified by contrast medium via pyelolymphatic backflow at CT urography, which reflects urinary contrast agent leakage into perirenal lymphatic vessels via forniceal rupture. Pyelolymphatic backflow toward the renal hilum should be distinguished from urinary leakage due to urinary injury. Delayed subcapsular contrast material retention via pyelolymphatic backflow, appearing as hyperattenuating subcapsular foci on CT images, mimics other subcapsular cystic diseases. In contrast to renal parapelvic cysts originating from the renal parenchyma, renal peripelvic cysts are known to be of lymphatic origin. Congenital renal lymphangiectasia is mainly seen in children and assessed and followed up at imaging. Several lymphatic conditions, including lymphatic leakage as an early complication and acquired renal lymphangiectasia as a late complication, are sometimes identified at imaging follow-up of kidney transplant. Lymphangiographic contrast material accumulation in the renal hilar lymphatic vessels is characteristic of chylo-urinary fistula. Chyluria appears as a fat-layering fluid-fluid level in the urinary bladder or upper urinary tract. Recognition of the anatomic pathway of tumor spread via lymphatic vessels at imaging is of clinical importance for accurate management at oncologic imaging. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Targeted Training Reduces Search Errors but Not Classification Errors for Hepatic Metastasis Detection at Contrast-Enhanced CT.

RATIONALE AND OBJECTIVES: Methods are needed to improve the detection of hepatic metastases. Errors occur in both lesion detection (search) and decisions of benign versus malignant (classification). Our purpose was to evaluate a training program to reduce search errors and classification errors in the detection of hepatic metastases in contrast-enhanced abdominal computed tomography (CT). MATERIALS AND METHODS: After Institutional Review Board approval, we conducted a single-group prospective pretest-posttest study. Pretest and posttest were identical and consisted of interpreting 40 contrast-enhanced abdominal CT exams containing 91 liver metastases under eye tracking. Between pretest and posttest, readers completed search training with eye-tracker feedback and coaching to increase interpretation time, use liver windows, and use coronal reformations. They also completed classification training with part-task practice, rating lesions as benign or malignant. The primary outcome was metastases missed due to search errors (<2 seconds gaze under eye tracker) and classification errors (>2 seconds). Jackknife free-response receiver operator characteristic (JAFROC) analysis was also conducted. RESULTS: A total of 31 radiologist readers (8 abdominal subspecialists, 8 nonabdominal subspecialists, 15 senior residents/fellows) participated. Search errors were reduced (pretest 11%, posttest 8%, difference 3% [95% confidence interval, 0.3%-5.1%], P = .01), but there was no difference in classification errors (difference 0%, P = .97) or in JAFROC figure of merit (difference -0.01, P = .36). In subgroup analysis, abdominal subspecialists demonstrated no evidence of change. CONCLUSION: Targeted training reduced search errors but not classification errors for the detection of hepatic metastases at contrast-enhanced abdominal CT. Improvements were not seen in all subgroups.

Infrapopliteal Segments on Lower-Extremity CTA: Prospective Intraindividual Comparison of Energy-Integrating Detector CT and Photon-Counting Detector CT.

Background: The higher spatial resolution and image contrast for iodine-containing tissues of photon-counting detector (PCD) CT may address challenges in evaluating small, calcified vessels when performing lower-extremity CTA by energy-integrating detector (EID) CTA. Purpose: To compare the evaluation of infrapopliteal vasculature between lower-extremity CTA performed using EID CT and PCD CT. Methods: This prospective study included 32 patients (mean age 69.5±8.3 years; 27 men, 5 women) who underwent clinically indicated lower-extremity EID CTA between April 2021 and March 2022; participants underwent investigational lower-extremity PCD CTA later in the same day as EID CTA using a reduced IV contrast media dose. Two radiologists independently reviewed examinations in two sessions, each containing a random combination of EID-CT and PCD-CT examinations, assessing the number of visualized fibular perforators, characteristics of stenoses at 11 infrapopliteal segmental levels, and subjective arterial sharpness. Results: Mean IV contrast media dose was 60.0±11.0 ml for PCD CTA versus 139.6±11.8 ml for EID CTA (p<.001). Number of identified fibular perforators per lower extremity was significantly higher for PCD CTA than for EID CTA for reader 1 (6.4±3.2 vs 4.2±2.4, p<.001) and reader 2 (8.8±3.4 vs 7.6±3.3, p=.04). Reader confidence for assessing stenosis was significantly higher for PCD CTA than for EID CTA for reader 1 (82.3±20.3 vs 78.0±20.2; p<.001), but not reader 2 (89.8±16.7 vs 90.6±7.1; p=.24). Number of segments per lower extremity with total occlusion was significantly lower for PCD CTA than for EID CTA for reader 2 (0.5±1.3 vs 0.9±1.7; p=.04) but not reader 1 (0.6±1.3 vs 1.0±1.5; p=.07). Number of segments per lower extremity with clinically significant nonocclusive stenosis was significantly higher for PCD CTA than for EID CTA for reader 1 (2.2±2.2 vs 1.6±1.7; p=.01) but not reader 2 (1.1±2.0 vs 1.1±1.4; p=.89). Arterial sharpness was significantly greater for PCD CTA than for EID CTA for reader 1 (3.2±0.5 vs 1.8±0.5; p<.001) and reader 2 (3.2±0.4 vs 1.7±0.8; p<.001). Conclusion: PCD CTA yielded multiple advantages relative to EID CTA for visualizing small infrapopliteal vessels and characterizing associated plaque. Clinical Impact: Use of PCD CTA may improve vascular evaluation in patients with peripheral arterial disease.

Self-trained deep convolutional neural network for noise reduction in CT.

Purpose: Supervised deep convolutional neural network (CNN)-based methods have been actively used in clinical CT to reduce image noise. The networks of these methods are typically trained using paired high- and low-quality data from a massive number of patients and/or phantom images. This training process is tedious, and the network trained under a given condition may not be generalizable to patient images acquired and reconstructed under different conditions. We propose a self-trained deep CNN (ST_CNN) method for noise reduction in CT that does not rely on pre-existing training datasets. Approach: The ST_CNN training was accomplished using extensive data augmentation in the projection domain, and the inference was applied to the data itself. Specifically, multiple independent noise insertions were applied to the original patient projection data to generate multiple realizations of low-quality projection data. Then, rotation augmentation was adopted for both the original and low-quality projection data by applying the rotation angle directly on the projection data so that images were rotated at arbitrary angles without introducing additional bias. A large number of paired low- and high-quality images from the same patient were reconstructed and paired for training the ST_CNN model. Results: No significant difference was found between the ST_CNN and conventional CNN models in terms of the peak signal-to-noise ratio and structural similarity index measure. The ST_CNN model outperformed the conventional CNN model in terms of noise texture and homogeneity in liver parenchyma as well as better subjective visualization of liver lesions. The ST_CNN may sacrifice the sharpness of vessels slightly compared to the conventional CNN model but without affecting the visibility of peripheral vessels or diagnosis of vascular pathology. Conclusions: The proposed ST_CNN method trained from the data itself may achieve similar image quality in comparison with conventional deep CNN denoising methods pre-trained on external datasets.

The diagnostic accuracy of endoscopic ultrasound-shear wave elastography in multiple pancreatic regions for chronic pancreatitis based on the Rosemont criteria.

PURPOSE: Although endoscopic ultrasound (EUS) has been widely used for diagnosing chronic pancreatitis (CP), the assessment of fibrosis using the Rosemont criteria (RC) is generally subjective. Shear wave elastography using EUS (EUS-SWE) has been advocated as an objective approach to evaluating pancreatic fibrosis; however, it is unknown which pancreatic region should be selected for measurement. This study aims to compare the diagnostic accuracy in diagnosing CP by measurement site. METHODS: Fifty patients with CP or suspected CP who underwent EUS-SWE were retrospectively analyzed. As per the RC, they were classified into two groups: CP and non-CP. Pancreatic stiffness was evaluated by measuring the velocities of the shear wave (Vs) in addition to determining the relevant cutoff value of Vs for diagnosing CP. The correlation between Vs and RC, and the RC factors affecting pancreatic stiffness were evaluated. RESULTS: In the CP group, the Vs were notably higher in all regions (P < 0.001). The Vs for diagnostic accuracy of CP were highest in the body [area under the curve (AUC): 0.87]. A significant correlation was seen between the number of RC and Vs in all regions, with the correlation coefficient being highest in the pancreatic body (rs = 0.55). Multivariate analysis revealed that lobularity with honeycombing was an independent factor for pancreatic stiffness (P = 0.02). CONCLUSION: The pancreatic body is a suitable region for assessing pancreatic stiffness using EUS-SWE. Additionally, quantifying Vs is a valuable objective indicator for diagnosing CP.

Seeing More with Less: Clinical Benefits of Photon-counting Detector CT.

Photon-counting detector (PCD) CT is an emerging technology that has led to continued innovation and progress in diagnostic imaging after it was approved by the U.S. Food and Drug Administration for clinical use in September 2021. Conventional energy-integrating detector (EID) CT measures the total energy of x-rays by converting photons to visible light and subsequently using photodiodes to convert visible light to digital signals. In comparison, PCD CT directly records x-ray photons as electric signals, without intermediate conversion to visible light. The benefits of PCD CT systems include improved spatial resolution due to smaller detector pixels, higher iodine image contrast, increased geometric dose efficiency to allow high-resolution imaging, reduced radiation dose for all body parts, multienergy imaging capabilities, and reduced artifacts. To recognize these benefits, diagnostic applications of PCD CT in musculoskeletal, thoracic, neuroradiologic, cardiovascular, and abdominal imaging must be optimized and adapted for specific diagnostic tasks. The diagnostic benefits and clinical applications resulting from PCD CT in early studies have allowed improved visualization of key anatomic structures and radiologist confidence for some diagnostic tasks, which will continue as PCD CT evolves and clinical use and applications grow. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Ananthakrishnan in this issue.

A training program to reduce reader search errors for liver metastasis detection in CT.

Detection of low contrast liver metastases varies between radiologists. Training may improve performance for lower-performing readers and reduce inter-radiologist variability. We recruited 31 radiologists (15 trainees, 8 non-abdominal staff, and 8 abdominal staff) to participate in four separate reading sessions: pre-test, search training, classification training, and post-test. In the pre-test, each radiologist interpreted 40 liver CT exams containing 91 metastases, circumscribed suspected hepatic metastases while under eye tracker observation, and rated confidence. In search training, radiologists interpreted a separate set of 30 liver CT exams while receiving eye tracker feedback and after coaching to increase use of coronal reformations, interpretation time, and use of liver windows. In classification training, radiologists interpreted up to 100 liver CT image patches, most with benign or malignant lesions, and compared their annotations to ground truth. Post-test was identical to pre-test. Between pre- and post-test, sensitivity increased by 2.8% (p = 0.01) but AUC did not change significantly. Missed metastases were classified as search errors (<2 seconds gaze time) or classification errors (>2 seconds gaze time) using the eye tracker. Out of 2775 possible detections, search errors decreased (10.8% to 8.1%; p < 0.01) but classification errors were unchanged (5.7% vs 5.7%). When stratified by difficulty, easier metastases showed larger reductions in search errors: for metastases with average sensitivity of 0-50%, 50-90%, and 90-100%, reductions in search errors were 16%, 35%, and 58%, respectively. The training program studied here may be able to improve radiologist performance by reducing errors but not classification errors.

Bile duct penetrating duodenal wall sign: a novel computed tomography finding of common bile duct stone impaction into duodenal major papilla.

PURPOSE: Impacted common bile duct stones cause severe acute cholangitis. However, the early and accurate diagnosis, especially iso-attenuating stone impaction, is still challenging. Therefore, we proposed and validated the bile duct penetrating duodenal wall sign (BPDS), which shows the common bile duct penetrating the duodenal wall on coronal reformatted computed tomography (CT), as a novel sign of stone impaction. METHODS: Patients who underwent urgent endoscopic retrograde cholangiopancreatography (ERCP) for acute cholangitis due to common bile duct stones were retrospectively enrolled. Stone impaction was defined by endoscopic findings as a reference standard. Two abdominal radiologists blinded to clinical information interpreted CT images to record the presence of the BPDS. The diagnostic accuracy of the BPDS to diagnose stone impaction was analyzed. Clinical data related to the severity of acute cholangitis were compared between patients with and without the BPDS. RESULTS: A total of 40 patients (mean age 70.6 years; 18 female) were enrolled. The BPDS was observed in 15 patients. Stone impaction occurred in 13/40 (32.5%) cases. Overall accuracy, sensitivity, and specificity were 34/40 (85.0%), 11/13 (84.6%), and 23/27 (85.2%), respectively; 14/16 (87.5%), 5/6 (83.3%), and 9/10 (90.0%) for iso-attenuating stones; and 20/24 (83.3%), 6/7 (85.7%), and 14/17 (82.4%) for high-attenuating stones. Interobserver agreement of the BPDS was substantial (κ = 0.68). In addition, the BPDS was significantly correlated with the number of factors in the systemic inflammatory response syndrome (P = 0.03) and total bilirubin (P = 0.04). CONCLUSION: The BPDS was a unique CT imaging finding to identify common bile duct stone impaction regardless of stone attenuation with high accuracy.

Multislice input for 2D and 3D residual convolutional neural network noise reduction in CT.

Purpose: Deep convolutional neural network (CNN)-based methods are increasingly used for reducing image noise in computed tomography (CT). Current attempts at CNN denoising are based on 2D or 3D CNN models with a single- or multiple-slice input. Our work aims to investigate if the multiple-slice input improves the denoising performance compared with the single-slice input and if a 3D network architecture is better than a 2D version at utilizing the multislice input. Approach: Two categories of network architectures can be used for the multislice input. First, multislice images can be stacked channel-wise as the multichannel input to a 2D CNN model. Second, multislice images can be employed as the 3D volumetric input to a 3D CNN model, in which the 3D convolution layers are adopted. We make performance comparisons among 2D CNN models with one, three, and seven input slices and two versions of 3D CNN models with seven input slices and one or three output slices. Evaluation was performed on liver CT images using three quantitative metrics with full-dose images as reference. Visual assessment was made by an experienced radiologist. Results: When the input channels of the 2D CNN model increases from one to three to seven, a trend of improved performance was observed. Comparing the three models with the seven-slice input, the 3D CNN model with a one-slice output outperforms the other models in terms of noise texture and homogeneity in liver parenchyma as well as subjective visualization of vessels. Conclusions: We conclude the that multislice input is an effective strategy for improving performance for 2D deep CNN denoising models. The pure 3D CNN model tends to have a better performance than the other models in terms of continuity across axial slices, but the difference was not significant compared with the 2D CNN model with the same number of slices as the input.

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

OBJECTIVE: This study aimed to determine the optimal photon energy for virtual monoenergetic images (VMI) in computed tomography angiography (CTA) using photon-counting-detector (PCD) CT. METHODS: Under institutional review board approval, 10 patients (abdominal, n = 4; lower extremity, n = 3; head and neck, n = 3) were scanned on an investigational PCD-CT (Count Plus, Siemens Healthcare) at 120 or 140 kV. All images were iteratively reconstructed with Bv48 kernel and 2-mm slice thickness. Axial and coronal VMI maximum-intensity projections were created in the range 40 to 65 keV (5-keV steps). Contrast-to-noise ratio (CNR) was calculated for major arteries in each VMI series. Two radiologists blindly ranked each VMI series for overall image quality and visualization of small vessels and pathology. The median and SD of scores for each photon energy were calculated. In addition, readers identified any VMIs that distinguished itself from others in terms of vessel/pathology visualization or artifacts. RESULTS: Mean iodine CNR was highest in 40-keV VMIs for all evaluated arteries. Across readers, the 50-keV VMI had the highest combined score (2.00 ± 1.11). Among different body parts, the 45-keV VMI was ranked highest for the head-and-neck (1.75 ± 0.68) and lower extremity (2.00 ± 1.41) CTA. Meanwhile, 50- and 55-keV VMIs were ranked highest for abdominal (2.50 ± 1.35 and 2.50 ± 1.56) CTA. The 40-keV VMI received the highest score for iodine visualization in vessels, and the 65-keV VMI for reduced metal/calcium-blooming artifacts. CONCLUSIONS: Quantitatively, VMIs at 40 keV had the highest CNR in major arterial vasculature using PCD-CTA. Based on radiologists' preference, the 45- and 50-keV VMIs were optimal for small body parts (eg, head and neck and lower extremity) and large body parts (eg, abdomen), respectively.

Rectal cancer pelvic recurrence: imaging patterns and key concepts to guide treatment planning.

For rectal cancer, MRI plays an important role in assessing extramural tumor spread and informs surgical planning. The contemporary standardized management of rectal cancer with total mesorectal excision guided by imaging-based risk stratification has dramatically improved patient outcomes. Colonoscopy and CT are utilized in surveillance after surgery to detect intraluminal and extramural recurrence, respectively; however, local recurrence of rectal cancer remains a challenge because postoperative changes such as fat necrosis and fibrosis can resemble tumor recurrence; additionally, mucinous adenocarcinoma recurrence may mimic fluid collection or abscess on CT. MRI and 18F-FDG PET are problem-resolving modalities for equivocal imaging findings on CT. Treatment options for recurrent rectal cancer include pelvic exenteration to achieve radical (R0 resection) resection and intraoperative radiation therapy. After pathologic diagnosis of recurrence, imaging plays an essential role for evaluating the feasibility and approach of salvage surgery. Patterns of recurrence can be divided into axial/central, anterior, lateral, and posterior. Some lateral and posterior recurrence patterns especially in patients with neurogenic pain are associated with perineural invasion. Cross-sectional imaging, especially MRI and 18F-FDG PET, permit direct visualization of perineural spread, and contribute to determining the extent of resection. Multidisciplinary discussion is essential for treatment planning of locally recurrent rectal cancer. This review article illustrates surveillance strategy after initial surgery, imaging patterns of rectal cancer recurrence based on anatomic classification, highlights imaging findings of perineural spread on each modality, and discusses how resectability and contemporary surgical approaches are determined based on imaging findings.

Pineal cyst: results of long-term MRI surveillance and analysis of growth and shrinkage rates.

OBJECTIVE: Pineal cyst (PC) is a relatively common true cyst in the pineal gland. Its long-term natural course remains ill defined. This study aims to evaluate the long-term natural history of PC and examine MRI risk factors for cyst growth and shrinkage to help better define which patients might benefit from surgical intervention. METHODS: The records and MRI of 409 consecutive patients with PC were retrospectively examined (nonsurgical cohort). Cyst growth and shrinkage were defined as a ≥ 2-mm increase and decrease in cyst diameter in any direction, respectively. In addition to size, MRI signal intensity ratios were analyzed. RESULTS: The median radiological follow-up period was 10.7 years (interquartile range [IQR] 6.4-14.3 years). The median change in maximal diameter was -0.6 mm (IQR -1.5 to 1.3 mm). During the observation period, cyst growth was confirmed in 21 patients (5.1%). Multivariate logistic regression analysis revealed that only age (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.93-0.99, p < 0.01) was significantly associated with cyst growth. No patient required resection during the observation period. Cyst shrinkage was confirmed in 57 patients (13.9%). Multivariate analysis revealed that maximal diameter (OR 1.22, 95% CI 1.12-1.35, p < 0.01) and cyst CSF T2 signal intensity ratio (OR 9.06, 95% CI 1.38-6.62 × 101, p = 0.02) were significantly associated with cyst shrinkage. CONCLUSIONS: Only 5% of PCs, mainly in patients younger than 50 years of age, have the potential to grow, while cyst shrinkage is more likely to occur across all age groups. Younger age is associated with cyst growth, while larger diameter and higher signal intensity on T2-weighted imaging are associated with shrinkage. Surgery is rarely needed for PCs, despite the possibility of a certain degree of growth.

Diagnostic Performance in Low- and High-Contrast Tasks of an Image-Based Denoising Algorithm Applied to Radiation Dose-Reduced Multiphase Abdominal CT Examinations.

BACKGROUND. Anatomic redundancy between phases can be used to achieve denoising of multiphase CT examinations. A limitation of iterative reconstruction (IR) techniques is that they generally require use of CT projection data. A frequency-split multi-band-filtration algorithm applies denoising to the multiphase CT images themselves. This method does not require knowledge of the acquisition process or integration into the reconstruction system of the scanner, and it can be implemented as a supplement to commercially available IR algorithms. OBJECTIVE. The purpose of the present study is to compare radiologists' performance for low-contrast and high-contrast diagnostic tasks (i.e., tasks for which differences in CT attenuation between the imaging target and its anatomic background are subtle or large, respectively) evaluated on multiphase abdominal CT between routine-dose images and radiation dose-reduced images processed by a frequency-split multiband-filtration denoising algorithm. METHODS. This retrospective single-center study included 47 patients who underwent multiphase contrast-enhanced CT for known or suspected liver metastases (a low-contrast task) and 45 patients who underwent multiphase contrast-enhanced CT for pancreatic cancer staging (a high-contrast task). Radiation dose-reduced images corresponding to dose reduction of 50% or more were created using a validated noise insertion technique and then underwent denoising using the frequency-split multi-band-filtration algorithm. Images were independently evaluated in multiple sessions by different groups of abdominal radiologists for each task (three readers in the low-contrast arm and four readers in the high-contrast arm). The noninferiority of denoised radiation dose-reduced images to routine-dose images was assessed using the jackknife alternative free-response ROC (JAFROC) figure-of-merit (FOM; limit of noninferiority, -0.10) for liver metastases detection and using the Cohen kappa statistic and reader confidence scores (100-point scale) for pancreatic cancer vascular invasion. RESULTS. For liver metastases detection, the JAFROC FOM for denoised radiation dose-reduced images was 0.644 (95% CI, 0.510-0.778), and that for routine-dose images was 0.668 (95% CI, 0.543-0.792; estimated difference, -0.024 [95% CI, -0.084 to 0.037]). Intraobserver agreement for pancreatic cancer vascular invasion was substantial to near perfect when the two image sets were compared (κ = 0.53-1.00); the 95% CIs of all differences in confidence scores between image sets contained zero. CONCLUSION. Multiphase contrast-enhanced abdominal CT images with a radiation dose reduction of 50% or greater that undergo denoising by a frequency-split multiband-filtration algorithm yield performance similar to that of routine-dose images for detection of liver metastases and vascular staging of pancreatic cancer. CLINICAL IMPACT. The image-based denoising algorithm facilitates radiation dose reduction of multiphase examinations for both low- and high-contrast diagnostic tasks without requiring manufacturer-specific hardware or software.

Understanding Reader Variability: A 25-Radiologist Study on Liver Metastasis Detection at CT.

Background Substantial interreader variability exists for common tasks in CT imaging, such as detection of hepatic metastases. This variability can undermine patient care by leading to misdiagnosis. Purpose To determine the impact of interreader variability associated with (a) reader experience, (b) image navigation patterns (eg, eye movements, workstation interactions), and (c) eye gaze time at missed liver metastases on contrast-enhanced abdominal CT images. Materials and Methods In a single-center prospective observational trial at an academic institution between December 2020 and February 2021, readers were recruited to examine 40 contrast-enhanced abdominal CT studies (eight normal, 32 containing 91 liver metastases). Readers circumscribed hepatic metastases and reported confidence. The workstation tracked image navigation and eye movements. Performance was quantified by using the area under the jackknife alternative free-response receiver operator characteristic (JAFROC-1) curve and per-metastasis sensitivity and was associated with reader experience and image navigation variables. Differences in area under JAFROC curve were assessed with the Kruskal-Wallis test followed by the Dunn test, and effects of image navigation were assessed by using the Wilcoxon signed-rank test. Results Twenty-five readers (median age, 38 years; IQR, 31-45 years; 19 men) were recruited and included nine subspecialized abdominal radiologists, five nonabdominal staff radiologists, and 11 senior residents or fellows. Reader experience explained differences in area under the JAFROC curve, with abdominal radiologists demonstrating greater area under the JAFROC curve (mean, 0.77; 95% CI: 0.75, 0.79) than trainees (mean, 0.71; 95% CI: 0.69, 0.73) (P = .02) or nonabdominal subspecialists (mean, 0.69; 95% CI: 0.60, 0.78) (P = .03). Sensitivity was similar within the reader experience groups (P = .96). Image navigation variables that were associated with higher sensitivity included longer interpretation time (P = .003) and greater use of coronal images (P < .001). The eye gaze time was at least 0.5 and 2.0 seconds for 71% (266 of 377) and 40% (149 of 377) of missed metastases, respectively. Conclusion Abdominal radiologists demonstrated better discrimination for the detection of liver metastases on abdominal contrast-enhanced CT images. Missed metastases frequently received at least a brief eye gaze. Higher sensitivity was associated with longer interpretation time and greater use of liver display windows and coronal images. © RSNA, 2022 Online supplemental material is available for this article.

Lung Cancer Screening Using Clinical Photon-Counting Detector Computed Tomography and Energy-Integrating-Detector Computed Tomography: A Prospective Patient Study.

OBJECTIVE: To evaluate the diagnostic quality of photon-counting detector (PCD) computed tomography (CT) in patients undergoing lung cancer screening compared with conventional energy-integrating detector (EID) CT in a prospective multireader study. MATERIALS: Patients undergoing lung cancer screening with conventional EID-CT were prospectively enrolled and scanned on a PCD-CT system using similar automatic exposure control settings and reconstruction kernels. Three thoracic radiologists blinded to CT system compared PCD-CT and EID-CT images and scored examinations using a 5-point Likert comparison score (-2 [left image is worse] to +2 [left image is better]) for artifacts, sharpness, image noise, diagnostic image quality, emphysema visualization, and lung nodule evaluation focusing on the border. Post hoc correction of Likert scores was performed such that they reflected PCD-CT performance in comparison to EID-CT. A nonreader radiologist measured objective image noise. RESULTS: Thirty-three patients (mean, 66.9 ± 5.6 years; 11 female; body mass index; 30.1 ± 5.1 kg/m 2 ) were enrolled. Mean volume CT dose index for PCD-CT was lower (0.61 ± 0.21 vs 0.73 ± 0.22; P < 0.001). Pooled reader results showed significant differences between imaging modalities for all comparative rankings ( P < 0.001), with PCD-CT favored for sharpness, image noise, image quality, and emphysema visualization and lung nodule border, but not artifacts. Photon-counting detector CT had significantly lower image noise (74.4 ± 10.5 HU vs 80.1 ± 8.6 HU; P = 0.048). CONCLUSIONS: Photon-counting detector CT with similar acquisition and reconstruction settings demonstrated improved image quality and less noise despite lower radiation dose, with improved ability to depict pulmonary emphysema and lung nodule borders compared with EID-CT at low-dose lung cancer CT screening.

Mucinous cystic neoplasms of the liver with biliary prolapse.

OBJECTIVES: To describe the prevalence, clinical and radiological findings of biliary prolapse in pathologically proven mucinous cystic neoplasm of the liver (MCN-L). METHODS: Thirty-four patients, all female with median age 50 years (range, 14-82), with histologically confirmed MCN-L were enrolled. Median tumor size was 9 cm (range, 2-21 cm). Fifty-seven examinations (17 ultrasound, 25 CT, and 15 MR) among 34 MCN-Ls were reviewed. Two radiologists retrospectively assessed images for tumor location, size and other morphological features of the tumor, presence of biliary prolapse and upstream bile duct dilatation. Ultrasound, CT, and MR were assessed separately. Clinical features were evaluated. Clinical and radiological characteristics of MCN-L with and without biliary prolapse were compared. RESULTS: 15% (5/34) of MCN-Ls showed biliary prolapse confirmed at pathology. None of MCN-Ls were associated with invasive carcinoma. Patients with biliary prolapse were significantly younger than those without (median 27 years [22-56] vs. median 51 years [14-82], p = 0.03). MCN-Ls with biliary prolapse were significantly smaller than those without (median 6.4 cm [2.2-7.5] vs. median 9.6 cm [3.1-21], p = 0.01). The upstream bile duct was dilated more frequently in MCN-Ls with biliary prolapse (100% vs. 38%, p = 0.02). Jaundice was significantly more common in MCN-Ls with biliary prolapse (80 vs 3%, p = 0.0005). Other clinical or radiological features were not significantly different between two groups. CONCLUSIONS: Biliary prolapse was found in 15% of MCN-Ls. MCN-Ls with biliary prolapse were significantly smaller and were more commonly associated with upstream bile duct dilation and jaundice than those without biliary prolapse.

Individualized and generalized models for predicting observer performance on liver metastasis detection using CT.

Purpose: Radiologists exhibit wide inter-reader variability in diagnostic performance. This work aimed to compare different feature sets to predict if a radiologist could detect a specific liver metastasis in contrast-enhanced computed tomography (CT) images and to evaluate possible improvements in individualizing models to specific radiologists. Approach: Abdominal CT images from 102 patients, including 124 liver metastases in 51 patients were reconstructed at five different kernels/doses using projection domain noise insertion to yield 510 image sets. Ten abdominal radiologists marked suspected metastases in all image sets. Potentially salient features predicting metastasis detection were identified in three ways: (i) logistic regression based on human annotations (semantic), (ii) random forests based on radiologic features (radiomic), and (iii) inductive derivation using convolutional neural networks (CNN). For all three approaches, generalized models were trained using metastases that were detected by at least two radiologists. Conversely, individualized models were trained using each radiologist's markings to predict reader-specific metastases detection. Results: In fivefold cross-validation, both individualized and generalized CNN models achieved higher area under the receiver operating characteristic curves (AUCs) than semantic and radiomic models in predicting reader-specific metastases detection ability ( p < 0.001 ). The individualized CNN with an AUC of mean (SD) 0.85(0.04) outperformed the generalized one [ AUC = 0.78 ( 0.06 ) , p = 0.004 ]. The individualized semantic [ AUC = 0.70 ( 0.05 ) ] and radiomic models [ AUC = 0.68 ( 0.06 ) ] outperformed the respective generalized versions [semantic AUC = 0.66 ( 0.03 ) , p = 0.009 ; radiomic AUC = 0.64 ( 0.06 ) , p = 0.03 ]. Conclusions: Individualized models slightly outperformed generalized models for all three feature sets. Inductive CNNs were better at predicting metastases detection than semantic or radiomic features. Generalized models have implementation advantages when individualized data are unavailable.

Photon-Counting Detector CT: Key Points Radiologists Should Know.

Photon-counting detector (PCD) CT is a new CT technology utilizing a direct conversion X-ray detector, where incident X-ray photon energies are directly recorded as electronical signals. The design of the photon-counting detector itself facilitates improvements in spatial resolution (via smaller detector pixel design) and iodine signal (via count weighting) while still permitting multi-energy imaging. PCD-CT can eliminate electronic noise and reduce artifacts due to the use of energy thresholds. Improved dose efficiency is important for low dose CT and pediatric imaging. The ultra-high spatial resolution of PCD-CT design permits lower dose scanning for all body regions and is particularly helpful in identifying important imaging findings in thoracic and musculoskeletal CT. Improved iodine signal may be helpful for low contrast tasks in abdominal imaging. Virtual monoenergetic images and material classification will assist with numerous diagnostic tasks in abdominal, musculoskeletal, and cardiovascular imaging. Dual-source PCD-CT permits multi-energy CT images of the heart and coronary arteries at high temporal resolution. In this special review article, we review the clinical benefits of this technology across a wide variety of radiological subspecialties.