A prototype assembled 3D-printed phantom of the glenohumeral joint for fluoroscopic-guided shoulder arthrography.

PURPOSE: To describe the methodology of constructing a three-dimensional (3D) printed model of the glenohumeral joint, to serve as an interventional phantom for fluoroscopy-guided shoulder arthrography training. MATERIALS AND METHODS: The osseous structures, intra-articular space and skin surface of the shoulder were digitally extracted as separate 3D meshes from a normal CT arthrogram of the shoulder, using commercially available software. The osseous structures were 3D-printed in gypsum, a fluoroscopically radiopaque mineral, using binder jet technology. The joint capsule was 3D printed with rubber-like TangoPlus material, using PolyJet technology. The capsule was secured to the humeral head and glenoid to create a sealed intra-articular space. A polyamide mold of the skin was printed using selective laser sintering. The joint was stabilized inside the mold, and the surrounding soft tissues were cast in silicone of varying densities. Fluoroscopically-guided shoulder arthrography was performed using anterior, posterior, and rotator interval approaches. CT arthrographic imaging of the phantom was also performed. RESULTS: A life-size phantom of the glenohumeral joint was constructed. The radiopaque osseous structures replicated in-vivo osseous corticomedullary differentiation, with dense cortical bone and less dense medullary cancellous bone. The glenoid labrum was successfully integrated into the printed capsule, and visualized on CT arthrography. The phantom was repeatedly used to perform shoulder arthrography using all three conventional approaches, and simulated the in vivo challenges of needle guidance. CONCLUSIONS: 3D printing of a complex capsule, such as the glenohumeral joint, is possible with this technique. Such a model can serve as a valuable training tool.

Prevalence of Low-Attenuation Homogeneous Papillary Renal Cell Carcinoma Mimicking Renal Cysts on CT.

OBJECTIVE: The objective of our study was to determine the attenuation range of homogeneous papillary renal cell carcinomas (RCCs) on contrast-enhanced CT. MATERIALS AND METHODS: This retrospective study was performed at two institutions from January 1, 2007, to January 1, 2017. Multiphasic CT studies with and without IV contrast material of 114 patients with pathologically proven papillary RCCs were independently reviewed by two sets of two abdominal radiologists. Seventy-two cases were excluded because of subjective lesion heterogeneity, leaving 42 homogeneous RCCs. Three ROIs were placed on all lesions for all CT phases, and the mean attenuations were calculated. RESULTS: Mean lesion size was 2.8 cm (range, 1.2-11.0 cm). The attenuation range for each CT phase was as follows: unenhanced, 14.7-50.7 HU; corticomedullary, 32.2-99.5 HU; portal venous, 40.8-95.1 HU; nephrographic, 17.9-90.8 HU; and excretory, 18.0-73.0 HU. Two of 114 (1.8%; 95% CI, 0.2-6.5%) RCCs were homogeneous and less than 30 HU on the portal venous or nephrographic phase. One of these RCCs was a solid hypoenhancing mass, and the other was a homogeneous cystic RCC. Of the cases with an unenhanced phase, three of 107 (2.8%; 95% CI, 0.6-8.8%) were both homogeneous and were less than 20 HU in attenuation. CONCLUSION: Papillary RCCs are rarely both subjectively homogeneous and less than 20 HU at unenhanced CT and less than 30 HU at portal venous or nephrographic phase CT.

Comparing Dose-Length Product-Based and Monte Carlo Simulation Organ-Based Calculations of Effective Dose in 16- and 64-MDCT Examinations Using Automatic Tube Current Modulation.

OBJECTIVE: The purpose of this study is to compare dose-length product (DLP)-based calculation of effective dose (EDDLP) with Monte Carlo simulation organ-based calculation of effective dose (EDMCO) in 16- and 64-MDCT examinations, with the use of clinical examinations with automatic tube current modulation. MATERIALS AND METHODS: Dose data were obtained from 50 consecutive unenhanced head CT examinations, unenhanced chest CT examinations, and unenhanced and contrast-enhanced abdominopelvic CT examinations performed using 16- and 64-MDCT scanners, as well as from 50 pulmonary CT angiography (CTA) examinations performed using a 64-MDCT scanner and 31 pulmonary CTA examinations performed using a 16-MDCT scanner. The EDMCO and the mean patient effective diameter were calculated using commercially available software. The EDDLP was also calculated. Both the mean difference and percentage difference between EDDLP and EDMCO were calculated, and they were statistically compared according to patient sex, type of examination performed, and type of scanner used. RESULTS: EDDLP significantly underestimated the EDMCO by 0.3 mSv (19%) for men who underwent unenhanced head CT, 0.5 mSv (29%) for women who underwent unenhanced head CT, 0.9-1.4 mSv (9-13%) for men who underwent chest CT, and 4.7-4.8 mSv (39%) for women who underwent chest CT (p < 0.001). The EDDLP overestimated the EDMCO by 1.9-2.0 mSv (12-14%) for men who underwent abdominopelvic CT (p < 0.001), with no significant difference noted for women who underwent abdominopelvic CT's. No significant difference was noted in the percentage difference in ED between the 16- and 64-MDCT scanners (p ≥ 0.13). CONCLUSION: EDDLP underestimates EDMCO, the reference standard for dose calculation, by 19-39% in unenhanced head CT examinations and, among women, in chest CT examinations. EDDLP deviates from EDMCO by less than 15% for chest CT examinations of men and for abdominopelvic CT. These differences can be attributed to variable patient body habitus, automatic tube current modulation, and sex-neutral k-coefficients, and they should be considered when calculating ED, particularly in women.

CT of suspected thoracic acute aortic injury in the emergency department: is routine abdominopelvic imaging worth the additional collective radiation dose?

This study aimed to determine the incidence of non-traumatic acute aortic injury (AAI) extending from the chest into the abdomen or pelvis in emergency department (ED) patients with acute aortic syndrome (AAS), to estimate the effective dose of the abdominopelvic portion of these CT exams, and to compare the number needed to screen (NNS) with the collective population radiation dose of imaging those stations. All patients (n = 238) presenting to the ED with AAS between March 2014 and June 2015 who were imaged per CT AAI protocol (noncontrast and contrast-enhanced CT angiography of the chest, abdomen, and pelvis) were retrospectively identified in this IRB-approved HIPAA-compliant study. The Stanford classification for positive cases of AAI was further subclassified based on chest, abdominal, or pelvic involvement. The dose length product (DLP) of each exam was used to estimate the dose of the abdominal and pelvic stations and the collective effective dose for the population. There were five cases of aortic dissection (AD) and two of intramural hematoma (IMH), with an AAI incidence of 2.9/100. Three cases of AAI were confined to the chest. Two cases of AAI were confined to the chest and abdomen, and two cases involved the chest, abdomen, and pelvis. There was only one case of AAI involving the ascending aorta that extended into the abdomen or pelvis. The number needed to screen to identify (a) AAI extending from the chest into the abdomen or pelvis was 59.5 and (b) Stanford A AAI extending into the abdomen or pelvis was 238. The estimated mean effective dose for the abdominopelvic stations were unenhanced abdomen 2.3 mSv, unenhanced pelvis 3.3 mSv, abdominal CTA 2.5 mSv, and pelvic CTA 3.6 mSv. The collective effective doses to the abdomen and pelvis with unenhanced CT and CTA in 59.5 patients and 238 patients were 761.6 and 3046.4 mSv, respectively. While the estimated mean effective dose for imaging of the abdominopelvic stations are low, the collective effective dose should also be considered. It may be beneficial to modify or omit routine unenhanced CT and/or CTA of the abdomen/pelvis in this patient population in the absence of abdominal symptoms, and image the abdomen and pelvis in positive thoracic cases only.

Multiparametric MRI of the prostate gland: technical aspects.

With recent technological advancements, multiparametric MRI (mpMRI) has evolved into an important tool in the detection, localization and staging of prostate cancer. Optimization of image quality is paramount to mpMRI technique. While PI-RADS version 2 established guidelines for minimum technical parameters, there is no uniformity in mpMRI protocols across institutions. This review will discuss the key sequences that comprise a mpMRI exam. Technical factors that affect image quality, such as pre-exam patient preparation, magnet field strength, endorectal coil utilization and sequence parameters will also be examined. Several emerging technologies with potential to aid in the maturation of mpMRI will be introduced.

Hemoglobin, Albumin, Lymphocyte, and Platelet Count is a Significant Biomarker Surrogate for Nutritional Status to Predict Overall Survival in Patients Post-radical Cystectomy.

INTRODUCTION: Nutritional status is an independent predictor of overall survival after radical cystectomy. Various biomarkers of nutritional status are proposed to predict postoperative outcome, including albumin, anemia, thrombocytopenia, and sarcopenia. Recently, a score comprising hemoglobin, albumin, lymphocyte, and platelet counts was postulated as an encompassing biomarker to predict overall survival post-radical cystectomy in a single-institution study. However, cutoffs for hemoglobin, albumin, lymphocyte, and platelet count are not well defined. In this study, we analyzed hemoglobin, albumin, lymphocyte, and platelet count thresholds predicting overall survival and examined the platelet-to-lymphocyte as an additional prognostic biomarker. METHODS: Fifty radical cystectomy patients were retrospectively evaluated from 2010-2021. American Society of Anesthesiologists classification, pathological data, and survival were extracted from our institutional registry. Univariable and multivariable Cox regression analysis was fit to the data to predict overall survival. RESULTS: Median follow-up was 22 (12-54) months. Hemoglobin, albumin, lymphocyte, and platelet count (continuous) was a significant predictor of overall survival on multivariable Cox regression analysis (HR 0.95, 95% CI: 0.90-0.99, P = .03), adjusting for Charlson Comorbidity Index, lymphadenopathy (pN >N0), muscle-invasive disease, and neoadjuvant chemotherapy. Optimal hemoglobin, albumin, lymphocyte, and platelet count cutoff was 25.0. Patients with hemoglobin, albumin, lymphocyte, and platelet count <25.0 had inferior overall survival (median, 33 months) vs with those with hemoglobin, albumin, lymphocyte, and platelet count ≥25.0 (median, not reached) (P = .03). CONCLUSIONS: Low hemoglobin, albumin, lymphocyte, and platelet count <25.0 was an independent predictor of inferior overall survival.

Role of Race and Insurance Status in Prostate Cancer Diagnosis-to-Treatment Interval.

INTRODUCTION: Numerous studies have shown that both race and insurance status may affect prostate cancer (PCa) workup and treatment. Preliminary investigations have shown that these factors may be associated with treatment delays, which may indicate inequitable care and increase risk of tumor progression. This investigation aimed to assess whether race and insurance impacted the interval between multiparametric MRI (mpMRI)-to-biopsy, and biopsy-to-prostatectomy. MATERIALS AND METHODS: A single-institution analysis of 261 patients with recorded race and insurance data was performed using an Institutional Review Board-compliant database with information spanning from 2016 to 2022. Race was self-reported during intake, and insurance status was retrieved from the electronic medical record. Insurance was sub-divided into private, Medicare, and Medicaid. Diagnostic or treatment latency was defined as time between mpMRI-to-biopsy, or biopsy-to-surgery. RESULTS: Stratified by race, there was no difference in either latency period when comparing African American (AA) and white patients. Stratified by insurance status, there was no difference in time from mpMRI-to-biopsy (P = .50), but there was a significantly longer interval from biopsy-to-prostatectomy for patients with Medicaid insurance (P = .02). Patients with Medicaid waited on average 168 days to receive surgery, in contrast to 92 days for private and 87 for Medicare. Notably, 82% of Medicaid patients were AA. CONCLUSION: Insurance status, which is inherently linked to race and social determinants of health, portended a significantly increased interval between biopsy and surgery. Physicians should be aware of the relationship between insurance status and treatment delay, as well as its potential downstream consequences.

Prediction of histologic grade and type of small (< 4 cm) papillary renal cell carcinomas using texture and neural network analysis: a feasibility study.

OBJECTIVE: To predict the histologic grade and type of small papillary renal cell carcinomas (pRCCs) using texture analysis and machine learning algorithms. METHODS: This was a retrospective HIPAA-compliant study. 24 noncontrast (NC), 22 corticomedullary (CM) phase, and 24 nephrographic (NG) phase CTs of small (< 4 cm) surgically resected pRCCs were identified. Surgical pathology classified the tumors as low- or high-Fuhrman histologic grade and type 1 or 2. The axial image with the largest cross-sectional tumor area was exported and segmented. Six histogram and 31 texture (20 gray-level co-occurrences and 11 gray-level run-lengths) features were calculated for each tumor in each phase. Feature values in low- versus high-grade and type 1 versus 2 pRCCs were compared. Area under the receiver operating curve (AUC) was calculated for each feature to assess prediction of histologic grade and type of pRCCs in each phase. Histogram, texture, and combined histogram and texture feature sets were used to train and test three classification algorithms (support vector machine (SVM), random forest, and histogram-based gradient boosting decision tree (HGBDT)) with stratified shuffle splits and threefold cross-validation; AUCs were calculated for each algorithm in each phase to assess prediction of histologic grade and type of pRCCs. RESULTS: Individual histogram and texture features did not have statistically significant differences between low- and high-grade or type 1 and type 2 pRCCs across all phases. Individual features had low predictive power for tumor grade or type in all phases (AUC < 0.70). HGBDT was highly accurate at predicting pRCC histologic grade and type using histogram, texture or combined histogram and texture feature data from the CM phase (AUCs = 0.97-1.0). All algorithms had highest AUCs using CM phase feature data sets; AUCs decreased using feature sets from NC or NG phases. CONCLUSIONS: The histologic grade and type of small pRCCs can be predicted with classification algorithms using CM histogram and texture features, which outperform NC and NG phase image data. The accurate prediction of pRCC histologic grade and type may be able to further guide management of patients with small (< 4 cm) pRCCs being considered for active surveillance.

Three contrast injection protocols for electrocardiogram-gated 64-slice computed tomographic angiography: comparing vessel density and perceived quality.

OBJECTIVE: To compare aortic, pulmonary artery (PA), and coronary artery (CA) density and examination quality using 3 different injection protocols for electrocardiogram-gated 64-detector row computed tomographic angiography. METHODS: We reviewed 30 consecutive computed tomographic angiography studies for each of 3 different contrast protocols (A, B, and C)-90 studies total-performed in patients with chest pain and low to moderate suspicion for coronary disease. All used a 20-mL timing bolus followed by 30 mL of saline. Protocol A (PrA) was composed of 50-mL contrast at 5 mL/s, 40-mL contrast/10-mL saline at 4 mL/s, and 40-mL saline at 4 mL/s. Protocol B (PrB) was composed of 50-mL contrast at 5 mL/s, 30- to 50-mL contrast at 3.5 mL/s (timing bolus-dependent), and 50-mL saline at 3.5 mL/s. Protocol C (PrC) was composed of 60-mL contrast at 5.5 mL/s, 50-mL contrast at 4.5 mL/s, and 50-mL saline at 3.5 mL/s. Density measurements were made at 20 points. Studies were graded for quality on a 4-point scale. RESULTS: Main PA density for PrA (263 Hounsfield units [HU]) was significantly lower than for PrB (335 HU) and PrC (366 HU). For PrA, PrB, and PrC, there were 10, 1, and 1 nondiagnostic PA studies, respectively; the numbers of good or very good quality studies were 10, 21, and 25. Left main CA densities for PrA (393 HU), PrB (353 HU), and PrC (356 HU) were not significantly different; likewise for aortic root densities (400, 375, and 372 HU). For the aortic root, the numbers of good or very good studies were 30, 27, and 28. Grade (G) is linearly related to average density per grade (D): G = 0.011 × D - 1.46, r = 0.96. CONCLUSIONS: Protocols B and C yielded consistently high attenuation of the aorta, PAs, and CAs with commensurate examination quality.

Texture analysis and machine learning algorithms accurately predict histologic grade in small (< 4 cm) clear cell renal cell carcinomas: a pilot study.

PURPOSE: To predict the histologic grade of small clear cell renal cell carcinomas (ccRCCs) using texture analysis and machine learning algorithms. METHODS: Fifty-two noncontrast (NC), 26 corticomedullary (CM) phase, and 35 nephrographic (NG) phase CTs of small (< 4 cm) surgically resected ccRCCs were retrospectively identified. Surgical pathology classified the tumors as low- or high-Fuhrman histologic grade. The axial image with the largest cross-sectional tumor area was exported and segmented. Six histogram and 31 texture (gray-level co-occurrences (GLC) and gray-level run-lengths (GLRL)) features were calculated for each tumor in each phase. T testing compared feature values in low- and high-grade ccRCCs, with a (Benjamini-Hochberg) false discovery rate of 10%. Area under the receiver operating curve (AUC) was calculated for each feature to assess prediction of low- and high-grade ccRCCs in each phase. Histogram, texture, and combined histogram and texture data sets were used to train and test four algorithms (k-nearest neighbor (KNN), support vector machine (SVM), random forests, and decision tree) with tenfold cross-validation; AUCs were calculated for each algorithm in each phase to assess prediction of low- and high-grade ccRCCs. RESULTS: Zero, 23, and 0 features in the NC, CM, and NG phases had statistically significant differences between low and high-grade ccRCCs. CM histogram skewness and GLRL short run emphasis had the highest AUCs (0.82) in predicting histologic grade. All four algorithms had the highest AUCs (0.97) predicting histologic grade using CM histogram features. The algorithms' AUCs decreased using histogram or texture features from NC or NG phases. CONCLUSION: The histologic grade of small ccRCCs can be accurately predicted with machine learning algorithms using CM histogram features, which outperform NC and NG phase image data.

Angiographic changes following the use of a purse-string suture hemostasis device in hemodialysis access interventions.

PURPOSE: To evaluate late angiographic changes at the puncture site with use of a suture lock device for hemostasis after hemodialysis access interventions. MATERIALS AND METHODS: Thirty-five patients who underwent percutaneous intervention of a failing or thrombosed access had 76 puncture sites (58 grafts, 15 fistulas, three composite) managed with a purse-string suture lock device. All patients had follow-up fistulograms available for analysis. Fistulograms at the site of sheath insertion were retrospectively compared with those obtained during subsequent hemodialysis access procedures to assess for changes in access lumen diameter. Access type, sheath size, and heparin dose were examined as predictors of access diameter change at the puncture site. RESULTS: The mean time to follow-up fistulography was 4.7 months; the cumulative observation time of the patient cohort was 30.5 dialysis years. The mean change in access diameter at the previous puncture site was -0.3%. No puncture sites became aneurysmal or stenotic during follow-up. Two of the 76 puncture sites (both grafts) developed mild (+28%) and moderate (+43%) bulging at the sheath site. The remaining 74 puncture sites (97%) showed no significant change in access diameter. The mean change in access diameter among fistulas was -6.2%, and that among grafts was +1.5% (P = .06). Neither sheath size (P = .26) nor heparin dose (P = .48) had an effect on access diameter. CONCLUSIONS: No patients developed aneurysms or stenosis at the puncture site after use of a suture lock device for hemostasis. This technique is consistent, safe, and effective in obtaining hemostasis after dialysis access interventions of fistulas and grafts.

Retinal vasculitis with Chronic Recurrent Multifocal Osteomyelitis: a case report and review of the literature.

BACKGROUND: Concurrent presentation of retinal vasculitis with mixed sclerotic and lytic bone lesions is rare. CASE PRESENTATION: We present the case of a 37-year old woman with a several year history of episodic sternoclavicular pain who presented for rheumatologic evaluation due to a recent diagnosis of retinal vasculitis. We review the differential diagnosis of retinal vasculitis, along with the differential diagnosis of mixed sclerotic and lytic bone lesions. Ultimately, bone marrow biopsy confirmed diagnosis of chronic recurrent multifocal osteomyelitis (CRMO). Concurrent presentation of CRMO with retinal vasculitis is extremely rare but important to recognize. The patient demonstrated clinical response to prednisone and tumor necrosis factor-alpha inhibition (TNF-i). CONCLUSION: This case reports and unusual presentation of CRMO spectrum disease involving the sternum and sternoclavicular joint with concurrent retinal vasculitis.

An unusual case of fatty posterior mediastinal ganglioneuroma.

Ganglioneuromas, which arise from neural crest cells, are typically seen in adolescent and young adults. We describe an unusual case of posterior mediastinal ganglioneuroma with a large fatty component in a middle-aged male. This imaging feature has only been reported in five published manuscripts in the English literature.

The Transaxial Orientation Is Superior to Both the Short Axis and Horizontal Long Axis Orientations for Determining Right Ventricular Volume and Ejection Fraction Using Simpson's Method with Cardiac Magnetic Resonance.

We sought to determine which of the three orientations is the most reliable and accurate for quantifying right ventricular (RV) volume and ejection fraction (EF) by cardiac magnetic resonance using Simpson's method. We studied 20 patients using short axis (SA), transaxial (TA), and horizontal long axis (HLA) orientations. Three readers independently traced RV endocardial contours at end-diastole and end-systole for each orientation. End-diastolic volumes (EDVs), end-systolic volumes (ESVs), and EF were calculated and compared with the 3D piecewise smooth subdivision surface (PSSS) method. The intraclass correlation coefficients among the 3 readers for EDV, ESV, and EF were 0.92, 0.82, and 0.42, respectively, for SA, 0.95, 0.92, and 0.67 for TA, and 0.85, 0.93, and 0.69 for HLA. For mean data there was no significant difference between TA and PSSS for EDV (-2.6%, 95% CI: -8.2 to 3.3%), ESV (-5.9%, -15.2 to 4.5%), and EF (1.7%, -1.5 to 4.9%). HLA was accurate for ESV (-8.9%, -18.5 to 1.8%) and EF (-0.7%, -3.8 to 2.5%) but significantly underestimated EDV (-9.8, -16.6 to -2.4%). SA was accurate for EDV (0.5%, -6.0 to 7.5%) but overestimated ESV (10.5%, 0.1 to 21.9%) and had poor interrater reliability for EF. Conclusions. The TA orientation provides the most reliable and accurate measures of EDV, ESV, and EF.

Adrenal imaging: a comprehensive review.

The discovery of an incidental adrenal mass (adrenal incidentaloma) continues to rise with the increasing use of cross-sectional imaging. Although most adrenal lesions are benign and asymptomatic, radiologists should guide evaluation of these lesions, whether benign or malignant. This article reviews the various imaging techniques used to evaluate adrenal masses and their relative strengths and weaknesses. It focuses on the most prevalent adrenal pathologies and their typical imaging characteristics, and concludes with a brief discussion of developing techniques, including diffusion-weighted imaging and dual-energy CT.