Spontaneous hepatic arterioportal fistula in extrahepatic portal vein obstruction: Combined endovascular and surgical management

Hepatic arterioportal fistulae are abnormal communications between the hepatic artery and portal vein. They are reported to be congenital or acquired secondary to trauma, iatrogenic procedures, hepatic cirrhosis, and hepatocellular carcinoma, but less likely to occur spontaneously. Extrahepatic portal venous obstruction (EHPVO) can lead to pre-hepatic portal hypertension. A spontaneous superimposed hepatic arterioportal fistula can lead to pre-sinusoidal portal hypertension, further exacerbating its physiology. This report describes a young woman with long-standing EHPVO presenting with repeated upper gastrointestinal variceal bleeding and symptomatic hypersplenism. Computed tomography scan demonstrated a cavernous transformation of the portal vein and a macroscopic hepatic arterioportal fistula between the left hepatic artery and portal vein collateral in the central liver. The hepatic arterioportal fistula was associated with a flow-related left hepatic artery aneurysm and a portal venous collateral aneurysm proximal and distal to the fistula, respectively. Endovascular coiling was performed for the hepatic arterioportal fistula, followed by proximal splenorenal shunt procedure. This case illustrates an uncommon association of a spontaneous hepatic arterioportal fistula with EHPVO and the utility of a combined endovascular and surgical approach for managing multifactorial non-cirrhotic portal hypertension in such patients.

Magnetic Resonance Fingerprinting: A Review of Clinical Applications

ABSTRACT

Magnetic resonance fingerprinting (MRF) is an approach to quantitative magnetic resonance imaging that allows for efficient simultaneous measurements of multiple tissue properties, which are then used to create accurate and reproducible quantitative maps of these properties. As the technique has gained popularity, the extent of preclinical and clinical applications has vastly increased. The goal of this review is to provide an overview of currently investigated preclinical and clinical applications of MRF, as well as future directions. Topics covered include MRF in neuroimaging, neurovascular, prostate, liver, kidney, breast, abdominal quantitative imaging, cardiac, and musculoskeletal applications.

Non-Contrast Magnetic Resonance Angiography: Techniques, Principles, and Applications

Several non-contrast magnetic resonance angiography (MRA) techniques have been developed, providing an attractive alternative to contrast-enhanced MRA and a radiation-free alternative to computed tomography (CT) CT angiography. This review describes the physical principles, limitations, and clinical applications of bright-blood (BB) non-contrast MRA techniques. The principles of BB MRA techniques can be broadly divided into (a) flow-independent MRA, (b) blood-inflow-based MRA, (c) cardiac phase dependent, flow-based MRA, (d) velocity sensitive MRA, and (e) arterial spin-labeling MRA. The review also includes emerging multi-contrast MRA techniques that provide simultaneous BB and black-blood images for combined luminal and vessel wall evaluation.

Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis

BACKGROUND & AIMS

Our purpose was to detect pancreatic ductal adenocarcinoma (PDAC) at the prediagnostic stage (3-36 months before clinical diagnosis) using radiomics-based machine-learning (ML) models, and to compare performance against radiologists in a case-control study.

METHODS

Volumetric pancreas segmentation was performed on prediagnostic computed tomography scans (CTs) (median interval between CT and PDAC diagnosis: 398 days) of 155 patients and an age-matched cohort of 265 subjects with normal pancreas. A total of 88 first-order and gray-level radiomic features were extracted and 34 features were selected through the least absolute shrinkage and selection operator-based feature selection method. The dataset was randomly divided into training (292 CTs: 110 prediagnostic and 182 controls) and test subsets (128 CTs: 45 prediagnostic and 83 controls). Four ML classifiers, k-nearest neighbor (KNN), support vector machine (SVM), random forest (RM), and extreme gradient boosting (XGBoost), were evaluated. Specificity of model with highest accuracy was further validated on an independent internal dataset (n = 176) and the public National Institutes of Health dataset (n = 80). Two radiologists (R4 and R5) independently evaluated the pancreas on a 5-point diagnostic scale.

RESULTS

Median (range) time between prediagnostic CTs of the test subset and PDAC diagnosis was 386 (97-1092) days. SVM had the highest sensitivity (mean; 95% confidence interval) (95.5; 85.5-100.0), specificity (90.3; 84.3-91.5), F1-score (89.5; 82.3-91.7), area under the curve (AUC) (0.98; 0.94-0.98), and accuracy (92.2%; 86.7-93.7) for classification of CTs into prediagnostic versus normal. All 3 other ML models, KNN, RF, and XGBoost, had comparable AUCs (0.95, 0.95, and 0.96, respectively). The high specificity of SVM was generalizable to both the independent internal (92.6%) and the National Institutes of Health dataset (96.2%). In contrast, interreader radiologist agreement was only fair (Cohen's kappa 0.3) and their mean AUC (0.66; 0.46-0.86) was lower than each of the 4 ML models (AUCs: 0.95-0.98) (P < .001). Radiologists also recorded false positive indirect findings of PDAC in control subjects (n = 83) (7% R4, 18% R5).

CONCLUSIONS

Radiomics-based ML models can detect PDAC from normal pancreas when it is beyond human interrogation capability at a substantial lead time before clinical diagnosis. Prospective validation and integration of such models with complementary fluid-based biomarkers has the potential for PDAC detection at a stage when surgical cure is a possibility.

Multicenter Repeatability and Reproducibility of MR Fingerprinting in Phantoms and in Prostatic Tissue

PURPOSE

To evaluate multicenter repeatability and reproducibility of T1 and T2 maps generated using MR fingerprinting (MRF) in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and in prostatic tissues.

METHODS

MRF experiments were performed on 5 different 3 Tesla MRI scanners at 3 different institutions: University Hospitals Cleveland Medical Center (Cleveland, OH), Brigham and Women's Hospital (Boston, MA) in the United States, and Diagnosticos da America (Rio de Janeiro, RJ) in Brazil. Raw MRF data were reconstructed using a Gadgetron-based MRF online reconstruction pipeline to yield quantitative T1 and T2 maps. The repeatability of T1 and T2 values over 6 measurements in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom was assessed to demonstrate intrascanner variation. The reproducibility between the 4 clinical scanners was assessed to demonstrate interscanner variation. The same-day test-retest normal prostate mean T1 and T2 values from peripheral zone and transitional zone were also compared using the intraclass correlation coefficient and Bland-Altman analysis.

RESULTS

The intrascanner variation of values measured using MRF was less than 2% for T1 and 4.7% for T2 for relaxation values, within the range of 307.7 to 2360 ms for T1 and 19.1 to 248.5 ms for T2 . Interscanner measurements showed that the T1 variation was less than 4.9%, and T2 variation was less than 8.1% between multicenter scanners. Both T1 and T2 values in in vivo prostatic tissue demonstrated high test-retest reliability (intraclass correlation coefficient > 0.92) and strong linear correlation (R2  > 0.840).

CONCLUSION

Prostate MRF measurements of T1 and T2 are repeatable and reproducible between MRI scanners at different centers on different continents for the above measurement ranges.

MR fingerprinting of the prostate

Multiparametric magnetic resonance imaging (mpMRI) has been adopted as the key tool for detection, localization, characterization, and risk stratification of patients suspected to have prostate cancer. Despite advantages over systematic biopsy, the interpretation of prostate mpMRI has limitations including a steep learning curve, leading to considerable interobserver variation. There is growing interest in clinical translation of quantitative imaging techniques for more objective lesion assessment. However, traditional mapping techniques are slow, precluding their use in the clinic. Magnetic resonance fingerprinting (MRF) is an efficient approach for quantitative maps of multiple tissue properties simultaneously. The T₁ and T₂ values obtained with MRF have been validated with phantom studies as well as in normal volunteers and patients. Studies have shown that MRF-derived T₁ and T₂ along with ADC values are all significant independent predictors in the differentiation between normal prostate tissue and prostate cancer, and hold promise in differentiating low and intermediate/high-grade cancers. This review seeks to introduce the basics of the prostate MRF technique, discuss the potential applications of prostate MRF for the characterization of prostate cancer, and describes ongoing areas of research.

Quantitative CT and machine learning classification of fibrotic interstitial lung diseases

OBJECTIVES

To evaluate quantitative computed tomography (QCT) features and QCT feature-based machine learning (ML) models in classifying interstitial lung diseases (ILDs). To compare QCT-ML and deep learning (DL) models' performance.

METHODS

We retrospectively identified 1085 patients with pathologically proven usual interstitial pneumonitis (UIP), nonspecific interstitial pneumonitis (NSIP), and chronic hypersensitivity pneumonitis (CHP) who underwent peri-biopsy chest CT. Kruskal-Wallis test evaluated QCT feature associations with each ILD. QCT features, patient demographics, and pulmonary function test (PFT) results trained eXtreme Gradient Boosting (training/validation set n = 911) yielding 3 models: M1 = QCT features only; M2 = M1 plus age and sex; M3 = M2 plus PFT results. A DL model was also developed. ML and DL model areas under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs) were compared for multiclass (UIP vs. NSIP vs. CHP) and binary (UIP vs. non-UIP) classification performances.

RESULTS

The majority (69/78 [88%]) of QCT features successfully differentiated the 3 ILDs (adjusted p ≤ 0.05). All QCT-ML models achieved higher AUC than the DL model (multiclass AUC micro-averages 0.910, 0.910, 0.925, and 0.798 and macro-averages 0.895, 0.893, 0.925, and 0.779 for M1, M2, M3, and DL respectively; binary AUC 0.880, 0.899, 0.898, and 0.869 for M1, M2, M3, and DL respectively). M3 demonstrated statistically significant better performance compared to M2 (∆AUC: 0.015, CI: [0.002, 0.029]) for multiclass prediction.

CONCLUSIONS

QCT features successfully differentiated pathologically proven UIP, NSIP, and CHP. While QCT-based ML models outperformed a DL model for classifying ILDs, further investigations are warranted to determine if QCT-ML, DL, or a combination will be superior in ILD classification.

KEY POINTS

• Quantitative CT features successfully differentiated pathologically proven UIP, NSIP, and CHP. • Our quantitative CT-based machine learning models demonstrated high performance in classifying UIP, NSIP, and CHP histopathology, outperforming a deep learning model. • While our quantitative CT-based machine learning models performed better than a DL model, additional investigations are needed to determine whether either or a combination of both approaches delivers superior diagnostic performance.

Twitter Use by Academic Nuclear Medicine Programs: Pilot Content Analysis Study

Background

There is scant insight into the presence of nuclear medicine (NM) and nuclear radiology (NR) programs on social media.

Objective

Our purpose was to assess Twitter engagement by academic NM/NR programs in the United States.

Methods

We measured Twitter engagement by the academic NM/NR community, accounting for various NM/NR certification pathways. The Twitter presence of NM/NR programs at both the department and program director level was identified. Tweets by programs were cross-referenced against potential high-yield NM- or NR-related hashtags, and tabulated at a binary level. A brief survey was done to identify obstacles and benefits to Twitter use by academic NM/NR faculty.

Results

For 2019-2020, 88 unique programs in the United States offered NM/NR certification pathways. Of these, 52% (46/88) had Twitter accounts and 24% (21/88) had at least one post related to NM/NR. Only three radiology departments had unique Twitter accounts for the NM/molecular imaging division. Of the other 103 diagnostic radiology residency programs, only 16% (16/103) had a presence on Twitter and 5% (5/103) had tweets about NM/NR. Only 9% (8/88) of NM/NR program directors were on Twitter, and three program directors tweeted about NM/NR. The survey revealed a lack of clarity and resources around using Twitter, although respondents acknowledged the perceived value of Twitter engagement for attracting younger trainees.

Conclusions

Currently, there is minimal Twitter engagement by the academic NM/NR community. The perceived value of Twitter engagement is counterbalanced by identifiable obstacles. Given radiologists’ overall positive views of social media’s usefulness, scant social media engagement by the NM community may represent a missed opportunity. More Twitter engagement and further research by trainees and colleagues should be encouraged, as well as the streamlined use of unique hashtags.

Whole brain 3D MR fingerprinting in multiple sclerosis: a pilot study

Background

MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis.

Methods

Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1 × 1 × 1 mm³) and a total acquisition time of 4 min 38 s. Data were collected on 18 subjects paired with 18 controls. Regions of interest were drawn over MRF-derived T₁ relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T₁ and T₂ relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms. Partial least squares discriminant analysis was performed to discriminate NAWM and Splenium in MS compared with controls.

Results

Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65 % (p = 0.21) and approached 90 % (p < 0.01) for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p = 0.015), minimum T1 (p = 0.03) and negative correlation with splenium uniformity (p = 0.04). Perfect discrimination (AUC = 1) was achieved between selected features from MS lesions and F-NAWM.

Conclusions

3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.

Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset

PURPOSE

To develop a two-stage three-dimensional (3D) convolutional neural networks (CNNs) for fully automated volumetric segmentation of pancreas on computed tomography (CT) and to further evaluate its performance in the context of intra-reader and inter-reader reliability at full dose and reduced radiation dose CTs on a public dataset.

METHODS

A dataset of 1994 abdomen CT scans (portal venous phase, slice thickness ≤ 3.75-mm, multiple CT vendors) was curated by two radiologists (R1 and R2) to exclude cases with pancreatic pathology, suboptimal image quality, and image artifacts (n = 77). Remaining 1917 CTs were equally allocated between R1 and R2 for volumetric pancreas segmentation [ground truth (GT)]. This internal dataset was randomly divided into training (n = 1380), validation (n = 248), and test (n = 289) sets for the development of a two-stage 3D CNN model based on a modified U-net architecture for automated volumetric pancreas segmentation. Model's performance for pancreas segmentation and the differences in model-predicted pancreatic volumes vs GT volumes were compared on the test set. Subsequently, an external dataset from The Cancer Imaging Archive (TCIA) that had CT scans acquired at standard radiation dose and same scans reconstructed at a simulated 25% radiation dose was curated (n = 41). Volumetric pancreas segmentation was done on this TCIA dataset by R1 and R2 independently on the full dose and then at the reduced radiation dose CT images. Intra-reader and inter-reader reliability, model's segmentation performance, and reliability between model-predicted pancreatic volumes at full vs reduced dose were measured. Finally, model's performance was tested on the benchmarking National Institute of Health (NIH)-Pancreas CT (PCT) dataset.

RESULTS

Three-dimensional CNN had mean (SD) Dice similarity coefficient (DSC): 0.91 (0.03) and average Hausdorff distance of 0.15 (0.09) mm on the test set. Model's performance was equivalent between males and females (P = 0.08) and across different CT slice thicknesses (P > 0.05) based on noninferiority statistical testing. There was no difference in model-predicted and GT pancreatic volumes [mean predicted volume 99 cc (31cc); GT volume 101 cc (33 cc), P = 0.33]. Mean pancreatic volume difference was -2.7 cc (percent difference: -2.4% of GT volume) with excellent correlation between model-predicted and GT volumes [concordance correlation coefficient (CCC)=0.97]. In the external TCIA dataset, the model had higher reliability than R1 and R2 on full vs reduced dose CT scans [model mean (SD) DSC: 0.96 (0.02), CCC = 0.995 vs R1 DSC: 0.83 (0.07), CCC = 0.89, and R2 DSC:0.87 (0.04), CCC = 0.97]. The DSC and volume concordance correlations for R1 vs R2 (inter-reader reliability) were 0.85 (0.07), CCC = 0.90 at full dose and 0.83 (0.07), CCC = 0.96 at reduced dose datasets. There was good reliability between model and R1 at both full and reduced dose CT [full dose: DSC: 0.81 (0.07), CCC = 0.83 and reduced dose DSC:0.81 (0.08), CCC = 0.87]. Likewise, there was good reliability between model and R2 at both full and reduced dose CT [full dose: DSC: 0.84 (0.05), CCC = 0.89 and reduced dose DSC:0.83(0.06), CCC = 0.89]. There was no difference in model-predicted and GT pancreatic volume in TCIA dataset (mean predicted volume 96 cc (33); GT pancreatic volume 89 cc (30), p = 0.31). Model had mean (SD) DSC: 0.89 (0.04) (minimum-maximum DSC: 0.79 -0.96) on the NIH-PCT dataset.

CONCLUSION

A 3D CNN developed on the largest dataset of CTs is accurate for fully automated volumetric pancreas segmentation and is generalizable across a wide range of CT slice thicknesses, radiation dose, and patient gender. This 3D CNN offers a scalable tool to leverage biomarkers from pancreas morphometrics and radiomics for pancreatic diseases including for early pancreatic cancer detection.

Abstract PO-084: Automated detection of pancreatic ductal adenocarcinoma (PDAC) on CT scans using artificial intelligence (AI): Impact of inclusion of automated pancreas segmentation on the accuracy of 3D-convolutional neural network (CNN)

Purpose: Around 30% of PDAC less than 2-cm tend to go undetected on CT due to their subtle imaging signatures. Automated detection of PDAC using AI represents an opportunity to augment physician expertise and to improve outcomes through early detection of PDAC. Our purpose was to develop a 3D-CNN for fully automated detection of PDAC and to further evaluate the impact of inclusion of pancreas segmentation on the accuracy of this 3D-CNN. Methods: A Medical Imaging Data Readiness Scale (MIDaR) level A dataset (portal venous phase CTs, slice thickness ≤ 3.75 mm) of 466 treatment-naïve biopsy-proven PDAC and 1994 subjects with normal pancreas was created after exclusion of CTs with suboptimal image quality or biliary stents. Volumetric pancreas and tumor segmentations on CTs were done by two radiologists using 3D Slicer. A total of 370 CTs with PDAC and 370 CTs with normal pancreas were randomly selected for separate training and validation sets, and 396 CTs (96 CTs with PDAC and 300 CTs with normal pancreas) were utilized for testing. Two separate 3D-CNNs were trained. A three-stage bounding-box-only model (A): stage 1 was based on a UNET-like architecture and localized the pancreas on CT with a bounding box; stage 2 utilized an Inception ResNet architecture and classified each slice through the pancreas into PDAC vs. normal; and stage 3 utilized the output of stage 2 to generate final classification for a given CT. Conversely, a four-stage pancreas segmentation-based model (B) included stage 1 of model A followed by an additional stage of automated pancreas and tumor segmentation (stage 2), classification of each slice through the pancreas into PDAC vs. normal (stage 3) and, finally, generation of final classification score (stage 4) for a given CT. Area under the receiver operating characteristic curve (AUROC) of the two models were compared on the test set. Results: Mean (SD) PDAC diameter in the test set was 1.1 (0.43) cm. Model A (three-stage bounding-box-only) correctly classified 305 (77%) out of 396 CTs from the test set into PDAC vs. normal. It incorrectly classified 12/96 (12.5%) CTs with PDAC as normal and 79/300 (26%) normal CTs as PDAC. AUROC for model A was 0.85. Model B (four-stage pancreas segmentation-based) correctly classified 351 (88%) out of 396 CTs. It incorrectly classified 13/96 (13.5%) CTs with PDAC as normal and 32/300 (10.7%) normal CTs as PDAC. AUROC for model B was 0.94. AUROC for model B was significantly higher than model A (p&lt;0.005). Conclusion: A 3D-CNN can detect small PDAC with high accuracy using automated localization of pancreas with a bounding box without relying on separate pancreas segmentation. Inclusion of an additional automated pancreas segmentation step reduced false positives with consequent incremental gain in the model’s accuracy. Prospective validation and subsequent integration of such models into clinical workflows has the potential to reduce inadvertent errors in detection of subtle or small PDAC on standard-of-care CT scans.

Citation Format: Anurima Patra, Korfiatis Panagiotis, Garima Suman, Ananya Panda, Sushil Kumar Garg, Ajit Goenka. Automated detection of pancreatic ductal adenocarcinoma (PDAC) on CT scans using artificial intelligence (AI): Impact of inclusion of automated pancreas segmentation on the accuracy of 3D-convolutional neural network (CNN) [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-084.

Whole-body 18-F-FDG-PET in patients with leptomeningeal disease and correlation with MRI

OBJECTIVE

Studies evaluating leptomeningeal disease on whole-body 18F-FDG PET are lacking. The purpose was to evaluate PET imaging of leptomeningeal disease and investigate the incremental utility of newer PET reconstructions in leptomeningeal disease.

METHODS

PET imaging of 56 patients with leptomeningeal disease detected initially on MRI (n = 53) or cytopathology (n = 35) were retrospectively reviewed. Regular 3-dimensional iterative reconstruction (3D IR, n = 56) and advanced reconstruction (AdvRecon, n = 41) PET images were evaluated by readers blinded to clinical and MRI findings for uptake involving cauda equina, posterior fossa and spinal cord. Spinal cord uptake pattern was classified as normal (uptake < liver), uptake = liver, conus uptake > liver, conus and cervical cord uptake > liver and multifocal/diffuse uptake > liver. SUVmax ratios of conus/liver, conus/left atrium and conus/cervical cord were compared between 3D IR and AdvRecon datasets.

RESULTS

Cauda equina uptake was seen in 64% and 78% on 3D IR and AdvRecon; posterior fossa uptake was seen in 52% and 54% on 3D IR and AdvRecon, respectively. Twelve percent had cauda equina or posterior fossa uptake visible only on AdvRecon. On 3D IR, normal spinal cord uptake was most common (27%); on AdvRecon, conus and cervical cord uptake > liver was most common (32%). Seven of 11 patients with normal spinal cord uptake on 3D IR were upgraded to increased uptake on AdvRecon. AdvRecon showed significantly higher conus/liver, conus/blood pool and conus/cervical cord SUVmax ratios (P < 0.0001).

CONCLUSION

Abnormal uptake in cauda equina, posterior fossa and spinal cord uptake are visible on FDG PET in leptomeningeal disease with increased conspicuity advanced PET reconstructions.

Effect of surfactant on quality and performance attributes of topical semisolids

Surfactants are the most common inactive ingredients used in topical drug products. Surfactants in topical products play many functional roles such as emulsifiers, permeation enhancers, and solubilizers. This study was aimed to evaluate the influence of incremental change in the concentration of a surfactant (tween 80) on the quality attributes and performance of semisolid topical products. Four creams were prepared using metronidazole as a model drug using the same manufacturing protocol and similar composition except for the concentration of tween 80, which was increased by 5% w/w across SF1 to SF4. The quality attributes like globule size, pH, drying rate, and in-vitro permeation profile were characterized. The critical quality attributes did not differ significantly across the products. However, there was a significant difference in the permeation profile of the products. The permeation flux (J_max) varied from SF1 to SF4 (51.25 ± 35.29 to 307.98 ± 138.89 ng/cm²/h, respectively). The reason for the difference in the performance of products despite having consistent quality attributes was investigated. One of the major reasons was found to be the difference in the time course of degree of saturation of drug during the evaporative metamorphosis. This study confirms that the time course of degree of saturation is one of the important quality attributes of the topical product that could influence bioavailability and performance of topical products.

Beyond Tympanomastoidectomy: A Review of Less Common Postoperative Temporal Bone CT Findings

Postoperative temporal bone imaging after surgical procedures such as ossiculoplasty, tympanomastoidectomy, cochlear implantation, and vestibular schwannoma resection is often encountered in clinical neuroradiology practice. Less common otologic procedures can present diagnostic dilemmas, particularly if access to prior operative reports is not possible. Lack of familiarity with the less common surgical procedures and expected postoperative changes may render radiologic interpretation challenging. This review illustrates key imaging findings after surgery for Ménière disease, superior semicircular canal dehiscence, temporal encephalocele repairs, internal auditory canal decompression, active middle ear implants, jugular bulb and sigmoid sinus dehiscence repair, and petrous apicectomy.

18F-fluorodeoxyglucose positron emission tomography/computed tomography of giant cell arteritis with lower extremity involvement in association with polymyalgia rheumatica

An 80-year-old man presented with new-onset pain in the shoulders and lower extremities and elevated serum inflammatory markers. A clinical diagnosis of polymyalgia rheumatica (PMR) was made, but there was a suboptimal response to glucocorticoid therapy, prompting further evaluation. ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) revealed intense FDG uptake in the arteries of the bilateral lower extremities, head, and neck, but sparing the aorta, suggestive of an uncommon pattern of giant cell arteritis (GCA). There were also imaging signs consistent with PMR, including FDG uptake in the synovium of large joints. This case highlights the uncommon manifestation of GCA with lower extremity involvement and sparing of the aorta. The combination of FDG PET imaging features and elevated serum markers obviated the need for invasive biopsy. One might also conclude that standard FDG PET/CT imaging protocols covering orbits/vertex to thighs incompletely evaluate the extent of arterial distribution of GCA.

Spinal Cord Cavernous Malformations: MRI Commonly Shows Adjacent Intramedullary Hemorrhage

BACKGROUND AND PURPOSE

There is a relative paucity of radiology literature on spinal cord cavernous malformations (SCMs). We hypothesized that the classic MRI features of cavernous malformations are not highly prevalent. The purpose was to review MR imaging findings of SCMs with a focus on prevalence of hemorrhagic features, including adjacent intramedullary hemorrhage at initial presentation.

METHODS

In this single-institution study, 78 SCMs in 76 patients diagnosed on imaging/pathology were retrospectively evaluated for size, location, cord expansion, exophytic component, popcorn morphology, signal characteristics, including T1 weighted (T1w) and T2w rims, blood-fluid levels, and adjacent intramedullary hemorrhage. Intramedullary hemorrhage was defined as centrally and/or eccentrically located linear or flame shaped non-edematous signal abnormality extending longitudinally away from SCMs, distinct from lesional rim.

RESULTS

Sixty-three percent (49/78) of SCMs measured <1 cm in length, 78% (61/78) extended to the cord surface, 65% (51/78) were expansile, and 32% (25/78) were exophytic. Popcorn morphology was seen in 15% (12/78) on T1w and 22% (17/78) on T2w. Internal blood-fluid levels were evident in 4% (3/78). Sixty-nine percent (54/78) showed T2w hypointense rims; the T2w rim was complete/near-complete in 37% (29/78). A rim on T1w was visible in 49% (38/78); this was hyperintense in 58% (22/38). Adjacent intramedullary hemorrhage was seen in 45/78 (58%), was most commonly bidirectional in 67% (30/45) and eccentric in 68% (30/44). Cord edema was seen in 22% (17/78); 53% (9/17) also demonstrated intramedullary hemorrhage with edema.

CONCLUSIONS

The classically described popcorn morphology, internal blood-fluid levels, and complete/near-complete T2w hypointense rims are often absent on MRIs in SCMs. Adjacent intramedullary hemorrhage is frequently present, often eccentric and bidirectional.

Assessing Nasal Soft-Tissue Envelope Thickness for Rhinoplasty: Normative Data and a Predictive Algorithm

Importance

Preoperative assessment of nasal soft-tissue envelope (STE) thickness is an important component of rhinoplasty that presently lacks validated tools.

Objective

To measure and assess the distribution of nasal STE thickness in a large patient population and to determine if facial plastic surgery clinicians can predict nasal STE thickness based on visual examination of the nose.

Design, Setting, and Participants

This retrospective review and prospective assessment of 190 adult patients by 4 expert raters was conducted at an academic tertiary referral center. The patients had high-resolution maxillofacial computed tomography (CT) scans and standardized facial photographs on file and did not have a history of nasal fracture, septal perforation, rhinoplasty, or other surgery or medical conditions altering nasal form. Data were analyzed in March 2019.

Main Outcomes and Measures

Measure nasal STE thickness at defined anatomic subsites using high-resolution CT scans. Measure expert-predicted nasal STE thickness based on visual examination of the nose using a scale from 0 (thinnest) to 100 (thickest).

Results

Of the 190 patients, 78 were women and the mean (SD) age was 45 (17) years. The nasal STE was thickest at the sellion (mean [SD]) (6.7 [1.7] mm), thinnest at the rhinion (2.1 [0.7] mm), thickened over the supratip (4.8 [1.0] mm) and nasal tip (3.1 [0.6] mm), and thinned over the columella (2.6 [0.4] mm). In the study population, nasal STE thickness followed a nearly normal distribution for each measured subsite, with the majority of patients in a medium thickness range. Comparison of predicted and actual nasal STE thickness showed that experts could accurately predict nasal STE thickness, with the highest accuracy at the nasal tip (r, 0.73; prediction accuracy, 91%). A strong positive correlation was noted among the experts' STE estimates (r, 0.83-0.89), suggesting a high level of agreement between individual raters.

Conclusions and Relevance

There is variable thickness of the nasal STE, which influences the external nasal contour and rhinoplasty outcomes. With visual analysis of the nose, experts can agree on and predict nasal STE thickness, with the highest accuracy at the nasal tip. These data can aid in preoperative planning for rhinoplasty, allowing implementation of preoperative, intraoperative, and postoperative strategies to optimize the nasal STE, which may ultimately improve patient outcomes and satisfaction.

Level of Evidence

NA.

An Unusual case of neurocysticercosis leading to blindness in a young Indian male

Neurocysticercosis is an endemic disease in India. It is caused by infection from the larval form of Taenia solium and humans serve as the intermediate host. Its diverse manifestations include seizures, headaches, focal neurological signs. Obstructive hydrocephalus, with its potential for death is the most disastrous complication. We hereby report a case of 24 year old boy presenting with blindness without hydrocephalus.

MR Fingerprinting and ADC Mapping for Characterization of Lesions in the Transition Zone of the Prostate Gland

BackgroundPreliminary studies have shown that MR fingerprinting-based relaxometry combined with apparent diffusion coefficient (ADC) mapping can be used to differentiate normal peripheral zone from prostate cancer and prostatitis. The utility of relaxometry and ADC mapping for the transition zone (TZ) is unknown.PurposeTo evaluate the utility of MR fingerprinting combined with ADC mapping for characterizing TZ lesions.Materials and MethodsTZ lesions that were suspicious for cancer in men who underwent MRI with T2-weighted imaging and ADC mapping (b values, 50-1400 sec/mm2), MR fingerprinting with steady-state free precession, and targeted biopsy (60 in-gantry and 15 cognitive targeting) between September 2014 and August 2018 in a single university hospital were retrospectively analyzed. Two radiologists blinded to Prostate Imaging Reporting and Data System (PI-RADS) scores and pathologic diagnosis drew regions of interest on cancer-suspicious lesions and contralateral visually normal TZs (NTZs) on MR fingerprinting and ADC maps. Linear mixed models compared two-reader means of T1, T2, and ADC. Generalized estimating equations logistic regression analysis was used to evaluate both MR fingerprinting and ADC in differentiating NTZ, cancers and noncancers, clinically significant (Gleason score ≥ 7) cancers from clinically insignificant lesions (noncancers and Gleason 6 cancers), and characterizing PI-RADS version 2 category 3 lesions.ResultsIn 67 men (mean age, 66 years ± 8 [standard deviation]) with 75 lesions, targeted biopsy revealed 37 cancers (six PI-RADS category 3 cancers and 31 PI-RADS category 4 or 5 cancers) and 38 noncancers (31 PI-RADS category 3 lesions and seven PI-RADS category 4 or 5 lesions). The T1, T2, and ADC of NTZ (1800 msec ± 150, 65 msec ± 22, and [1.13 ± 0.19] × 10-3 mm2/sec, respectively) were higher than those in cancers (1450 msec ± 110, 36 msec ± 11, and [0.57 ± 0.13] × 10-3 mm2/sec, respectively; P < .001 for all). The T1, T2, and ADC in cancers were lower than those in noncancers (1620 msec ± 120, 47 msec ± 16, and [0.82 ± 0.13] × 10-3 mm2/sec, respectively; P = .001 for T1 and ADC and P = .03 for T2). The area under the receiver operating characteristic curve (AUC) for T1 plus ADC was 0.94 for separation. T1 and ADC in clinically significant cancers (1440 msec ± 140 and [0.58 ± 0.14] × 10-3 mm2/sec, respectively) were lower than those in clinically insignificant lesions (1580 msec ± 120 and [0.75 ± 0.17] × 10-3 mm2/sec, respectively; P = .001 for all). The AUC for T1 plus ADC was 0.81 for separation. Within PI-RADS category 3 lesions, T1 and ADC of cancers (1430 msec ± 220 and [0.60 ± 0.17] × 10-3 mm2/sec, respectively) were lower than those of noncancers (1630 msec ± 120 and [0.81 ± 0.13] × 10-3 mm2/sec, respectively; P = .006 for T1 and P = .004 for ADC). The AUC for T1 was 0.79 for differentiating category 3 lesions.ConclusionMR fingerprinting-based relaxometry combined with apparent diffusion coefficient mapping may improve transition zone lesion characterization.© RSNA, 2019Online supplemental material is available for this article.

Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping

OBJECTIVE

This study aims for targeted biopsy validation of magnetic resonance fingerprinting (MRF) and diffusion mapping for characterizing peripheral zone (PZ) prostate cancer and noncancers.

MATERIALS AND METHODS

One hundred four PZ lesions in 85 patients who underwent magnetic resonance imaging were retrospectively analyzed with apparent diffusion coefficient (ADC) mapping, MRF, and targeted biopsy (cognitive or in-gantry). A radiologist blinded to pathology drew regions of interest on targeted lesions and visually normal peripheral zone on MRF and ADC maps. Mean T1, T2, and ADC were analyzed using linear mixed models. Generalized estimating equations logistic regression analyses were used to evaluate T1 and T2 relaxometry combined with ADC in differentiating pathologic groups.

RESULTS

Targeted biopsy revealed 63 cancers (low-grade cancer/Gleason score 6 = 10, clinically significant cancer/Gleason score ≥7 = 53), 15 prostatitis, and 26 negative biopsies. Prostate cancer T1, T2, and ADC (mean ± SD, 1660 ± 270 milliseconds, 56 ± 20 milliseconds, 0.70 × 10 ± 0.24 × 10 mm/s) were significantly lower than prostatitis (mean ± SD, 1730 ± 350 milliseconds, 77 ± 36 milliseconds, 1.00 × 10 ± 0.30 × 10 mm/s) and negative biopsies (mean ± SD, 1810 ± 250 milliseconds, 71 ± 37 milliseconds, 1.00 × 10 ± 0.33 × 10 mm/s). For cancer versus prostatitis, ADC was sensitive and T2 specific with comparable area under curve (AUC; (AUCT2 = 0.71, AUCADC = 0.79, difference between AUCs not significant P = 0.37). T1 + ADC (AUCT1 + ADC = 0.83) provided the best separation between cancer and negative biopsies. Low-grade cancer T2 and ADC (mean ± SD, 75 ± 29 milliseconds, 0.96 × 10 ± 0.34 × 10 mm/s) were significantly higher than clinically significant cancers (mean ± SD, 52 ± 16 milliseconds, 0.65 ± 0.18 × 10 mm/s), and T2 + ADC (AUCT2 + ADC = 0.91) provided the best separation.

CONCLUSIONS

T1 and T2 relaxometry combined with ADC mapping may be useful for quantitative characterization of prostate cancer grades and differentiating cancer from noncancers for PZ lesions seen on T2-weighted images.

Repeatability and reproducibility of 3D MR fingerprinting relaxometry measurements in normal breast tissue

BACKGROUND

The 3D breast magnetic resonance fingerprinting (MRF) technique enables T₁ and T₂ mapping in breast tissues. Combined repeatability and reproducibility studies on breast T₁ and T₂ relaxometry are lacking.

PURPOSE

To assess test-retest and two-visit repeatability and interscanner reproducibility of the 3D breast MRF technique in a single-institution setting.

STUDY TYPE

Prospective.

SUBJECTS

Eighteen women (median age 29 years, range, 22-33 years) underwent Visit 1 scans on scanner 1. Ten of these women underwent test-retest scan repositioning after a 10-minute interval. Thirteen women had Visit 2 scans within 7-15 days in same menstrual cycle. The remaining five women had Visit 2 scans in the same menstrual phase in next menstrual cycle. Five women were also scanned on scanner 2 at both visits for interscanner reproducibility.

FIELD STRENGTH/SEQUENCE

Two 3T MR scanners with the 3D breast MRF technique.

ASSESSMENT

T₁ and T₂ MRF maps of both breasts.

STATISTICAL TESTS

Mean T₁ and T₂ values for normal fibroglandular tissues were quantified at all scans. For variability, between and within-subjects coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability was assessed with Bland-Altman analysis and coefficient of repeatability (CR). Reproducibility was assessed with interscanner coefficient of variation (CoV) and Wilcoxon signed-rank test.

RESULTS

The bCV at test-retest scans was 9-12% for T₁ , 7-17% for T₂ , wCV was <4% for T₁ , and <7% for T₂ . For two visits in same menstrual cycle, bCV was 10-15% for T₁ , 13-17% for T₂ , wCV was <7% for T₁ and <5% for T₂ . For two visits in the same menstrual phase, bCV was 6-14% for T₁ , 15-18% for T₂ , wCV was <7% for T₁ , and <9% for T₂ . For test-retest scans, CR for T₁ and T₂ were 130 msec and 11 msec. For two visit scans, CR was <290 msec for T₁ and 10-14 msec for T₂ . Interscanner CoV was 3.3-3.6% for T₁ and 5.1-6.6% for T₂ , with no differences between interscanner measurements (P = 1.00 for T₁ , P = 0.344 for T₂ ).

DATA CONCLUSION

3D breast MRF measurements are repeatable across scan timings and scanners and may be useful in clinical applications in breast imaging.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1133-1143.

Three-dimensional MR Fingerprinting for Quantitative Breast Imaging

Purpose To develop a fast three-dimensional method for simultaneous T1 and T2 quantification for breast imaging by using MR fingerprinting. Materials and Methods In this prospective study, variable flip angles and magnetization preparation modules were applied to acquire MR fingerprinting data for each partition of a three-dimensional data set. A fast postprocessing method was implemented by using singular value decomposition. The proposed technique was first validated in phantoms and then applied to 15 healthy female participants (mean age, 24.2 years ± 5.1 [standard deviation]; range, 18-35 years) and 14 female participants with breast cancer (mean age, 55.4 years ± 8.8; range, 39-66 years) between March 2016 and April 2018. The sensitivity of the method to B₁ field inhomogeneity was also evaluated by using the Bloch-Siegert method. Results Phantom results showed that accurate and volumetric T1 and T2 quantification was achieved by using the proposed technique. The acquisition time for three-dimensional quantitative maps with a spatial resolution of 1.6 × 1.6 × 3 mm³ was approximately 6 minutes. For healthy participants, averaged T1 and T2 relaxation times for fibroglandular tissues at 3.0 T were 1256 msec ± 171 and 46 msec ± 7, respectively. Compared with normal breast tissues, higher T2 relaxation time (68 msec ± 13) was observed in invasive ductal carcinoma (P < .001), whereas no statistical difference was found in T1 relaxation time (1183 msec ± 256; P = .37). Conclusion A method was developed for breast imaging by using the MR fingerprinting technique, which allows simultaneous and volumetric quantification of T1 and T2 relaxation times for breast tissues. © RSNA, 2018 Online supplemental material is available for this article.

Bronchial artery embolization in hemoptysis: a systematic review

We systematically reviewed the role of bronchial artery embolization (BAE) in hemoptysis. Literature search was done for studies on BAE published between 1976 and 2016. Twenty-two studies published in English, with sample size of at least 50 patients, reporting indications, technique, efficacy, and follow-up were included in the final analysis. Common indications for BAE included tuberculosis (TB), post-tubercular sequelae, bronchiectasis, and aspergillomas. Most common embolizing agent used was polyvinyl alcohol (size, 300-600 μm) with increasing use of glue in recent years. Overall immediate clinical success rate of BAE, defined as complete cessation of hemoptysis, varied from 70%-99%. However, recurrence rate remains high, ranging from 10%-57%, due to incomplete initial embolization, recanalization of previously embolized arteries, and recruitment of new collaterals. Presence of nonbronchial systemic collaterals, bronchopulmonary shunting, aspergillomas, reactivation TB, and multidrug resistant TB were associated with significantly higher recurrence rates (P < 0.05). Rate of major complications remained negligible and stable over time with median incidence of 0.1% (0%-6.6%). Despite high hemoptysis recurrence rates, BAE continues to be the first-line, minimally invasive treatment of hemoptysis in emergency settings, surgically unfit patients, or in patients with diffuse or bilateral lung disease.

Magnetic Resonance Fingerprinting-An Overview

Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. The ability to reproducibly and quantitatively measure tissue properties could enable more objective tissue diagnosis, comparisons of scans acquired at different locations and time points, longitudinal follow-up of individual patients and development of imaging biomarkers. This review provides a general overview of MRF technology, current preclinical and clinical applications and potential future directions. MRF has been initially evaluated in brain, prostate, liver, cardiac, musculoskeletal imaging, and measurement of perfusion and microvascular properties through MR vascular fingerprinting.

Can multidetector CT detect the site of gastrointestinal tract injury in trauma? - A retrospective study

PURPOSE

We aimed to assess the performance of computed tomography (CT) in localizing site of traumatic gastrointestinal tract (GIT) injury and determine the diagnostic value of CT signs in site localization.

METHODS

CT scans of 97 patients with surgically proven GIT or mesenteric injuries were retrospectively reviewed by radiologists blinded to surgical findings. Diagnosis of either GIT or mesenteric injuries was made. In patients with GIT injuries, site of injury and presence of CT signs such as focal bowel wall hyperenhancement, hypoenhancement, wall discontinuity, wall thickening, extramural air, intramural air, perivisceral infiltration, and active vascular contrast leak were evaluated.

RESULTS

Out of 97 patients, 90 had GIT injuries (70 single site injuries and 20 multiple site injuries) and seven had isolated mesenteric injury. The overall concordance between CT and operative findings for exact site localization was 67.8% (61/90), partial concordance rate was 11.1% (10/90), and discordance rate was 21.1% (19/90). For single site localization, concordance rate was 77.1% (54/70), discordance rate was 21.4% (15/70), and partial concordance rate was 1.4% (1/70). In multiple site injury, concordance rate for all sites of injury was 35% (7/20), partial concordance rate was 45% (9/20), and discordance rate was 20% (4/20). For upper GIT injuries, wall discontinuity was the most accurate sign for localization. For small bowel injury, intramural air and hyperenhancement were the most specific signs for site localization, while for large bowel injury, wall discontinuity and hypoenhancement were the most specific signs.

CONCLUSION

CT performs better in diagnosing small bowel injury compared with large bowel injury. CT can well predict the presence of multiple site injury but has limited performance in exact localization of all injury sites.

Circulating genotypes of Pneumocystis jirovecii and its clinical correlation in patients from a single tertiary center in India

The present study was carried out with the objectives of genotyping Pneumocystis jirovecii at three distinct loci, to identify the single nucleotide polymorphisms (SNPs), and to study its clinical implications in patients with Pneumocystis pneumonia (PCP). Analysis of genetic diversity in P. jirovecii from immunocompromised patients was carried out by genotyping at three distinct loci encoding mitochondrial large subunit rRNA (mtLSU rRNA), cytochrome b (CYB), and superoxide dismutase (SOD) using polymerase chain reaction (PCR) assays followed by direct DNA sequencing. Of the 300 patients enrolled in the present study, 31 (10.33%) were positive for PCP by a specific mtLSU rRNA nested PCR assay, whereas only 15 P. jirovecii could be amplified at the other two loci (SOD and CYB). These positives were further subjected to sequence typing. Important genotypic combinations between four SNPs (mt85, SOD110, SOD215, and CYB838) and clinical outcomes could be observed in the present study, and mt85A, mt85T, and SOD110C/SOD215T were frequently associated with "negative follow-up". These SNPs were also noted to be relatively more prevalent amongst circulating genotypes in our study population. The present study is the first of its kind from the Indian subcontinent and demonstrated that potential SNPs of P. jirovecii may possibly be attributed to the clinical outcome of PCP episodes in terms of severity or fatality in different susceptible populations likely to develop PCP during their course of illness.

Idiopathic myelofibrosis with disseminated hepatosplenic, mesenteric, renal and pulmonary extramedullary haematopoeisis, portal hypertension and tuberculosis: initial presentation and 2 years follow-up

A 35-year-old man with a 12-year history of idiopathic myelofibrosis (IMF) presented in 2014 with fatigue and abdominal distension. CT scan revealed massive hepatosplenomegaly with focal splenic lesions, soft tissue around renal pelvis, mesenteric masses compressing bowel loops and perilymphatic nodules in lungs. There was portal hypertension, ascites, pleural effusion, bilateral psoas abscesses and necrotic retroperitoneal lymphadenopathy. MRI additionally revealed hypointense periportal infiltrative lesions in liver, not seen on CT scan. None of these lesions showed diffusion restriction. Biopsy from mesenteric masses revealed extramedullary haematopoeisis. Aspiration from psoas abscess confirmed tuberculosis. Follow-up after 6 weeks of ruxolitinib (JAK2 tyrosine kinase inhibitor) and 9 months of antitubercular therapy revealed resolution of psoas abscesses and lymph nodes. Mild reduction was noted in mesenteric masses and ascites while perirenal soft tissue had increased. Follow-up imaging after another 1 year of ruloxitinib showed new-onset bilateral paravertebral and presacral foci of extramedullary haematopoeisis.

Epithelial Myoepithelial Carcinoma of Parotid Gland

Epithelial myoepithelial carcinoma (EMC) is a rare biphasic tumor of salivary glands with low malignant potential. Although known to occur in submandibular gland and minor salivary glands, its most common location is parotid. Clinical and radiological findings often mimic a benign tumor. Because of rarity of EMC a standard treatment guideline is not yet known. Surgical resection is the most widely used approach. Although it is a low grade tumor, local recurrence rates of 23-50 % have been reported with 25 % chance of distant metastasis. Patients with histo-pathologic markers of aggressive disease should be considered for adjuvant radiotherapy. We report a case of epithelial myoepithelial carcinoma of parotid in a 40 year male that was treated with surgery followed by post-operative radiotherapy.

Imaging of Retrosternal Space Lesions - A Pictorial Review

The retrosternal region (RSS) can be involved by diverse lesions. The RSS is the region behind the sternum and anterior to the ascending aorta. It normally is less than 3 cm deep. Chest X-ray is usually the first imaging modality to raise a suspicion of RSS pathology; however computed tomography is the mainstay to delineate and characterize lesions in this location. Lesions in this location include thyroid, thymic and lymph node lesions; germ cell tumors and vascular lesions. Lesions arising from the sternum, lungs as well as the pleura can also involve this space. The pictorial review depicts the diverse spectrum of lesions in this location.

Blunt pancreatic trauma: A persistent diagnostic conundrum?

Blunt pancreatic trauma is an uncommon injury but has high morbidity and mortality. In modern era of trauma care, pancreatic trauma remains a persistent challenge to radiologists and surgeons alike. Early detection of pancreatic trauma is essential to prevent subsequent complications. However early pancreatic injury is often subtle on computed tomography (CT) and can be missed unless specifically looked for. Signs of pancreatic injury on CT include laceration, transection, bulky pancreas, heterogeneous enhancement, peripancreatic fluid and signs of pancreatitis. Pan-creatic ductal injury is a vital decision-making parameter as ductal injury is an indication for laparotomy. While lacerations involving more than half of pancreatic parenchyma are suggestive of ductal injury on CT, ductal injuries can be directly assessed on magnetic resonance imaging (MRI) or encoscopic retrograde cholangio-pancreatography. Pancreatic trauma also shows temporal evolution with increase in extent of injury with time. Hence early CT scans may underestimate the extent of injures and sequential imaging with CT or MRI is important in pancreatic trauma. Sequential imaging is also needed for successful non-operative management of pancreatic injury. Accurate early detection on initial CT and adopting a multimodality and sequential imaging strategy can improve outcome in pancreatic trauma.

Correlation of chest computed tomography findings with dyspnea and lung functions in post-tubercular sequelae

Aims:

To study the correlation between dyspnea, radiological findings, and pulmonary function tests (PFTs) in patients with sequelae of pulmonary tuberculosis (TB).

Materials and Methods:

Clinical history, chest computed tomography (CT), and PFT of patients with post-TB sequelae were recorded. Dyspnea was graded according to the Modified Medical Research Council (mMRC) scale. CT scans were analyzed for fibrosis, cavitation, bronchiectasis, consolidation, nodules, and aspergilloma. Semi-quantitative analysis was done for these abnormalities. Scores were added to obtain a total morphological score (TMS). The lungs were also divided into three zones and scores added to obtain the total lung score (TLS). Spirometry was done for forced vital capacity (FVC), forced expiratory volume in 1 s (FEV₁), and FEV₁/FVC.

Results:

Dyspnea was present in 58/101 patients. A total of 22/58 patients had mMRC Grade 1, and 17/58 patients had Grades 2 and 3 dyspnea each. There was a significant difference in median fibrosis, bronchiectasis, nodules (P < 0.01) scores, TMS, and TLS (P < 0.0001) between dyspnea and nondyspnea groups. Significant correlations were obtained between grades of dyspnea and fibrosis (r = 0.34, P = 0.006), bronchiectasis (r = 0.35, P = 0.004), nodule (r = 0.24, P = 0.016) scores, TMS (r = 0.398, P = 0.000), and TLS (r = 0.35, P = 0.0003). PFTs were impaired in 78/101 (77.2%) patients. Restrictive defect was most common in 39.6% followed by mixed in 34.7%. There was a negative but statistically insignificant trend between PFT and fibrosis, bronchiectasis, nodule scores, TMS, and TLS. However, there were significant differences in median fibrosis, cavitation, and bronchiectasis scores in patients with normal, mild to moderate, and severe respiratory defects. No difference was seen in TMS and TLS according to the severity of the respiratory defect.

Conclusion:

Both fibrosis and bronchiectasis correlated with dyspnea and with PFT. However, this correlation was not linear. The overall extent of radiological abnormalities correlated only with dyspnea but not with PFT.

Composite renal cell carcinoma and angiomyolipoma in a patient with Tuberous sclerosis: A diagnostic dilemma

Tuberous sclerosis (TS) is an autosomal dominant disorder associated with various renal pathologies, including angiomyolipoma (AML). Renal cell carcinoma (RCC) with concomitant AML is rare. We report a case of composite RCC and AML in a young male with TS. This 25-year-old male presented with an abdominal mass. The abdominal computed tomography scan revealed RCC in the left kidney and AML in right kidney. A left radical nephrectomy was performed. Microscopy showed a tumour composed of closely intermingled RCC and AML components. Immunohistochemistry was performed for confirmation. A diagnosis of composite tumour with clear cell RCC and AML was made. Though the coexistence of RCC with AML is rare, and the composite variant is even rarer, one must be aware of this entity to prevent misdiagnosis as well as upstaging of RCC, and also to avoid missing areas of RCC within a large AML, especially in TS patients.

Are traumatic bilateral adrenal injuries associated with higher morbidity and mortality?-A prospective observational study

BACKGROUND

Traumatic bilateral adrenal injuries are uncommon. Adrenal injuries are overall associated with worse outcome than non-adrenal injuries. However, direct comparative evidence between unilateral and bilateral adrenal injuries is unavailable in literature. This study aims to investigate clinical significance of bilateral adrenal hematomas in terms of injury severity, morbidity and mortality.

METHODS

All blunt trauma abdomen patients with adrenal gland involvement on initial CECT scans of abdomen presenting to our Level 1 trauma centre over 21 months were prospectively included and followed-up. Patients were divided into unilateral and bilateral adrenal hematoma groups. For all patients, mechanism of injury, initial pulse, blood pressure, respiratory rate, Glasgow Coma Scale (GCS) scores, Injury Severity Score (ISS), New Injury Severity Score (NISS), length of ICU stay (LOI), length of hospital stay (LOS), total blood products (TBP) received were recorded. Final outcome was noted as complete recovery; discharge with poor prognosis and death. Quantitative parameters between both groups were compared using appropriate statistical tests and P < 0.05 was considered significant.

RESULTS

Forty seven patients were detected to have adrenal hematomas, 34 with unilateral (30 right and 4 left) and 13 with bilateral involvement. An oval mass replacing the gland was the most common appearance of injury (35/60) and periadrenal fat stranding was most common associated finding (47/60). Patients with bilateral adrenal hematoma had significantly lower GCS (13 vs 15, P < 0.01), ISS (38 vs 22, P < 0.01), NISS (47 vs 21, P < 0.01), LOI as proportion of LOS (91.7 % vs 10.5 %, P = 0.01) and TBP received (10 vs 4 units, P < 0.05). Outcome in bilateral group was comparatively worse with higher proportion of deaths or discharge with poor prognosis (P = 0.000).

CONCLUSIONS

Patients with bilateral adrenal injury are associated with higher injury severity, morbidity and mortality compared to unilateral adrenal injury.

Perfusion computed tomography in renal cell carcinoma

Various imaging modalities are available for the diagnosis, staging and response evaluation of patients with renal cell carcinoma (RCC). While contrast enhanced computed tomography (CT) is used as the standard of imaging for size, morphological evaluation and response assessment in RCC, a new functional imaging technique like perfusion CT (pCT), goes down to the molecular level and provides new perspectives in imaging of RCC. pCT depicts regional tumor perfusion and vascular permeability which are indirect parameters of tumor angiogenesis and thereby provides vital information regarding tumor microenvironment. Also response evaluation using pCT may predate the size criteria used in Response Evaluation Criteria in Solid Tumors, as changes in the perfusion occurs earlier following tissue kinase inhibitors before any actual change in size. This may potentially help in predicting prognosis, better selection of therapy and more accurate and better response evaluation in patients with RCC. This article describes the techniques and role of pCT in staging and response assessment in patients with RCCs.