Faculty Bibliography

BACKGROUND:Quantifying the biomechanical properties of pancreatic tumors could potentially help with assessment of tumor aggressiveness, prognosis, and prediction of therapy response. PURPOSE/OBJECTIVE:To quantify respiratory-induced deformation in the pancreas and pancreatic lesions using XD-GRASP (eXtra-Dimensional Golden-angle RAdial Sparse Parallel), MRI. STUDY TYPE/METHODS:W) imaging were studied. SUBJECTS/METHODS:Thirty-two patients (12 male and 20 female) including nine with pancreatic lesions constituted our study cohort. FIELD STRENGTH/SEQUENCE/UNASSIGNED:WI contrast-enhanced gradient echo radial free-breathing acquisition. ASSESSMENT/RESULTS:Using the XD-GRASP imaging technique, the acquired free-breathing radial data were sorted and binned into 10 consecutive respiratory motion states that were jointly reconstructed. 3D deformation fields along the respiratory dimension were computed using an optical flow method and were analyzed in the pancreas. STATISTICAL TESTS/UNASSIGNED:The Wilcoxon signed-rank test was used to assess the difference in average displacement across pancreatic regions, while the Wilcoxon rank-sum test was used for displacement differences between patients with and without tumors. The interclass correlation coefficient (ICC) was computed to assess consistency between observers for each image quality measure. RESULTS:There was a significantly larger displacement in the pancreatic tail compared with the head (8.2 ± 3.7 mm > 5.8 ± 2.4 mm; P < 0.001) and body regions (8.2 ± 3.7 mm > 6.6 ± 2.9 mm; P < 0.001). Furthermore, there was reduced normalized average displacement in patients with pancreatic lesions compared with subjects without lesions (0.33 ± 0.1 < 0.69 ± 0.26, P < 0.001 for the head; 0.30 ± 0.1 < 0.84 ± 0.31, P < 0.001 for the body; and 0.44 ± 0.31 < 1.08 ± 0.53, P < 0.001 for the tail, respectively). DATA CONCLUSION/UNASSIGNED:Free-breathing respiratory motion-sorted XD-GRASP MRI has the potential to noninvasively characterize the biomechanical properties of the pancreas by quantifying breathing-induced mechanical displacement. LEVEL OF EVIDENCE/METHODS:4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019.

Incidence of kidney cancer is steadily rising likely due to incidental detection of small renal masses. Nearly 20% of all small renal masses (less than 4cm in size) are benign at pathology. Furthermore, these small renal cancers represents 70% of all newly diagnosed Renal Cell Cancers (RCC). Detection of small renal masses leads to management dilemma, as it is not always possible to characterise these lesions on conventional imaging. Inability to discriminate benign from malignant and indolent from aggressive tumour results in surgical treatment for many of these patients. Surgery provides excellent oncologic control but it is associated with increased morbidity. Treatment based on tumour aggressiveness will result in optimal outcome by selecting patients with aggressive tumour for surgery and avoiding unnecessary surgery in indolent tumours. Such a paradigm requires non-invasive methods to accurately diagnose tumours of different aggressiveness. Tumours of different histopathology differ in tumour aggressiveness. Imaging can help investigate renal tumour histopathology and aggressiveness and can impact treatment decision and lower treatment cost. Imaging can assist with: (A). Differentiating benign renal masses from malignant tumours. - Protenacious or hemorrhagic cysts are hyperdense on CT and T1 hyperintense on MRI. Differentiating these lesions from solid masses requires assessment of enhancement. To assess for enhancement we can obtain pre-and post-contrast imaging on CT or MRI. Dual energy CT permits a single phase CT imaging to assess for enhancement, thus decreasing radiation dose. Subtraction imaging on MRI is useful to assess for enhancement. - Benign angiomyolipoma (AML) contain bulk fat. This can be easily diagnosed on CT and MRI. - Lipid poor AML can be difficult to differentiate from other types of renal masses on CT imaging. MRI can be helpful in suggesting the diagnosis of lipid poor AML. Some of the MRI features that suggest diagnosis of AML include homogenous and uniform enhancement, homogenous T2 signal similar to that of muscle, and restricted diffusion with low ADC. Suggesting this diagnosis is important as diagnosis of lipid poor AML can be made confidently at core biopsy, thus avoiding surgery in these patients - It is nearly impossible to discriminate benign oncocytoma from chromophobe and clear cell subtypes of kidney cancers on conventional imaging. However, diffusion weighted imaging (DWI) and perfusion weighted imaging (PWI) has shown some promise in small pilot studies. (B). Tumour subtypes of solid R

PURPOSE/OBJECTIVE:To compare qualitative results obtained from computer-aided dual-ratio analysis on T1-weighted two-point Dixon, with T2*-corrected multi-echo Dixon and T2-corrected multi-echo single-voxel MR spectroscopy sequence (MRS) for evaluation of liver fat and iron at 3T. METHODS AND MATERIALS/METHODS:This retrospective, HIPAA-compliant, IRB-approved study included 479 patients with known or suspected liver disease. Two-point Dixon, multi-echo Dixon, and MR spectroscopy sequences were performed for each patient at 3T. A receiver-operating characteristic analysis was performed to compare the diagnostic performance in 80 patients using biopsy as the standard. Sensitivity, specificity, PPV, and NPV of qualitative two-point Dixon results, multi-echo Dixon (PDFF and R2*), and MRS (fat fraction and R2 water) for detection of hepatic steatosis and siderosis were assessed. RESULTS:, respectively. CONCLUSION/CONCLUSIONS:The computer-aided dual-ratio discrimination with two-point Dixon is a useful qualitative screening tool with high negative predictive value for hepatic steatosis and iron overload. Multi-echo Dixon and MRS have similar accuracy for detection of hepatic steatosis and iron overload at 3 Tesla.

OBJECTIVE:To quantify how surgeons translate two-dimensional (2D) CT or MRI data to a three-dimensional (3D) model and evaluate if 3D printed models improve tumor localization. MATERIALS AND METHODS/METHODS:Twenty patients with renal masses were randomly selected from our IRB approved prospective 3D modeling study. Three surgeons reviewed the clinically available CT or MRI data; and using computer-aided design (CAD) software, translated the renal tumor to the position on the kidney that corresponded with the image interpretation. The renal tumor location determined by each surgeon was compared to the true renal mass location determined by the segmented imaging data and the Dice Similarity Coefficient (DSC) was calculated to evaluate the spatial overlap accuracy. The exercise was repeated for a subset of patients with a 3D printed model. RESULTS:The mean DSC was 0.243 ± 0.236 for the entire cohort (n=60). There was no overlap between the actual renal tumor and renal tumor identified by the surgeons in 16/60 cases (26.67%). Seven cases were reviewed again by two surgeons in a different setting with a 3D printed renal cancer model. For these cases, the DSC improved from 0.277 ± 0.248 using imaging only to 0.796 ± 0.090 with the 3D printed model (p < 0.01). CONCLUSIONS:In this study, cognitive renal tumor localization based on CT and MRI data was poor. This study demonstrates that experienced surgeons cannot always translate 2D imaging studies into 3D. Furthermore, 3D printed models can improve tumor localization and potentially assist with appropriate surgical approach.

Cystic renal cell carcinoma (RCC) is almost certainly overdiagnosed and overtreated. Efforts to diagnose and treat RCC at a curable stage result in many benign neoplasms and indolent cancers being resected without clear benefit. This is especially true for cystic masses, which compared with solid masses are more likely to be benign and, when malignant, less aggressive. For more than 30 years, the Bosniak classification has been used to stratify the risk of malignancy in cystic renal masses. Although it is widely used and still effective, the classification does not formally incorporate masses identified at MRI or US or masses that are incompletely characterized but are highly likely to be benign, and it is affected by interreader variability and variable reported malignancy rates. The Bosniak classification system cannot fully differentiate aggressive from indolent cancers and results in many benign masses being resected. This proposed update to the Bosniak classification addresses some of these shortcomings. The primary modifications incorporate MRI, establish definitions for previously vague imaging terms, and enable a greater proportion of masses to enter lower-risk classes. Although the update will require validation, it aims to expand the number of cystic masses to which the Bosniak classification can be applied while improving its precision and accuracy for the likelihood of cancer in each class.

PURPOSE/OBJECTIVE:To compare 2D gradient-recalled echo (GRE) and 2D spin-echo (SE) echo-planar imaging (EPI) MR elastography (MRE) for measurement of hepatic stiffness in adult patients with known or suspected liver disease at 3 Tesla. MATERIALS AND METHODS/METHODS:Three hundred and eighty-seven consecutive patients underwent MRE of the liver at 3 Tesla with 2D-GRE and 2D-SE-EPI sequences. 'Mean liver stiffness (LS)' calculated by averaging 3 ROIs in the right lobe, 'Maximum LS' calculated by an ROI in the right lobe; and 'Freehand LS' calculated by an ROI in the entire liver were measured by two independent readers. Inter-observer and inter-class variability in stiffness measurements were assessed. Stiffness values were correlated with degree of liver fibrosis (METAVIR scores) in 97 patients who underwent biopsy. The diagnostic performance was compared by a receiver-operating characteristic analysis. RESULTS:indicating iron overload). There is high reproducibility for both GRE and SE-EPI variants (ICC = 0.84-0.94 for both GRE and SE-EPI MRE). The highest sensitivity, specificity, and accuracy of differentiating mild fibrosis (F0-F2) from advanced fibrosis (F3-F4) are 0.84 (GRE Freehand measurement), 0.92 (GRE Maximum stiffness measurement), and 0.88 (GRE Freehand measurement), respectively. CONCLUSIONS:High intra-class correlation and intra-reader correlation are seen on measured hepatic stiffness for both 2D-GRE and 2D-SE-EPI MRE. 2D-SE-EPI has lower failure rate. Diagnostic performance of both sequences is equivalent, with highest sensitivity for 2D-GRE Freehand stiffness measurement, and highest specificity 2D-GRE Maximum stiffness measurement.

OBJECTIVE:The aim of this study was to determine which apparent diffusion coefficient-derived texture features are associated with malignancy in Bosniak IIF and III renal cystic lesions. METHODS:Twenty benign and 7 malignant Bosniak IIF (22) or III (5) renal cysts, as evaluated with magnetic resonance imaging, were assessed for progression to pathology-confirmed malignancy. Whole-cyst volumes of interest were manually segmented from apparent diffusion coefficient maps. Texture features were extracted from each volume of interest, including first-order histogram-based features and higher-order features, and data were analyzed with the Mann-Whitney U test to predict malignant progression. RESULTS:Eleven of 17 first-order features were significantly greater in benign compared with malignant cysts. Eight higher-order gray-level co-occurrence matrix (GLCM) texture features were significantly different between groups, 5 of which were greater in the benign population. CONCLUSIONS:Apparent diffusion coefficient-derived texture measures may help differentiate between benign and malignant Bosniak IIF and III cysts.

This article proposes a consensus nomenclature for fat-containing renal and adrenal masses at MRI to reduce variability, improve understanding, and enhance communication when describing imaging findings. The MRI appearance of "macroscopic fat" occurs due to a sufficient number of aggregated adipocytes and results in one or more of: 1) intratumoral signal intensity (SI) loss using fat-suppression techniques, or 2) chemical shift artifact of the second kind causing linear or curvilinear India-ink (etching) artifact within or at the periphery of a mass at macroscopic fat-water interfaces. "Macroscopic fat" is most commonly observed in adrenal myelolipoma and renal angiomyolipoma (AML) and only rarely encountered in other adrenal cortical tumors and renal cell carcinomas (RCC). Nonlinear noncurvilinear signal intensity loss on opposed-phase (OP) compared with in-phase (IP) chemical shift MRI (CSI) may be referred to as "microscopic fat" and is due to: a) an insufficient amount of adipocytes, or b) the presence of fat within tumor cells. Determining whether the signal intensity loss observed on CSI is due to insufficient adipocytes or fat within tumor cells cannot be accomplished using CSI alone; however, it can be inferred when other imaging features strongly suggest a particular diagnosis. Fat-poor AML are homogeneously hypointense on T₂ -weighted (T₂ W) imaging and avidly enhancing; signal intensity loss at OP CSI is uncommon, but when present is usually focal and is caused by an insufficient number of adipocytes within adjacent voxels. Conversely, clear-cell RCC are heterogeneously hyperintense on T₂ W imaging and avidly enhancing, with the signal intensity loss observed on OP CSI being typically diffuse and due to fat within tumor cells. Adrenal adenomas, adrenal cortical carcinoma, and adrenal metastases from fat-containing primary malignancies also show signal intensity loss on OP CSI due to fat within tumor cells and not from intratumoral adipocytes. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019.

OBJECTIVE:The purpose of this study is to increase the value of MRI by reengineering the MRI workflow at a new imaging center to shorten the interval (i.e., turnaround time) between each patient examination by at least 5 minutes. MATERIALS AND METHODS/METHODS:The elements of the MRI workflow that were optimized included the use of dockable tables, the location of patient preparation rooms, the number of doors per scanning room, and the storage location and duplication of coils. Turnaround times at the new center and at two existing centers were measured both for all patients and for situations when the next patient was ready to be brought into the scanner room after the previous patient's examination was completed. RESULTS:Workflow optimizations included the use of dockable tables, dedicated patient preparation rooms, two doors in each MRI room, positioning the scanner to provide the most direct path to the scanner, and coil storage in the preparation rooms, with duplication of the most frequently used coils. At the new imaging center, the median and mean (± SD) turnaround times for situations in which patients were ready for scanning were 115 seconds (95% CI, 113-117 seconds) and 132 ± 72 seconds (95% CI, 129-135 seconds), respectively, and the median and mean turnaround times for all situations were 141 seconds (95% CI, 137-146 seconds) and 272 ± 270 seconds (95% CI, 263-282 seconds), respectively. For existing imaging centers, the median and mean turnaround times for situations in which patients were ready for scanning were 430 seconds (95% CI, 424-434 seconds) and 460 ± 156 seconds (95% CI, 455-465 seconds), respectively, and the median and mean turnaround times for all situations were 481 seconds (95% CI, 474-486 seconds) and 537 ± 219 seconds (95% CI, 532-543 seconds), respectively. CONCLUSION/CONCLUSIONS:The optimized MRI workflow resulted in a mean time savings of 5 minutes 28 seconds per patient.

BACKGROUND:Patient-specific 3D models are being used increasingly in medicine for many applications including surgical planning, procedure rehearsal, trainee education, and patient education. To date, experiences on the use of 3D models to facilitate patient understanding of their disease and surgical plan are limited. The purpose of this study was to investigate in the context of renal and prostate cancer the impact of using 3D printed and augmented reality models for patient education. METHODS:Patients with MRI-visible prostate cancer undergoing either robotic assisted radical prostatectomy or focal ablative therapy or patients with renal masses undergoing partial nephrectomy were prospectively enrolled in this IRB approved study (n = 200). Patients underwent routine clinical imaging protocols and were randomized to receive pre-operative planning with imaging alone or imaging plus a patient-specific 3D model which was either 3D printed, visualized in AR, or viewed in 3D on a 2D computer monitor. 3D uro-oncologic models were created from the medical imaging data. A 5-point Likert scale survey was administered to patients prior to the surgical procedure to determine understanding of the cancer and treatment plan. If randomized to receive a pre-operative 3D model, the survey was completed twice, before and after viewing the 3D model. In addition, the cohort that received 3D models completed additional questions to compare usefulness of the different forms of visualization of the 3D models. Survey responses for each of the 3D model groups were compared using the Mann-Whitney and Wilcoxan rank-sum tests. RESULTS:All 200 patients completed the survey after reviewing their cases with their surgeons using imaging only. 127 patients completed the 5-point Likert scale survey regarding understanding of disease and surgical procedure twice, once with imaging and again after reviewing imaging plus a 3D model. Patients had a greater understanding using 3D printed models versus imaging for all measures including comprehension of disease, cancer size, cancer location, treatment plan, and the comfort level regarding the treatment plan (range 4.60-4.78/5 vs. 4.06-4.49/5, p < 0.05). CONCLUSIONS:All types of patient-specific 3D models were reported to be valuable for patient education. Out of the three advanced imaging methods, the 3D printed models helped patients to have the greatest understanding of their anatomy, disease, tumor characteristics, and surgical procedure.