Image Quality Evaluation in Dual-Energy CT of the Chest, Abdomen, and Pelvis in Obese Patients With Deep Learning Image Reconstruction.

OBJECTIVE: The aim of this study was to evaluate image quality in vascular and oncologic dual-energy computed tomography (CT) imaging studies performed with a deep learning (DL)-based image reconstruction algorithm in patients with body mass index of ≥30. METHODS: Vascular and multiphase oncologic staging dual-energy CT examinations were evaluated. Two image reconstruction algorithms were applied to the dual-energy CT data sets: standard of care Adaptive Statistical Iterative Reconstruction (ASiR-V) and TrueFidelity DL image reconstruction at 2 levels (medium and high). Subjective quality criteria were independently evaluated by 4 abdominal radiologists, and interreader agreement was assessed. Signal-to-noise ratio (SNR) and contrast-to-noise ratio were compared between image reconstruction methods. RESULTS: Forty-eight patients were included in this study, and the mean patient body mass index was 39.5 (SD, 7.36). TrueFidelity-High (DL-High) and TrueFidelity-Medium (DL-Med) image reconstructions showed statistically significant higher Likert scores compared with ASiR-V across all subjective image quality criteria ( P < 0.001 for DL-High vs ASiR-V; P < 0.05 for DL-Med vs ASiR-V), and SNRs for aorta and liver were significantly higher for DL-High versus ASiR-V ( P < 0.001). Contrast-to-noise ratio for aorta and SNR for aorta and liver were significantly higher for DL-Med versus ASiR-V ( P < 0.05). CONCLUSIONS: TrueFidelity DL image reconstruction provides improved image quality compared with ASiR-V in dual-energy CTs obtained in obese patients.

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.

BACKGROUND: Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. PURPOSE: To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. STUDY TYPE: Prospective. POPULATION: Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE: 3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence. ASSESSMENT: Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). STATISTICAL TEST: Levene's test, P < 0.05 corrected for multiple comparisons was considered statistically significant. RESULTS: The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size. DATA CONCLUSION: We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Radio-pathomic mapping model generated using annotations from five pathologists reliably distinguishes high-grade prostate cancer.

Purpose: Our study predictively maps epithelium density in magnetic resonance imaging (MRI) space while varying the ground truth labels provided by five pathologists to quantify the downstream effects of interobserver variability. Approach: Clinical imaging and postsurgical tissue from 48 recruited prospective patients were used in our study. Tissue was sliced to match the MRI orientation and whole-mount slides were stained and digitized. Data from 28 patients ( n = 33 slides) were sent to five pathologists to be annotated. Slides from the remaining 20 patients ( n = 123 slides) were annotated by one of the five pathologists. Interpathologist variability was measured using Krippendorff's alpha. Pathologist-specific radiopathomic mapping models were trained using a partial least-squares regression using MRI values to predict epithelium density, a known marker for disease severity. An analysis of variance characterized intermodel means difference in epithelium density. A consensus model was created and evaluated using a receiver operator characteristic classifying high grade versus low grade and benign, and was statistically compared to apparent diffusion coefficient (ADC). Results: Interobserver variability ranged from low to acceptable agreement (0.31 to 0.69). There was a statistically significant difference in mean predicted epithelium density values ( p < 0.001 ) between the five models. The consensus model outperformed ADC (areas under the curve = 0.80 and 0.71, respectively, p < 0.05 ). Conclusion: We demonstrate that radiopathomic maps of epithelium density are sensitive to the pathologist annotating the dataset; however, it is unclear if these differences are clinically significant. The consensus model produced the best maps, matched the performance of the best individual model, and outperformed ADC.

Gleason Probability Maps: A Radiomics Tool for Mapping Prostate Cancer Likelihood in MRI Space.

Prostate cancer is the most common noncutaneous cancer in men in the United States. The current paradigm for screening and diagnosis is imperfect, with relatively low specificity, high cost, and high morbidity. This study aims to generate new image contrasts by learning a distribution of unique image signatures associated with prostate cancer. In total, 48 patients were prospectively recruited for this institutional review board-approved study. Patients underwent multiparametric magnetic resonance imaging 2 weeks before surgery. Postsurgical tissues were annotated by a pathologist and aligned to the in vivo imaging. Radiomic profiles were generated by linearly combining 4 image contrasts (T2, apparent diffusion coefficient [ADC] 0-1000, ADC 50-2000, and dynamic contrast-enhanced) segmented using global thresholds. The distribution of radiomic profiles in high-grade cancer, low-grade cancer, and normal tissues was recorded, and the generated probability values were applied to a naive test set. The resulting Gleason probability maps were stable regardless of training cohort, functioned independent of prostate zone, and outperformed conventional clinical imaging (area under the curve [AUC] = 0.79). Extensive overlap was seen in the most common image signatures associated with high- and low-grade cancer, indicating that low- and high-grade tumors present similarly on conventional imaging.

Multiparametric Prostate MR Imaging: Impact on Clinical Staging and Decision Making.

Meaningful changes to the approach of prostate cancer staging and management have been made over the past decade with increasing demand for high-quality multiparametric MR imaging (mpMRI) of the prostate. This article focuses on the evolving paradigm of prostate cancer staging, with emphasis on the role of mpMRI on staging and its integration into clinical decision making. Current prostate cancer staging systems are defined and mpMRI's role in the detection of non-organ-confined disease and how it has an impact on the selection of appropriate next steps are discussed. Several imaging pitfalls, limitations, and future directions of mpMRI also are discussed.

Energy-Specific Optimization of Attenuation Thresholds for Low-Energy Virtual Monoenergetic Images in Renal Lesion Evaluation.

OBJECTIVE: The purpose of this study was to determine in vitro and in vivo the optimal threshold for renal lesion vascularity at low-energy (40-60 keV) virtual monoenergetic imaging. MATERIALS AND METHODS: A rod simulating unenhanced renal parenchymal attenuation (35 HU) was fitted with a syringe containing water. Three iodinated solutions (0.38, 0.57, and 0.76 mg I/mL) were inserted into another rod that simulated enhanced renal parenchyma (180 HU). Rods were inserted into cylindric phantoms of three different body sizes and scanned with single- and dual-energy MDCT. In addition, 102 patients (32 men, 70 women; mean age, 66.8 ± 12.9 [SD] years) with 112 renal lesions (67 nonvascular, 45 vascular) measuring 1.1-8.9 cm underwent single-energy unenhanced and contrast-enhanced dual-energy CT. Optimal threshold attenuation values that differentiated vascular from nonvascular lesions at 40-60 keV were determined. RESULTS: Mean optimal threshold values were 30.2 ± 3.6 (standard error), 20.9 ± 1.3, and 16.1 ± 1.0 HU in the phantom, and 35.9 ± 3.6, 25.4 ± 1.8, and 17.8 ± 1.8 HU in the patients at 40, 50, and 60 keV. Sensitivity and specificity for the thresholds did not change significantly between low-energy and 70-keV virtual monoenergetic imaging (sensitivity, 87-98%; specificity, 90-91%). The AUC from 40 to 70 keV was 0.96 (95% CI, 0.93-0.99) to 0.98 (95% CI, 0.95-1.00). CONCLUSION: Low-energy virtual monoenergetic imaging at energy-specific optimized attenuation thresholds can be used for reliable characterization of renal lesions.

Renal Lesion Characterization with Spectral CT: Determining the Optimal Energy for Virtual Monoenergetic Reconstruction.

Purpose To investigate the relationship between energy level of virtual monoenergetic (VM) imaging and sensitivity in the detection of minimally enhancing renal lesions. Materials and Methods Phantoms simulating unenhanced and contrast material-enhanced renal parenchyma were equipped with inserts containing different concentrations of iodine (range, 0-1.15 mg iodine per milliliter). A total of 180 patients (117 men; mean age, 65.2 years ± 13.0 [standard deviation]) with 194 (62 solid, 132 cystic) renal lesions larger than 10 mm in diameter underwent unenhanced single-energy CT and contrast-enhanced dual-energy CT. VM imaging data sets were created for 70, 80, 90, and 100 keV. Renal lesions were measured, and enhancement was calculated. Area under the receiver operating characteristic curve (AUC) for renal lesion characterization was determined by using the DeLong method. Results The AUC was highest at 70 keV and decreased as energy increased toward 100 keV. AUC in the phantom decreased from 98% (95% confidence interval [CI]: 95, 100) at 70 keV to 88% (95% CI: 79, 96) at 100 keV (P = .004). AUC in patients decreased from 96% (95% CI: 94, 98) at 70 keV to 79% (95% CI: 71, 86) at 100 keV (P = .001). In patients with an enhancement threshold of 15 HU, sensitivity in the detection of solid renal lesions decreased between from 91% (49 of 62 [95% CI: 78, 97]) at 70 keV to 48% (33 of 62 [95% CI: 25, 71]) at 100 keV (P < .05), with no change in specificity (93% [120 of 132 {95% CI: 87, 97}] at 70 keV, 97% [125 of 132 {95% CI: 92, 99}] at 100 keV). Conclusion There is a reduction in diagnostic accuracy for renal lesion characterization with increasing VM imaging energy. The 70-keV setting may provide an optimal trade-off between sensitivity and specificity. © RSNA, 2018 Online supplemental material is available for this article.

Multiparametric Prostate MR Imaging: Impact on Clinical Staging and Decision Making.

Meaningful changes to the approach of prostate cancer staging and management have been made over the past decade with increasing demand for high-quality multiparametric MR imaging (mpMRI) of the prostate. This article focuses on the evolving paradigm of prostate cancer staging, with emphasis on the role of mpMRI on staging and its integration into clinical decision making. Current prostate cancer staging systems are defined and mpMRI's role in the detection of non-organ-confined disease and how it has an impact on the selection of appropriate next steps are discussed. Several imaging pitfalls, limitations, and future directions of mpMRI also are discussed.

Left Anterior Descending Coronary Artery and Multiple Peripheral Mycotic Aneurysms Due to Mycobacterium Bovis Following Intravesical Bacillus Calmette-Guerin Therapy: A Case Report.

The use of live attenuated intravesicular Bacillus Calmette-Guerin (BCG) therapy is a generally accepted safe and effective method for the treatment of superficial transitional cell carcinoma (TCC) of the bladder. Although rare, < 5% of patient's treated with intravesicular BCG therapy may develop potentially serious complications, including localized infections to the genitourinary tract, mycotic aneurysms and osteomyelitis. We present here a case of a 63-year-old male who developed left coronary and multiple peripheral M. Bovis mycotic aneurysms as a late complication of intravesicular BCG therapy for superficial bladder cancer. The patient initially presented with acute onset pain and swelling in the left knee > 2 years following initial therapy, and initial workup revealed a ruptured saccular aneurysm of the left popliteal artery as well as incidental bilateral common femoral artery aneurysms. Following endovascular treatment and additional workup, the patient was discovered to have additional aneurysms in the right popliteal artery and left anterior descending artery (LAD). Surgical pathology and bacterial cultures obtained from the excised femoral aneurysms and surgical groin wounds were positive for Mycobacterium Bovis, and the patient was initiated on a nine-month antimycobacterial course of isoniazid, rifampin and ethambutol. Including the present case, there has been a total of 32 reported cases of mycotic aneurysms as a complication from intravesicular BCG therapy, which we will review here. The majority of reported cases involve the abdominal aorta; however, this represents the first known reported case of a coronary aneurysm.

Rapid, robotic, small-scale protein production for NMR screening and structure determination.

Three-dimensional protein structure determination is a costly process due in part to the low success rate within groups of potential targets. Conventional validation methods eliminate the vast majority of proteins from further consideration through a time-consuming succession of screens for expression, solubility, purification, and folding. False negatives at each stage incur unwarranted reductions in the overall success rate. We developed a semi-automated protocol for isotopically-labeled protein production using the Maxwell-16, a commercially available bench top robot, that allows for single-step target screening by 2D NMR. In the span of a week, one person can express, purify, and screen 48 different (15)N-labeled proteins, accelerating the validation process by more than 10-fold. The yield from a single channel of the Maxwell-16 is sufficient for acquisition of a high-quality 2D (1)H-(15)N-HSQC spectrum using a 3-mm sample cell and 5-mm cryogenic NMR probe. Maxwell-16 screening of a control group of proteins reproduced previous validation results from conventional small-scale expression screening and large-scale production approaches currently employed by our structural genomics pipeline. Analysis of 18 new protein constructs identified two potential structure targets that included the second PDZ domain of human Par-3. To further demonstrate the broad utility of this production strategy, we solved the PDZ2 NMR structure using [U-(15)N,(13)C] protein prepared using the Maxwell-16. This novel semi-automated protein production protocol reduces the time and cost associated with NMR structure determination by eliminating unnecessary screening and scale-up steps.

A whole-animal microplate assay for metabolic rate using zebrafish.

Regulation of whole-body metabolism and energy homeostasis has been shown to require signaling between multiple organs. To identify genetic programs that determine metabolic rate, and compounds that can modify it, a whole-animal assay amenable to large-scale screening was developed. The direct correlation of acid production with metabolic rate was exploited to use a noninvasive colorimetric assay for acid secretion by individual zebrafish larvae in a 96-well plate format. A 3-fold increase in metabolic rate was detected that accompanied development between 24 and 96 h postfertilization. Dynamic changes in metabolic rate were also detected in response to different conditions such as temperature and drug treatments, in general agreement with the rate of oxygen consumption measured concomitantly. This assay was used to measure metabolic rate in the progeny of fish known to carry a recessive mutation in a gene required for ribosome biogenesis ( npo(fW07-g)), which would be expected to reduce energy consumption. A strong correlation was found (p < 10(-6) ) between reduced metabolic rate and genotype even before the developmental defect was visually evident. These studies support the conclusion that whole-animal acid secretion can be used as a readout for energy metabolism, thus enabling large-scale screening for genetic and chemical regulators of metabolic rate in a vertebrate.

Enhanced bacterial protein expression during auto-induction obtained by alteration of lac repressor dosage and medium composition.

The auto-induction method of protein expression in E. coli is based on diauxic growth resulting from dynamic function of lac operon regulatory elements (lacO and LacI) in mixtures of glucose, glycerol, and lactose. The results show that successful execution of auto-induction is strongly dependent on the plasmid promoter and repressor construction, on the oxygenation state of the culture, and on the composition of the auto-induction medium. Thus expression hosts expressing high levels of LacI during aerobic growth exhibit reduced ability to effectively complete the auto-induction process. Manipulation of the promoter to decrease the expression of LacI altered the preference for lactose consumption in a manner that led to increased protein expression and partially relieved the sensitivity of the auto-induction process to the oxygenation state of the culture. Factorial design methods were used to optimize the chemically defined growth medium used for expression of two model proteins, Photinus luciferase and enhanced green fluorescent protein, including variations for production of both unlabeled and selenomethionine-labeled samples. The optimization included studies of the expression from T7 and T7-lacI promoter plasmids and from T5 phage promoter plasmids expressing two levels of LacI. Upon the basis of the analysis of over 500 independent expression results, combinations of optimized expression media and expression plasmids that gave protein yields of greater than 1000 mug/mL of expression culture were identified.