Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy.

BACKGROUND: Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST). PURPOSE: To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST. STUDY TYPE: Prospective. POPULATION: Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR). FIELD STRENGTH/SEQUENCE: 3.0 T/reduced field of view single-shot echo-planar DTI sequence. ASSESSMENT: Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery. STATISTICAL TESTS: Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant. RESULTS: 47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm2 /s). DATA CONCLUSION: Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting the response to NAST in TNBC. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.

Whole-body MRI for staging prostate cancer: a narrative review.

OBJECTIVE: To present a narrative review regarding the diagnostic accuracy of whole-body magnetic resonance imaging (WBMRI) in staging patients with high-risk prostate cancer (HRPCa) and compare it to established imaging modalities. METHODS: A narrative review was carried out using PubMed using the following keywords: 'whole body', 'magnetic resonance imaging', 'MRI', 'prostate cancer', 'risk stratification', and 'staging'. Articles that evaluated WBMRI as the imaging modality to stage patients with HRPCa were included, while studies that solely assessed for biochemical recurrence or metastatic disease progression were excluded. RESULTS: In the evaluation of lymphatic metastases, WBMRI has demonstrated a comparable, if not improved, sensitivity and specificity compared to conventional imaging of computed tomography (CT). Furthermore, WBMRI demonstrates improved sensitivity and specificity in detecting bone metastases compared to bone scintigraphy (BS). However, with advent of prostate-specific membrane antigen (PSMA) radioligands for positron emission tomography (PET), the diagnostic performance of WBMRI to detect metastatic disease appears inferior. CONCLUSIONS: The diagnostic capabilities of WBMRI exceed that of conventional imaging of CT and BS in detecting metastatic disease in patients with HRPCa. However, WBMRI does not perform as well as PSMA PET/CT. Further study on cost comparisons between WBMRI and PSMA PET/CT are needed, as well as evaluations of combined PSMA PET/MRI are needed.

A Feasibility Study on Deep Learning Reconstruction to Improve Image Quality With PROPELLER Acquisition in the Setting of T2-Weighted Gynecologic Pelvic Magnetic Resonance Imaging.

OBJECTIVES: Evaluate deep learning (DL) to improve the image quality of the PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction technique) for 3 T magnetic resonance imaging of the female pelvis. METHODS: Three radiologists prospectively and independently compared non-DL and DL PROPELLER sequences from 20 patients with a history of gynecologic malignancy. Sequences with different noise reduction factors (DL 25%, DL 50%, and DL 75%) were blindly reviewed and scored based on artifacts, noise, relative sharpness, and overall image quality. The generalized estimating equation method was used to assess the effect of methods on the Likert scales. Quantitatively, the contrast-to-noise ratio and signal-to-noise ratio (SNR) of the iliac muscle were calculated, and pairwise comparisons were performed based on a linear mixed model. P values were adjusted using the Dunnett method. Interobserver agreement was assessed using the κ statistic. P value was considered statistically significant at less than 0.05. RESULTS: Qualitatively, DL 50 and DL 75 were ranked as the best sequences in 86% of cases. Images generated by the DL method were significantly better than non-DL images ( P < 0.0001). Iliacus muscle SNR on DL 50 and DL 75 was significantly better than non-DL images ( P < 0.0001). There was no difference in contrast-to-noise ratio between the DL and non-DL techniques in the iliac muscle. There was a high percent agreement (97.1%) in terms of DL sequences' superior image quality (97.1%) and sharpness (100%) relative to non-DL images. CONCLUSION: The utilization of DL reconstruction improves the image quality of PROPELLER sequences with improved SNR quantitatively.

Serum trimethylamine-N-oxide is associated with incident type 2 diabetes in middle-aged and older adults: a prospective cohort study.

BACKGROUND: The role of trimethylamine-N-oxide (TMAO) in the development of diabetes remains controversial, and prospective data are few. We aimed to investigate the association between serum TMAO and incident type 2 diabetes in middle-aged and older adults. METHODS: This study was based on the Guangzhou Nutrition and Health Study (GNHS), a community-based prospective cohort study in China. A total of 2088 diabetes-free participants aged 40-75 years were included from 2008 to 2010. Incident type 2 diabetes was ascertained during follow-up visits. Baseline serum TMAO was measured by high-performance liquid chromatography with online electrospray ionization tandem mass spectrometry. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for diabetes across tertiles of serum TMAO were calculated using Cox proportional hazard models. Prospective associations of serum TMAO with changes in glycemic traits (fasting glucose, HbA1c, insulin, HOMA-IR) over time were estimated using linear mixed-effects models (LMEMs). RESULTS: We ascertained 254 incident type 2 diabetes cases during a median follow-up of 8.9 years. The median (interquartile range) of serum TMAO was 1.54 (0.86-2.91) µmol/L. From the first to the third tertile of serum TMAO, the multivariable-adjusted HRs for diabetes were 1.00 (reference), 1.17 (95% CI: 0.84-1.61), and 1.42 (95% CI: 1.03-1.96) (P-trend = 0.031). LMEMs showed that the estimated yearly change in fasting glucose was 0.011 (0.001-0.022) mmol/L/y in the highest tertile of serum TMAO, compared with the lowest tertile (P-interaction = 0.044). Serum TMAO was not associated with longitudinal changes in HbA1c, insulin or HOMA-IR. CONCLUSIONS: Our findings suggested that higher serum TMAO was associated with a higher risk of type 2 diabetes and an increase in fasting glucose among middle-aged and older Chinese adults. TRIAL REGISTRATION: NCT03179657. https://clinicaltrials.gov/ct2/show/NCT03179657?term=NCT03179657&draw=2&rank=1.

Quantitative Apparent Diffusion Coefficients From Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer.

BACKGROUND: Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple-negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region (PTR) has been reported to be a negative prognostic factor in TNBC. PURPOSE: To determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) predict the response to NAST in TNBC. STUDY TYPE: Prospective. POPULATION/SUBJECTS: A total of 108 patients with biopsy-proven TNBC who underwent NAST and definitive surgery during 2015-2020. FIELD STRENGTH/SEQUENCE: A 3.0 T/rFOV single-shot diffusion-weighted echo-planar imaging sequence (DWI). ASSESSMENT: Three scans were acquired longitudinally (pretreatment, after two cycles of NAST, and after four cycles of NAST). For each scan, 11 ADC histogram features (minimum, maximum, mean, median, standard deviation, kurtosis, skewness and 10th, 25th, 75th, and 90th percentiles) were extracted from tumors and from PTRs of 5 mm, 10 mm, 15 mm, and 20 mm in thickness with inclusion and exclusion of fat-dominant pixels. STATISTICAL TESTS: ADC features were tested for prediction of pCR, both individually using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC), and in combination in multivariable models with k-fold cross-validation. A P value < 0.05 was considered statistically significant. RESULTS: Fifty-one patients (47%) had pCR. Maximum ADC from PTR, measured after two and four cycles of NAST, was significantly higher in pCR patients (2.8 ± 0.69 vs 3.5 ± 0.94 mm2 /sec). The top-performing feature for prediction of pCR was the maximum ADC from the 5-mm fat-inclusive PTR after cycle 4 of NAST (AUC: 0.74; 95% confidence interval: 0.64, 0.84). Multivariable models of ADC features performed similarly for fat-inclusive and fat-exclusive PTRs, with AUCs ranging from 0.68 to 0.72 for the cycle 2 and cycle 4 scans. DATA CONCLUSION: Quantitative ADC features from PTRs may serve as early predictors of the response to NAST in TNBC. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.

Tumor necrosis by pretreatment breast MRI: association with neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC).

PURPOSE: To determine if tumor necrosis by pretreatment breast MRI and its quantitative imaging characteristics are associated with response to NAST in TNBC. METHODS: This retrospective study included 85 TNBC patients (mean age 51.8 ± 13 years) with MRI before NAST and definitive surgery during 2010-2018. Each MRI included T2-weighted, diffusion-weighted (DWI), and dynamic contrast-enhanced (DCE) imaging. For each index carcinoma, total tumor volume including necrosis (TTV), excluding necrosis (TV), and the necrosis-only volume (NV) were segmented on early-phase DCE subtractions and DWI images. NV and %NV were calculated. Percent enhancement on early and late phases of DCE and apparent diffusion coefficient were extracted from TTV, TV, and NV. Association between necrosis with pathological complete response (pCR) was assessed using odds ratio (OR). Multivariable analysis was used to evaluate the prognostic value of necrosis with T stage and nodal status at staging. Mann-Whitney U tests and area under the curve (AUC) were used to assess performance of imaging metrics for discriminating pCR vs non-pCR. RESULTS: Of 39 patients (46%) with necrosis, 17 had pCR and 22 did not. Necrosis was not associated with pCR (OR, 0.995; 95% confidence interval [CI] 0.4-2.3) and was not an independent prognostic factor when combined with T stage and nodal status at staging (P = 0.46). None of the imaging metrics differed significantly between pCR and non-pCR in patients with necrosis (AUC < 0.6 and P > 0.40). CONCLUSION: No significant association was found between necrosis by pretreatment MRI or the quantitative imaging characteristics of tumor necrosis and response to NAST in TNBC.

Synthetic generation of DSC-MRI-derived relative CBV maps from DCE MRI of brain tumors.

PURPOSE: Perfusion MRI with gadolinium-based contrast agents is useful for diagnosis and treatment response evaluation of brain tumors. Dynamic susceptibility contrast (DSC) MRI and dynamic contrast enhanced (DCE) MRI are two gadolinium-based contrast agent perfusion imaging techniques that provide complementary information about the tumor vasculature. However, each requires a separate administration of a gadolinium-based contrast agent. The purpose of this retrospective study was to determine the feasibility of synthesizing relative cerebral blood volume (rCBV) maps, as computed from DSC MRI, from DCE MRI of brain tumors. METHODS: One hundred nine brain-tumor patients underwent both DCE and DSC MRI. Relative CBV maps were computed from the DSC MRI, and blood plasma volume fraction maps were computed from the DCE MRIs. Conditional generative adversarial networks were developed to synthesize rCBV maps from the DCE MRIs. Tumor-to-white matter ratios were calculated from real rCBV, synthetic rCBV, and plasma volume fraction maps and compared using correlation analysis. Real and synthetic rCBV in white and gray matter regions were also compared. RESULTS: Pearson correlation analysis showed that both the tumor rCBV and tumor-to-white matter ratios in the synthetic and real rCBV maps were strongly correlated (ρ = 0.87, P < .05 and ρ = 0.86, P < .05, respectively). Tumor plasma volume fraction and real rCBV were not strongly correlated (ρ = 0.47). Bland-Altman analysis showed a mean difference between the synthetic and real rCBV tumor-to-white matter ratios of 0.20 with a 95% confidence interval of ±0.47. CONCLUSION: Realistic rCBV maps can be synthesized from DCE MRI and contain quantitative information, enabling robust brain-tumor perfusion imaging of DSC and DCE parameters with a single gadolinium-based contrast agent administration.

Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer.

BACKGROUND: Dynamic contrast-enhanced (DCE) MRI is useful for diagnosis and assessment of treatment response in breast cancer. Fast DCE MRI offers a higher sampling rate of contrast enhancement curves in comparison to conventional DCE MRI, potentially characterizing tumor perfusion kinetics more accurately for measurement of functional tumor volume (FTV) as a predictor of treatment response. PURPOSE: To investigate FTV by fast DCE MRI as a predictor of neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). STUDY TYPE: Prospective. POPULATION/SUBJECTS: Sixty patients with biopsy-confirmed TNBC between December 2016 and September 2020. FIELD STRENGTH/SEQUENCE: A 3.0 T/3D fast spoiled gradient echo-based DCE MRI ASSESSMENT: Patients underwent MRI at baseline and after four cycles (C4) of NAST, followed by definitive surgery. DCE subtraction images were analyzed in consensus by two breast radiologists with 5 (A.H.A.) and 2 (H.S.M.) years of experience. Tumor volumes (TV) were measured on early and late subtractions. Tumors were segmented on 1 and 2.5-minute early phases subtractions and FTV was determined using optimized signal enhancement thresholds. Interpolated enhancement curves from segmented voxels were used to determine optimal early phase timing. STATISTICAL TESTS: Tumor volumes were compared between patients who had a pathologic complete response (pCR) and those who did not using the area under the receiver operating curve (AUC) and Mann-Whitney U test. RESULTS: About 26 of 60 patients (43%) had pCR. FTV at 1 minute after injection at C4 provided the best discrimination between pCR and non-pCR, with AUC (95% confidence interval [CI]) = 0.85 (0.74,0.95) (P < 0.05). The 1-minute timing was optimal for FTV measurements at C4 and for the change between C4 and baseline. TV from the early phase at C4 also yielded a good AUC (95%CI) of 0.82 (0.71,0.93) (P < 0.05). DATA CONCLUSION: FTV and TV measured at 1 minute after injection can predict response to NAST in TNBC. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: 4.

Computer-aided Detection of Brain Metastases in T1-weighted MRI for Stereotactic Radiosurgery Using Deep Learning Single-Shot Detectors.

Background Brain metastases are manually identified during stereotactic radiosurgery (SRS) treatment planning, which is time consuming and potentially challenging. Purpose To develop and investigate deep learning (DL) methods for detecting brain metastasis with MRI to aid in treatment planning for SRS. Materials and Methods In this retrospective study, contrast material-enhanced three-dimensional T1-weighted gradient-echo MRI scans from patients who underwent gamma knife SRS from January 2011 to August 2018 were analyzed. Brain metastases were manually identified and contoured by neuroradiologists and treating radiation oncologists. DL single-shot detector (SSD) algorithms were constructed and trained to map axial MRI slices to a set of bounding box predictions encompassing metastases and associated detection confidences. Performances of different DL SSDs were compared for per-lesion metastasis-based detection sensitivity and positive predictive value (PPV) at a 50% confidence threshold. For the highest-performing model, detection performance was analyzed by using free-response receiver operating characteristic analysis. Results Two hundred sixty-six patients (mean age, 60 years ± 14 [standard deviation]; 148 women) were randomly split into 80% training and 20% testing groups (212 and 54 patients, respectively). For the testing group, sensitivity of the highest-performing (baseline) SSD was 81% (95% confidence interval [CI]: 80%, 82%; 190 of 234) and PPV was 36% (95% CI: 35%, 37%; 190 of 530). For metastases measuring at least 6 mm, sensitivity was 98% (95% CI: 97%, 99%; 130 of 132) and PPV was 36% (95% CI: 35%, 37%; 130 of 366). Other models (SSD with a ResNet50 backbone, SSD with focal loss, and RetinaNet) yielded lower sensitivities of 73% (95% CI: 72%, 74%; 171 of 234), 77% (95% CI: 76%, 78%; 180 of 234), and 79% (95% CI: 77%, 81%; 184 of 234), respectively, and lower PPVs of 29% (95% CI: 28%, 30%; 171 of 581), 26% (95% CI: 26%, 26%; 180 of 681), and 13% (95% CI: 12%, 14%; 184 of 1412). Conclusion Deep-learning single-shot detector models detected nearly all brain metastases that were 6 mm or larger with limited false-positive findings using postcontrast T1-weighted MRI. © RSNA, 2020 See also the editorial by Kikinis and Wells in this issue.

Breast density, MR imaging biomarkers, and breast cancer risk.

Mammographic breast density and various breast MRI features are imaging biomarkers that can predict a woman's future risk of breast cancer. While mammographic density (MD) has been established as an independent risk factor for the development of breast cancer, MD assessment methods need to be accurate and reproducible for widespread clinical use in stratifying patients based on their risk. In addition, a number of breast MRI biomarkers using contrast-enhanced and noncontrast-enhanced techniques are also being investigated as risk predictors. The validation and standardization of these breast MRI biomarkers will be necessary for population-based clinical implementation of patient risk stratification, as well. This review provides an update on MD assessment methods, breast MRI biomarkers, and their ability to predict breast cancer risk.

Genome-wide identification and expression profiling of glutathione transferase gene family under multiple stresses and hormone treatments in wheat (Triticum aestivum L.).

BACKGROUND: Glutathione transferases (GSTs), the ancient, ubiquitous and multi-functional proteins, play significant roles in development, metabolism as well as abiotic and biotic stress responses in plants. Wheat is one of the most important crops, but the functions of GST genes in wheat were less studied. RESULTS: A total of 330 TaGST genes were identified from the wheat genome and named according to the nomenclature of rice and Arabidopsis GST genes. They were classified into eight classes based on the phylogenetic relationship among wheat, rice, and Arabidopsis, and their gene structure and conserved motif were similar in the same phylogenetic class. The 43 and 171 gene pairs were identified as tandem and segmental duplication genes respectively, and the Ka/Ks ratios of tandem and segmental duplication TaGST genes were less than 1 except segmental duplication gene pair TaGSTU24/TaGSTU154. The 59 TaGST genes were identified to have syntenic relationships with 28 OsGST genes. The expression profiling involved in 15 tissues and biotic and abiotic stresses suggested the different expression and response patterns of the TaGST genes. Furthermore, the qRT-PCR data showed that GST could response to abiotic stresses and hormones extensively in wheat. CONCLUSIONS: In this study, a large GST family with 330 members was identified from the wheat genome. Duplication events containing tandem and segmental duplication contributed to the expansion of TaGST family, and duplication genes might undergo extensive purifying selection. The expression profiling and cis-elements in promoter region of 330 TaGST genes implied their roles in growth and development as well as adaption to stressful environments. The qRT-PCR data of 14 TaGST genes revealed that they could respond to different abiotic stresses and hormones, especially salt stress and abscisic acid. In conclusion, this study contributed to the further functional analysis of GST genes family in wheat.

Development and clinical implementation of SeedNet: A sliding-window convolutional neural network for radioactive seed identification in MRI-assisted radiosurgery (MARS).

PURPOSE: To develop and evaluate a sliding-window convolutional neural network (CNN) for radioactive seed identification in MRI of the prostate after permanent implant brachytherapy. METHODS: Sixty-eight patients underwent prostate cancer low-dose-rate (LDR) brachytherapy using radioactive seeds stranded with positive contrast MR-signal seed markers and were scanned using a balanced steady-state free precession pulse sequence with and without an endorectal coil (ERC). A sliding-window CNN algorithm (SeedNet) was developed to scan the prostate images using 3D sub-windows and to identify the implanted radioactive seeds. The algorithm was trained on sub-windows extracted from 18 patient images. Seed detection performance was evaluated by computing precision, recall, F1 -score, false discovery rate, and false-negative rate. Seed localization performance was evaluated by computing the RMS error (RMSE) between the manually identified and algorithm-inferred seed locations. SeedNet was implemented into a clinical software package and evaluated on sub-windows extracted from 40 test patients. RESULTS: SeedNet achieved 97.6 ± 2.2% recall and 97.2 ± 1.9% precision for radioactive seed detection and 0.19 ± 0.04 mm RMSE for seed localization in the images acquired with an ERC. Without the ERC, the recall remained high, but the false-positive rate increased; the RMSE of the seed locations increased marginally. The clinical integration of SeedNet slightly increased the run-time, but the overall run-time was still low. CONCLUSION: SeedNet can be used to perform automated radioactive seed identification in prostate MRI after LDR brachytherapy. Image quality improvement through pulse sequence optimization is expected to improve SeedNet's performance when imaging without an ERC.

Diffusion-weighted MR imaging increases diagnostic accuracy of breast MR imaging for predicting axillary metastases in breast cancer patients.

PURPOSE: To evaluate the incremental value of diffusion-weighted imaging (DWI) to conventional MR imaging (CMRI) to predict ipsilateral metastatic axillary lymphadenopathy in patients with newly diagnosed breast cancer. SUBJECTS AND METHODS: In an IRB approved retrospective single-institution study, newly diagnosed consecutive breast cancer patients with pathological verification of axillary lymph node (LN) status who had undergone breast MR imaging, including DWI as part of their standard MRI between August 1, 2010, and December 31, 2010, were reviewed. Lesion size, tumor grade, and tissue prognostic factors were noted. Ipsilateral axillary LNs were evaluated using morphological criteria on CMRI. Apparent diffusion coefficient (ADC) values of suspicious ipsilateral LNs were obtained and compared with ADC values of contralateral benign axillary LNs. Receiver operating characteristic curves and multivariate logistic regression analyses were used using pathology as the gold standard. RESULTS: Eighty-five eligible patients were identified, with surgical pathology revealing 34 patients (40%) who had malignant and 51 (60%) had benign ipsilateral axillae. The sensitivity of CMRI was 79%, with a specificity of 81%, a positive predictive value (PPV) of 65%, and a negative predictive value (NPV) of 89%. On DWI, the mean ADC value was significantly lower for metastatic LNs (0.89 ± 0.18 × 10-3  mm2 /s) than for benign ipsilateral LNs (1.41 ± 0.21 × 10-3  mm2 /s; P < 0.0001). Using a cutoff ADC value of 0.985 × 10-3  mm2 /s, yielded improved sensitivity, specificity, PPV, and NPV of 83%, 98%, 95%, and 93%, respectively. CONCLUSION: Apparent diffusion coefficient values increase the specificity of CMRI for predicting ipsilateral axillary LN metastases in patients with newly diagnosed breast cancer.

American College of Radiology-Compliant Short Protocol Breast MRI for High-Risk Breast Cancer Screening: A Prospective Feasibility Study.

OBJECTIVE: The purpose of this study was to assess the feasibility of a short protocol for screening breast MRI that is noninferior to standard-of-care (SOC) MRI in image quality that complies with American College of Radiology accreditation requirements. SUBJECTS AND METHODS: In a prospective feasibility trial, 23 women at high risk underwent both an initial SOC MRI examination that included axial iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) and T1-weighted volume imaging for breast assessment (VIBRANT) dynamic contrast-enhanced sequences and a separate short breast MRI protocol comprising a fast spin-echo (FSE) triple-echo Dixon T2 sequence for T2-weighted imaging and a 3D dual-echo fast spoiled gradient-echo two-point Dixon sequence for dynamic contrast-enhanced imaging from October 1, 2015, through May 2, 2016. Image quality assessment was performed by three radiologists, who scored the images for fat saturation, artifact severity, and quality of normal anatomic structures. Enhancing lesions were evaluated according to BI-RADS MRI features. Quantitative analysis was performed by measuring the signal intensity of anatomic areas in each patient. RESULTS: The mean acquisition time for short-protocol breast MRI was 9.42 minutes and for SOC MRI was 22.09 minutes (p < 0.0001). The mean table times were 13.92 and 35.87 minutes (p < 0.0001). Compared with the FSE triple-echo Dixon T2 short-protocol breast MRI sequence, the IDEAL SOC MRI sequence had significantly worse motion artifact (p < 0.01) and fat saturation (p = 0.04). The other parameters did not differ significantly. Quantitative analysis showed that the FSE triple-echo Dixon T2 sequence had more effective fat saturation and higher tissue contrast. All five lesions were given the same assessments by the readers, and at BI-RADS lesion morphologic ranking, identical high image quality scores were assigned to both the VIBRANT and 3D dual-echo fast spoiled gradient-echo 2-point Dixon sequences. CONCLUSION: Short-protocol breast MRI comprising a T2-weighted sequence and a fast dynamic sequence with less than 10-minute acquisition time is feasible and has image quality at least equivalent to that of an SOC MRI protocol with a > 20-minute mean acquisition time. Larger studies comparing the cancer detection rate, sensitivity, and specificity of each imaging protocol are needed to determine whether short-protocol breast MRI can replace SOC MRI to screen patients at high breast cancer risk.

A flexible fast spin echo triple-echo Dixon technique.

PURPOSE: To develop a flexible fast spin echo (FSE) triple-echo Dixon (FTED) technique. METHODS: An FSE pulse sequence was modified by replacing each readout gradient with three fast-switching bipolar readout gradients with minimal interecho dead time. The corresponding three echoes were used to generate three raw images with relative phase shifts of -θ, 0, and θ between water and fat signals. A region growing-based two-point Dixon phase correction algorithm was used to joint process two separate pairs of the three raw images, yielding a final set of water-only and fat-only images. The flexible FTED technique was implemented on 1.5T and 3.0T scanners and evaluated in five subjects for fat-suppressed T2-weighted imaging and in one subject for post-contrast fat-suppressed T1-weighted imaging. RESULTS: The flexible FTED technique achieved a high data acquisition efficiency, comparable to that of FSE, and was flexible in scan protocols. The joint two-point Dixon phase correction algorithm helped to ensure consistency in the processing of the two separate pairs of raw images. Reliable and uniform separation of water and fat was achieved in all of the test cases. CONCLUSION: The flexible FTED technique incorporates the benefits of both FSE and Dixon imaging and provided more flexibility than the original FTED in applications such as fat-suppressed T2-weighted and T1-weighted imaging. Magn Reson Med 77:1049-1057, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Can reduced field-of-view diffusion sequence help assess microsatellite instability in FIGO stage 1 endometrial cancer?

PURPOSE: To determine if a reduced-field-of-view (rFOV) diffusion intravoxel incoherent motion (IVIM) sequence can differentiate the imaging characteristics of tumors with microsatellite instability (MSI) from those that are microsatellite stable (MSS) in patients with clinical FIGO stage IA endometrial cancer and if MRI can be used to determine MSI status. MATERIALS AND METHODS: Sagittal rFOV diffusion-weighted images were obtained in 12 patients on a 3T scanner using six b-values (0, 50, 100, 150, 200, and 600). These images were used to derive apparent diffusion coefficient (ADC), true diffusion coefficient (Dt ), pseudodiffusion (D*), and perfusion fraction (f). Regions of interest (ROIs) were drawn on the dynamic contrast-enhanced magnetic resonance imaging (MRI) sequence on an Advantage Windows workstation and were copied to the same location on IVIM-derived images. The ROI mean of these images was recorded and compared with the microsatellite status. The depth of myometrial invasion and IVIM-derived parameters were tabulated by microsatellite status. The Wilcoxon rank sum test was used to compare T1 postcontrast images and IVIM-derived images and microsatellite status. RESULTS: Six patients had MSS tumors and six had MSI tumors. MSS tumors had a significantly higher ADC value (P = 0.03) and Dt (P = 0.045) than the MSI tumors. There was no association between < and ≥ 50% depth of myometrial invasion (measured on pathology and MRI analysis) and MSI stability P > 0.99. CONCLUSION: IVIM, ADC and Dt may be able to determine microsatellite status noninvasively in patients with clinical FIGO stage I endometrial cancer. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:1216-1224.

Using MRI to non-invasively and accurately quantify preoperative hepatic steatosis.

BACKGROUND: The obesity epidemic has significantly increased the incidence and severity of hepatic steatosis in liver surgery patients and liver donors, potentially impacting postoperative liver regeneration and function. Development of a non-invasive means to quantify hepatic steatosis would facilitate selection of candidates for liver resection and transplant donation. METHODS: An IRB-approved protocol prospectively enrolled 28 patients with liver tumors requiring hepatic resection. In all patients, fast dual-echo gradient-echo MR images were acquired using 2-Point Dixon technique in 2D and 3D. The degree of steatosis was quantified by percent fat fraction (%FF) from in- and out-of-phase, and water-only and fat-only images. The technique-specific %FFs were compared to intraoperative and histopathological findings. RESULTS: For patients with >30% steatosis by histology, the mean %FF was 22% (SD ± 5.2%) compared to a mean %FF of 5.0% (SD ± 2.1%, p = 0.0001) in patients with <30% steatosis. Using scaled values for the MR-calculated %FF, all patients with >30% pathologic steatosis could be identified preoperatively. CONCLUSIONS: Quantitative MRI identified patients with clinically-relevant steatosis with 100% accuracy. These findings could have significant impact on the management of liver resection patients and transplant donors.

An improved region growing algorithm for phase correction in MRI.

PURPOSE: To develop an improved region-growing algorithm for phase correction in MRI. METHODS: Phase correction in MRI can sometimes be formulated as selecting a vector for each pixel of an image from two candidate vectors so that the orientation of the output is spatially smooth. Existing algorithms may run into difficulty in the presence of high noise, artifacts, or spatially isolated objects. In this study, we developed an improved region-growing algorithm to include the following novel and salient features: 1) automated quality guidance for determining the sequence of region growing, 2) joint consideration of two candidate vectors in selecting the output vector, and 3) automated segmentation during region growing for handling spatially isolated objects. The phase correction algorithm was tested in different body parts of five healthy volunteers at 3.0T and of one healthy volunteer at 1.5T for two-point Dixon water and fat imaging with flexible echo times. RESULTS: The algorithm achieved successful phase correction in all the data sets tested, providing improvement in areas of known difficulty, when compared with an algorithm lacking the new features. CONCLUSION: The improved region-growing algorithm can be used for reliable and robust phase correction even when regions of high noise, artifacts, or spatially isolated objects are present in an image. Magn Reson Med 76:519-529, 2016. © 2015 Wiley Periodicals, Inc.

Feasibility of a reduced field-of-view diffusion-weighted (rFOV) sequence in assessment of myometrial invasion in patients with clinical FIGO stage I endometrial cancer.

PURPOSE: To compare the clinical usefulness of reduced field-of-view diffusion-weighted imaging (rFOV) with other imaging techniques in determining the depth of myometrial invasion (DMI) in endometrial cancer. MATERIALS AND METHODS: In this prospective study we reviewed 3T magnetic resonance images of 51 patients with clinical Stage I endometrial cancer who underwent total abdominal hysterectomy with bilateral salphingoopherectomy within 3 days after imaging. rFOV with apparent diffusion coefficient reconstruction was obtained in three standard planes followed by sagittal T2 -weighted (T2 WI) images and 3D dynamic T1 -weighted and contrast-enhanced imaging (DCE MRI). Two radiologists with expertise in imaging gynecologic cancers evaluated images independently. The DMI was recorded on imaging and correlated with surgical pathology results. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for DMI were calculated (<50% vs. >50%). RESULTS: Compared with sagittal T2 WI + DCE MRI, rFOV imaging yielded greater specificity (82.2% vs. 90.0%, positive predictive value (42.8% vs. 60.0%), and accuracy (84.0% vs. 92%) for DMI determined by reader 1 and greater the sensitivity (83.3% vs. 100%) for DMI determined by reader 2. The error of measurement of DMI as a continuous variable in millimeters did not differ significantly between the rFOV and pathology results (P < 0.21). However, there was a statistically significant difference for the DMI measured on the dynamic sequence. The DMI on DCE was greater than that seen on pathology at P = 0.02. CONCLUSION: rFOV can be used to assess DMI in clinical Stage I endometrial cancer.

3-T breast diffusion-weighted MRI by echo-planar imaging with spectral spatial excitation or with additional spectral inversion recovery: an in vivo comparison of image quality.

OBJECTIVE: To compare conventional diffusion-weighted imaging (DWI) with spectral spatial excitation (cDWI) and an enhanced DWI with additional adiabatic spectral inversion recovery (eDWI) for 3-T breast magnetic resonance imaging (MRI). METHODS: Twenty-four patients were enrolled in the study with both cDWI and eDWI. Three breast radiologists scored cDWI and eDWI images of each patient for fat-suppression quality, geometric distortion, visibility of normal structure and biopsy-proven lesions, and overall image quality. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) for evaluable tissues were measured. Statistical tests were performed for qualitative and quantitative comparisons. RESULTS: Diffusion-weighted imaging with spectral spatial excitation yielded significantly higher CNR and SNR on a lesion basis, and higher glandular CNR and SNR and muscle SNR on a patient basis. Enhanced DWI also yielded significantly higher qualitative scores in all categories. No significant difference was found in ADC values. CONCLUSIONS: Enhanced DWI provided superior image quality and higher CNR and SNR on a lesion basis. Enhanced DWI can replace cDWI for 3-T breast DWI.