Natsuko Onishi¹, Jessica Gibbs¹, Wen Li¹, David C. Newitt¹, Elissa R. Price¹, Barbara LeStage², William F. Symmans³, Angela DeMichele⁴, Christina Yau⁵, The I-SPY 2 Imaging Working Group⁶, The I-SPY 2 Consortium⁶, Laura J. Esserman⁵, and Nola M. Hylton^1
1Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²I-SPY 2 Advocacy Group, San Francisco, CA, United States, ³MD Anderson Cancer Center, Houston, TX, United States, ⁴University of Pennsylvania, Philadelphia, PA, United States, ⁵Department of Surgery, University of California, San Francisco, San Francisco, CA, United States, ⁶Quantum Leap Healthcare Collaborative, San Francisco, CA, United States

In the I-SPY2 breast cancer trial, functional tumor volume (FTV) derived from dynamic contrast-enhanced MRI is used as a longitudinal measure of response to adjust patient randomization and evaluate drug efficacy. I-SPY2 is introducing a treatment “escalation” option, giving patients the opportunity to re-direct to potentially more effective treatment based on early indication of inferior response by MRI. We retrospectively investigated the ability of FTV reduction to predict inferior outcome. Combined criteria using FTV reduction at 3 and 6 weeks of treatment showed high PPV and high sensitivity in early detection of non-responders.

Aritrick Chatterjee^1,2, Tatjana Antic³, Alexander J Gallan⁴, Gladell P Paner³, Lawrence I-Kuei Lin⁵, Gregory S Karczmar^1,2, and Aytekin Oto^1,2
1Department of Radiology, University of Chicago, Chicago, IL, United States, ²Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, Chicago, IL, United States, ³Department of Pathology, University of Chicago, Chicago, IL, United States, ⁴Department of Pathology, Medical College of Wisconsin, Medical College of Wisconsin, WI, United States, ⁵JBS Consulting Services Inc., Carlsbad, CA, United States

We validated prostate tissue composition measured using HM-MRI by comparing with reference standard results from pathologists’ interpretation of clinical histopathology slides following whole mount prostatectomy. We are 95% confident that 90% of absolute paired differences (TDI_0.9) between HM-MRI and consensus results of pathologists were within 20.6% and 24.2% in measuring epithelium and lumen fractional volumes, respectively. These were less than our criterion of 30% and inter-pathologists’ agreement (22.3% for epithelium and 24.2% for lumen). Therefore, we accept the agreement performance of HM-MRI in measuring tissue composition measurement and consensus of pathologists is on par with the inter-raters (pathologists) agreement.

Tianyi Zhou¹, Liam Timms¹, Aya Hamadeh², David Drew³, Mukesh Harisinghani², and Srinivas Sridhar^1
1Department of Physics, Northeastern University, Boston, MA, United States, ²Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, ³Tufts Medical Center, Boston, MA, United States

A ferumoxytol-enhanced MRA technique using Ultrashort Time-to-Echo (UTE) sequences is demonstrated for kidney vasculature mapping and renal mass assessment. The blood volume (BV) map is calculated by scaling the post- and pre-contrast subtraction image from 0 to 1. BV is measured in one cystic mass (-6±7)% and one complex mass (17±8)% with sub-regions BV up to (32±10)% and (30±7)%. The quantification of BV provides a measurement of the distribution of micro-vessel density, reflecting the vascularity of the kidneys and masses. This technique potentially benefits surgical planning, renal mass characterization, and disease progression in patients with impaired renal function.

Neha Koonjoo¹, Bo Zhu^1,2, Danyal Bhutto^1,2,3, Arnaud Guidon⁴, Matthew Christensen^1,2, Mukesh Harisinghani¹, and Matthew S Rosen^1,2,5
1Department of Radiology, A.A Martinos Center for Biomedical Imaging / MGH, Charlestown, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Department of Biomedical Engineering, Boston University, Boston, MA, United States, ⁴GE Healthcare, Boston, MA, United States, ⁵Department of Physics, Harvard University, Cambridge, MA, United States

Ultra-high b-value Diffusion-weighted Prostate MR is gaining more attention in medical imaging, due to the non-invasiveness of imaging and to better contrast of malignant tissues as the lower diffusivity of water molecules can enable early diagnosis of cancer. The main drawback of MR at ultra-high b-value is the poor resultant SNR of the reconstructed images. We propose to improve the image quality of the prostate data acquired at b=2000 s/mm² using a machine learning based reconstruction approach. Significant increase in signal intensities in the central gland and peripheral zone of the prostate was observed in healthy subjects.

Rajiv S Deshpande^1,2, Michael C Langham², and Felix W Wehrli^2
1Dept. of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, ²Dept. of Radiology, University of Pennsylvania, Philadelphia, PA, United States

Type 2 diabetes mellitus is the leading cause of chronic kidney disease. Clinical measures of kidney function often detect dysfunction after irreversible damage has occurred. This highlights an unmet need for a biomarker that can enable earlier detection of disease. Quantification of renal metabolic rate of oxygen is a promising metric because it increases by 40-65% during the early stages of diabetic kidney disease. Here, we propose a “difference method” to quantify bilateral renal metabolic rate of oxygen by imaging above and below the renal vessels and exploiting conservation of blood flow rate and mass.

Anum S. Kazerouni¹, Yun An Chen¹, Callie Lind², Inyoung Youn³, Savannah C. Partridge¹, and Habib Rahbar^1
1Radiology, University of Washington, Seattle, WA, United States, ²Bioengineering, University of Washington, Seattle, WA, United States, ³Radiology, Sungkyunkwan University School of Medicine, Seoul, Korea, Republic of

We investigate the ability of quantitative measures derived from ultrafast DCE-MRI to improve breast MRI specificity for lesion diagnosis in a clinical setting. Sixty-nine women with BI-RADS 3, 4, or 5 lesions identified on clinical breast MRI exam, with subsequent diagnostic biopsy, were retrospectively identified. Ultrafast DCE-MRI was used to calculate semi-quantitative (bolus arrival time, max slope) and quantitative (K^trans, v_p) features for each lesion visible on the ultrafast series. Malignant lesions showed significantly higher v_p compared to benign lesions. Combined with qualitative assessment of visibility on ultrafast DCE-MRI (“yes”/“no”), v_p showed an AUC=0.73 for lesion diagnosis.

Yang Zhang^1,2, Yan-Lin Liu¹, Ke Nie², Jiejie Zhou³, Zhongwei Chen³, Jeon-Hor Chen¹, Meihao Wang³, and Min-Ying Su^1
1Department of Radiological Sciences, University of California, Irvine, CA, United States, ²Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ, United States, ³Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China

We developed two deep learning methods for breast MRI evaluation, first using Mask R-CNN for detection of suspicious areas, and then using ResNet50 for estimating the malignancy probability. These two networks were combined to test its diagnostic validity in two datasets. In Dataset-1, sensitivity=96.1% and specificity=78.1%. In Dataset-2, sensitivity=81.1% and specificity= 80.6%. We further characterized all false positives (FPs), and found other than confirmed benign lesions, FPs may come from vessels and asymmetric parenchymal enhancements, which can be further eliminated by other algorithms. The results suggest the potential of combined deep learning networks as a fully-automatic breast MRI CAD.

Muge Karaman^1,2, Shunan Che³, Guangyu Dan^1,2, Zheng Zhong^1,2, Han Ouyang³, Xiaohong Joe Zhou^1,2,4, and Xinming Zhao^3
1Center for MR Research, University of Illinois at Chicago, Chicago, IL, United States, ²Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, ³Department of Radiology, Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, China, ⁴Departments of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States

Neoadjuvant chemotherapy (NAC) has been shown to improve the outcome in patients with locally advanced inoperable or operable breast cancer. An early imaging assessment of response to NAC is critical for managing breast cancer to minimize the toxic side effects of ineffective chemotherapy. In this study, we have used an integrated diffusion-weighted imaging approach for simultaneous assessment of tissue cellularity, vascularity, and heterogeneity – DISMANTLE – from a full b-value spectrum to predict breast cancer’s response to NAC. Histogram features of pre-treatment DISMANTLE parameters were evaluated for predicting tumor response to NAC in terms of pathological complete response.

Rajat Thawani¹, Lina Gao², Ajay Mohinani², Alina Tudorica², Xin Li², Zahi Mitri¹, and Wei Huang^2
1Division of Hematology and Oncology, Oregon Health and Science University, Portland, OR, United States, ²Oregon Health and Science University, Portland, OR, United States

Neoadjuvant chemotherapy (NAC) is considered standard of care for locally advanced breast cancer. Pre- and post-NAC MRI is routinely used to assess response.  This study aims to investigate pre- and post-NAC quantitative DCE-MRI parameters, alone and in combination with clinico-pathologic variables, for prediction of breast cancer recurrence following NAC. 47 patients underwent DCE-MRI studies pre- and post-NAC. The results show that quantitative pharmacokinetic DCE-MRI parameters, whether alone or in combination with clinico-pathologic variables, outperformed tumor size measurement by conventional imaging in prediction of recurrence.  Furthermore, DCE-MRI parameters provided added value in predictive performance when combined with clinico-pathologic variables.

Ran Yan^1,2, Wakana Murakami¹, Shabnam Mortazavi¹, Tiffany Yu¹, Stephanie Lee-Felker¹, and Kyunghyun Sung^1,3
1Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States, ²Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ³Physics and Biology in Medicine IDP, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States

High background parenchymal enhancement (BPE) on breast MRI is related to increased breast cancer risk. In this study, we investigate possible differences in BPE among different breast cancer risk groups stratified based on BRCA 1/2 mutation status and lifetime risks. We use propensity score matching to adjust for potential confounders. We performed a quantitative BPE analysis on the 3D volume of the breast and fibroglandular tissue based on the enhancement maps and principal component analysis. The results showed a significant difference in BPE among different risk groups, indicating that BPE may improve breast cancer risk stratification.

Catherine J. Moran¹, Matthew J. Middione¹, Valentina Mazzoli¹, Jessica McKay-Nault¹, Arnaud Guidon², Uzma Waheed¹, Eric L. Rosen¹, Steven P. Poplack¹, Jarrett Rosenberg¹, Daniel B Ennis¹, Brian A. Hargreaves¹, and Bruce L. Daniel^1
1Radiology, Stanford University, Stanford, CA, United States, ²General Electric Healthcare, Botson, MA, United States

Diffusion-Weighted Imaging (DWI) in the supine position may provide a non-invasive, comfortable, and efficient MRI for breast cancer screening. The strong performance of multi-shot DWI in prone breast MRI has been established. However, supine breast MRI has increased motion, specific B0-inhomogeneity, and cardiac artifacts, all of which may affect multi-shot DWI. This work investigates supine multi-shot DWI of the breast with a flexible array coil. High image quality is achieved and the effects of number of shots and respiratory-gating are delineated. B0-inhomogeneity and ADCs in the supine position are reported including the potential effect of cardiac artifact on ADC measurement.

Esra Abaci Turk^1,2, Jeffrey N. Stout¹, Borjan Gagoski^1,2, Mary Katherine Manhard³, Elfar Adalsteinsson^4,5,6, Polina Golland^4,7, Drucilla J. Roberts⁸, William H. Barth Jr⁹, and P. Ellen Grant^1,2
1Fetal‐Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, ⁴Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁵Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁶Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁷Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, United States, ⁸Department of Pathology, Massachusetts General Hospital, Boston, MA, United States, ⁹Maternal-Fetal Medicine, Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, United States

Maternal-placental perfusion can be temporarily compromised by Braxton Hicks uterine contractions. The effect of Braxton Hicks contractions on placental function has not been well characterized or understood. In this study, we investigated the effect of Braxton Hicks contractions on placental T2* values across gestation together with the outcome measures. We observed positive correlation between the change in T2* during contraction, gestational age at delivery, and fetal birth weight. Additionally we observed differences in the placental T2* response in the regions closer to the maternal surface compared to regions closer to the fetal surface.

Aritrick Chatterjee^1,2, Teodora Szasz³, Milson Munakami³, Ibrahim Karademir¹, Mohamed Shaif Yusufishaq¹, Spencer Martens¹, Christina Wheeler⁴, Stephen Thomas¹, Gregory S Karczmar^1,2, and Aytekin Oto^1,2
1Department of Radiology, University of Chicago, Chicago, IL, United States, ²Sanford J. Grossman Center of Excellence in Prostate Imaging and Image Guided Therapy, Chicago, IL, United States, ³Research Computing Center, University of Chicago, Chicago, IL, United States, ⁴C. Wheeler Studios, Chicago, IL, United States

We created an interactive application Learn Radiology with multi-parametric MRI - whole mount histology correlation for enhanced prostate MRI training of radiologists and validated whether the use of a newly created learning application can enhance prostate MRI training of radiologists using an observer study. Sensitivity (R1: 54%→64%, R2: 44%→59%, R3: 62%→72%), PPV (R1: 68%→76%, R2: 52%→79%, R3: 48%→65%) and confidence score (R1: 4.0±1.0→4.3±0.8, R2: 3.1±0.8→4.0±1.1, R3: 2.8±1.2→4.1±1.1, p<0.05) for prostate cancer diagnosis using mpMRI improved for all three radiologists along with inter-observer agreement (α 0.78→0.85) after being exposed to our developed teaching app.

Philip Meng-en Lee¹, Hsin-Yu Chen¹, Jeremy W Gordon¹, Zhen J Wang¹, Robert A Bok¹, Kiersten Cheung¹, Francesca De Las Alas¹, Heather Daniel¹, Peder EZ Larson¹, Cornelius von Morze², Daniel B Vigneron¹, and Michael A Ohliger^1
1Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Radiology, Washington University in St. Louis, St. Louis, MO, United States

Whole-abdomen imaging with hyperpolarized  ¹³C is challenging due to B₀  and B₁ inhomogeneities, respiratory motion, and broad spatial coverage. There is also little baseline data about healthy metabolism in abdominal organs. We develop and describe a reliable imaging method to overcome these challenges, enabling metabolic imaging of the entire abdomen in a series of healthy volunteers. We establish normal values for conversion of HP [1-¹³C]pyruvate to lactate and alanine in key organs such as the liver, kidneys, pancreas, and spleen. Methods established here set a firm foundation for investigating a broad spectrum of metabolic and neoplastic abnormalities in the liver.

Esra Abaci Turk^1,2, Filiz Yetisir¹, Cindy Zhou¹, Jeffrey N. Stout¹, Judy A. Estroff^3,4, Carol Barnewolt^3,4, Elfar Adalsteinsson^5,6,7, P. Ellen Grant^1,2, and Lawrence L. Wald^2,6,8
1Fetal‐Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Department of Radiology, Boston Children’s Hospital, Boston, MA, United States, ⁴Maternal Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States, ⁵Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁶Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁷Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁸Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States

Despite the clinical and research potential of fetal MRI, there is no consensus on MRI safety in the 1st and early 2nd trimesters. Prior simulation studies at early gestational ages (GA) used only a single or unrealistic pregnant body models. To address this gap, we built 2 realistic uterine models for the early 2nd trimester and placed them into 3 existing pregnant body models at a later GA to investigate differences in RF exposure. Lower pSAR10g in both the fetus and amniotic fluid was observed in the early 2nd trimester models compared to later GA models.