Sungheon Kim

Alina Tudorica¹, Karen Y Oh¹, Stephen Y-C Chui¹, Nicole Roy¹, Megan L Troxell¹, Arpana Naik¹, Kathleen A Kemmer¹, Yiyi Chen¹, Megan L Holtorf¹, Aneela Afzal¹, Charles S Springer¹, Xin Li¹, and Wei Huang^1
1Oregon Health & Science University, Portland, OR, United States

21 women with locally advanced breast cancer underwent DCE-MRI scans before, after the first cycle of, at the midpoint of, and after completion of neoadjuvant chemotherapy. Quantitative DCE-MRI parameters of Ktrans, kep, and Tau_i were found to be superior to tumor size measurement for early prediction of pathologic response. DCE-MRI parameters were as good as tumor size, if not better, in evaluation of residual disease burden after the therapy.

Thian Ng^1,2, Bo Zhang³, Dennis Cheong⁴, Limiao Jiang⁵, Bingwen Zheng⁶, and Soo Chin Lee^7
1National University of Singapore, S'pore, Singapore, Singapore, ²CIRC/A*STAR, S'pore, Singapore, Singapore, ³CIRC/A*STAR, Singapore, Singapore,⁴CIRC/A*STAR, S'pore, Singapore, ⁵NUS/CIRC, S'pore, Singapore, ⁶NUS/NERI, S'pore, Singapore, ⁷NUS, S'pore, Singapore

This is a clinical trial study on advanced breast carcinoma using low-dose Sunitinib to 'Normalization' the microvascular environment to enhance the delivery of anti-cancer drugs (AC)to the cancer cells. In vivo DCE-MRI and DTI are used to monitor the perfusion,and 4 other vessel parameters changes prior to the main course of chemotherapy to reveal the most sensitive biomarker(s)with respect to tumor mass by MRI. Other histological parameters are measured.

Wen Li¹, Wei-Ching Lo¹, Ella F Jones¹, David C Newitt¹, John Kornak², Lisa J Wilmes¹, and Nola M Hylton^1
1Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, ²Epidemiology and Biostatistics, UCSF, San Francisco, CA, United States

This abstract presents our retrospective study of parameter optimization for tumor volume measurement in DCE-MRI to predict response to neoadjuvant chemotherapy by breast cancer subtype in clinical trials. Pilot study consisting of 64 patients was used to test the proposed optimization strategy. Two standard clinical outcomes were used to assess the prediction. Results showed that different profile was observed for different breast cancer subtype when the prediction was evaluated on a matrix of parameter settings and the predictive performance of tumor volume measured in DCE-MRI can be improved with parameter optimization.

Guillaume Thibault¹, Alina Tudorica¹, Aneela Afzal¹, Stephen Y-C Chui¹, Arpana Naik¹, Megan L Troxell¹, Kathleen A Kemmer¹, Karen Y Oh¹, Nicole Roy¹, Megan L Holtorf¹, Wei Huang¹, and Xubo Song^1
1Oregon Health & Science University, Portland, OR, United States

Twenty-eight women with locally advanced breast cancer who underwent neoadjuvant chemotherapy (NACT) consented to research DCE-MRI studies before, during, and after NACT. The DCE-MRI data were subjected to both Standard and Shutter-Speed model (SM and SSM) pharmacokinetic (PK) analyses to generate pixel-by-pixel parametric maps. Three texture analysis methods were employed to extract triple features from the maps and their changes after one NACT cycle were correlated with residual cancer burden (RCB) measured by pathology analysis of post-NACT resection specimens. Texture feature changes in several PK parametric maps provided good early prediction of therapy response, with the SSM maps the most frequently used in feature extraction with good early prediction of response.

Martin D Pickles¹, Peter Gibbs¹, Martin Lowry¹, and Lindsay W Turnbull^1
1Centre for Magnetic Resonance Investigations, Hull York Medical School at University of Hull, Hull, East Yorkshire, United Kingdom

The aim of this work was to develop a classification model to predict pCR, in patients undergoing neoadjuvant chemotherapy. To generate empirical vascular parameters dynamic data was interrogated in a pixel-by-pixel manner. Following pathological analysis Synthetic Minority Over-sampling TEchnique (SMOTE) was utilised to balance the pCR and non-pCR classes and a classification model was developed. High predictive accuracy was obtained from only 4 DCE-MRI parameters. This study suggests that prediction of pathological complete response, secondary to NAC treatment, can be made even prior to the initiation of chemotherapy from DCE-MRI parameters with a 86% accuracy.

Subashini Srinivasan¹, Brian A Hargreaves¹, and Bruce L Daniel^1
1Department of Radiology, Stanford University, Palo Alto, California, United States

Quantitative pharmacokinetic mapping of breast DCE MRI is often performed using a Tofts model and requires the measurement of arterial input function. The measured or modeled AIF in a distant artery is assumed to be identical to the tumor tissue’s input. However, angiogenesis can delay and disperse the AIF resulting in poor model fitting and errors in pharmacokinetic mapping. In this study, the fitting of pharmacokinetic parameters using two different dispersion models was compared to use of a Tofts model without dispersion in 10 patients. The goodness-of-fit was considerably improved using dispersion models and may improve the accuracy of tumor characterization and treatment response.

Ben R Dickie¹, Lucy E Kershaw¹, Stephanie Withey², Bernadette M Carrington³, Catharine M West⁴, and Chris J Rose^5
1Medical Physics and Engineering, Christie NHS Foundation Trust, Manchester, United Kingdom, ²RRPPS, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom, ³Department of Radiology, Christie NHS Foundation Trust, Manchester, United Kingdom, ⁴Institute of Cancer Sciences, University of Manchester, Manchester, United Kingdom, ⁵Centre for Imaging Sciences, University of Manchester, Manchester, United Kingdom

DCE-MRI studies of cervical cancer have reported that Tofts model-derived K^trans may predict outcome. Since K^trans depends on both microvascular perfusion and permeability, it is unclear whether one or both are important for predicting survival. We present what we believe to be the first prospective DCE-MRI study (n = 42) to employ the more specific two-compartment exchange model (2CXM) to separately measure perfusion (plasma flow) and permeability, and study their relationship to disease-free survival. High plasma flow (P = 0.022) and low FIGO stage (P = 0.020) were significant predictors of survival, but permeability was not (P = 0.63).

Sherif G Nour^1,2, Andrew David Nicholson³, Tracy E Powell^2,3, and Viraj Master^3
1Emory University, Atlanta, GA, United States, ²Interventional MRI Program, Emory University, GA, United States, ³Emory University, GA, United States

This investigation describes the technical aspects of using laser fibers to deliver ablative energy to renal tumors during interactive MRI guidance and reports patient tolerance, complication rates, long term efficacy of laser ablation of renal malignancies. The technique represents a considerable departure from the complex handling of cryo- and RFA probes within the MRI environment and is likely to facilitate future dissemination of MRI-guided renal ablation. The procedure is well tolerated with a high safety profile. Long-term follow up results for up to >32 months point to an efficacious ablative technique with no residual or recurrent neoplasms in our series.

Vidhya Kumar^1,2, Yves Boucher³, Diego Ferreira¹, Hao Liu³, Rakesh Jain³, and Alexander R Guimaraes^1,4
1Radiology, Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ²The Ohio State University, Columbus, OH, United States, ³Radiation Oncology/Steele Lab for Tumor Biology, Massachusetts General Hospital, Charlestown, MA, United States, ⁴Radiology, Oregon Health Sciences University, Portland, OR, United States

MRI using FDA approved magnetic nanoparticles allows a robust steady state technique that unlike intravital and confocal microscopy, is readily translatable to humans and scalable from mice to humans. The aim of this study was to develop and apply MRI based methods at interrogating tumor microvasculature in an established orthotopic pancreatic cancer model, and assess if angiotensin receptor blockade demonstrates quantificable changes in tumor microvasculature in addition to changes in drug delivery as measured by 18F-5fluorouracil.