BMC has one of the most-diverse patient populations (Fig. 1). 59% of its patients are from under-served populations and 31% of the patients do not speak English as a primary language. 32% of its patients are Black/African American (21% of these patients are of Haitian origin); 18% Hispanics, 5% are Asians. Furthermore, because the large portion of under-served patients, the spectrum of cancer disease (cancer subtypes, grade, stage) is broader and is more advanced at first presentation compared to the general population. Our researchers have therefore access to data of the most diverse patient population and broadest spectrum of disease in the nation.

Fig. 1. Distribution of Race and Ethnicity in BMC’s Breast Cancer Screening Patient Population.

The aim of our BMC cancer imaging program (CIP) is to improve clinical care and facilitate image guided precision medicine for our patients suffering from cancer. Two main foci of our multidisciplinary research endeavors are breast and prostate cancer imaging. Our research has focused on developing new imaging protocols and on correlating prostate and breast cancer imaging phenotypes and MR/US imaging classifiers with histology, immunohistochemistry, and gene expression profiles as well as proteomics. We recognize the imperative need for correlating imaging phenotypes with tumor genotypes in order to advance knowledge regarding a broad range of breast and prostate diseases, as well as their early diagnosis, progression/behavior and treatment, by developing new (imaging) biomarkers for a broad range of cancers and their subtypes.
Another major research focus of CIP is the design and development of biopsy and treatment tools, i.e. biopsy markers (biopsy clips; Coulter award 2011/2012; US patent US20150297316), and treatment planning phantoms and atlases in collaboration with biomedical engineers and image post-processors at Boston University and other universities.
CIP also collaborates with colleagues for Surgery, Oncology, Pathology, Biochemistry and from other specialties with the overarching goal to facilitate interdisciplinary research for the promotion of image guided precision medicine for our cancer patients at BMC.

Selected Recent Publications of CIP:

  1. Stereotactic core needle breast biopsy marker migration: An analysis of factors contributing to immediate marker migration. Jain A, Khalid M, Qureshi MM, Georgian-Smith D, Kaplan JA, Buch K, Grinstaff MW, Hirsch AE, Hines NL, Anderson SW, Gallagher KM, Bates DDB, Bloch BN. Eur Radiol. 2017 Nov;27(11):4797-4803. doi: 10.1007/s00330-017-4851-7. Epub 2017 May 19.
  2. Dosimetric impacts of endorectal balloon in CyberKnife stereotactic body radiation therapy (SBRT) for early-stage prostate cancer. Xiang HF, Lu HM, Efstathiou JA, Zietman AL, Armas R, Harris K, Bloch BN, Qureshi MM, Keohan S, Hirsch AE. J Appl Clin Med Phys. 2017 May;18(3):37-43. doi: 10.1002/acm2.12063. Epub 2017 Apr 13.
  3. A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores. Wan T, Bloch BN, Plecha D, Thompson CL, Gilmore H, Jaffe C, Harris L, Madabhushi A. Sci Rep. 2016 Feb 18;6:21394. doi: 10.1038/srep21394.
  4. Polymer film-nanoparticle composites as new multimodality, non-migrating breast biopsy markers. Kaplan JA, Grinstaff MW, Bloch BN. Eur Radiol. 2016 Mar;26(3):866-73. doi: 10.1007/s00330-015-3852-7. Epub 2015 Jun 10.
  5. Improved dosimetry in prostate brachytherapy using high resolution contrast enhanced magnetic resonance imaging: a feasibility study. Buch K, Morancy T, Kaplan I, Qureshi MM, Hirsch AE, Rofksy NM, Holupka E, Oismueller R, Hawliczek R, Helbich TH, Bloch BN. J Contemp Brachytherapy. 2015 Jan;6(4):337-43. doi: 10.5114/jcb.2014.46555. Epub 2014 Oct 28.
  6. Multiattribute probabilistic prostate elastic registration (MAPPER): application to fusion of ultrasound and magnetic resonance imaging. Sparks R, Bloch BN, Feleppa E, Barratt D, Moses D, Ponsky L, Madabhushi A. Med Phys. 2015 Mar;42(3):1153-63. doi: 10.1118/1.4905104.
  7. Surveillance of probably benign (BI-RADS 3) lesions in mammography: what is the right follow-up protocol? Buch KA, Qureshi MM, Carpentier B, Cunningham DA, Stone M, Jaffe C, Quinn M, Gonzalez C, LaVoye J, Hines N, Bloch BN. Breast J. 2015 Mar-Apr;21(2):168-74. doi: 10.1111/tbj.12387. Epub 2015 Feb 9.
  8. A Learning Based Fiducial-driven Registration Scheme for Evaluating Laser Ablation Changes in Neurological Disorders. Wan T, Bloch BN, Danish S, Madabhushi A. Neurocomputing. 2014 Nov 20;144:24-37.
  9. Prostatome: a combined anatomical and disease based MRI atlas of the prostate. Rusu M, Bloch BN, Jaffe CC, Genega EM, Lenkinski RE, Rofsky NM, Feleppa E, Madabhushi A. Med Phys. 2014 Jul;41(7):072301. doi: 10.1118/1.4881515.
  10. Novel PCA-VIP scheme for ranking MRI protocols and identifying computer-extracted MRI measurements associated with central gland and peripheral zone prostate tumors. Ginsburg SB, Viswanath SE, Bloch BN, Rofsky NM, Genega EM, Lenkinski RE, Madabhushi A. J Magn Reson Imaging. 2015 May;41(5):1383-93. doi: 10.1002/jmri.24676. Epub 2014 Jun 18.
  11. Statistical 3D Prostate Imaging Atlas Construction via Anatomically Constrained Registration. Rusu M, Bloch BN, Jaffe CC, Rofsky NM, Genega EM, Feleppa E, Lenkinski RE, Madabhushi A. Proc SPIE Int Soc Opt Eng. 2013 Mar 13;8669. doi: 10.1117/12.2006941.
  12. Fully Automated Prostate Magnetic Resonance Imaging and Transrectal Ultrasound Fusion via a Probabilistic Registration Metric. Sparks R, Bloch BN, Feleppa E, Barratt D, Madabhushi A. Proc SPIE Int Soc Opt Eng. 2013 Mar 8;8671. doi: 10.1117/12.2007610.
  13. Diagnosis of relevant prostate cancer using supplementary cores from magnetic resonance imaging-prompted areas following multiple failed biopsies. Costa DN, Bloch BN, Yao DF, Sanda MG, Ngo L, Genega EM, Pedrosa I, DeWolf WC, Rofsky NM. Magn Reson Imaging. 2013 Jul;31(6):947-52. doi: 10.1016/j.mri.2013.02.007. Epub 2013 Apr 18.
  14. Accuracy of endorectal magnetic resonance/transrectal ultrasound fusion for detection of prostate cancer during brachytherapy. Bubley GJ, Bloch BN, Vazquez C, Genega E, Holupka E, Rofsky N, Kaplan I. Urology. 2013 Jun;81(6):1284-9. doi: 10.1016/j.urology.2012.12.051. Epub 2013 Mar
  15. Prediction of prostate cancer extracapsular extension with high spatial resolution dynamic contrast-enhanced 3-T MRI. Bloch BN, Genega EM, Costa DN, Pedrosa I, Smith MP, Kressel HY, Ngo L, Sanda MG, Dewolf WC, Rofsky NM. Eur Radiol. 2012 Oct;22(10):2201-10. doi: 10.1007/s00330-012-2475-5. Epub 2012 Jun 3.
  16. Automated computer-derived prostate volumes from MR imaging data: comparison with radiologist-derived MR imaging and pathologic specimen volumes. Bulman JC, Toth R, Patel AD, Bloch BN, McMahon CJ, Ngo L, Madabhushi A, Rofsky NM. Radiology. 2012 Jan;262(1):144-51. doi: 10.1148/radiol.11110266.
  17. Elastic registration of multimodal prostate MRI and histology via multiattribute combined mutual information. Chappelow J, Bloch BN, Rofsky N, Genega E, Lenkinski R, DeWolf W, Madabhushi A. Med Phys. 2011 Apr;38(4):2005-2018.
  18. Accurate prostate volume estimation using multifeature active shape models on T2-weighted MRI. Toth R, Bloch BN, Genega EM, Rofsky NM, Lenkinski RE, Rosen MA, Kalyanpur A, Pungavkar S, Madabhushi A. Acad Radiol. 2011 Jun;18(6):745-54. doi: 10.1016/j.acra.2011.01.016.
  19. Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE): Detecting Prostate Cancer on Multi-Parametric MRI. Viswanath S, Bloch BN, Chappelow J, Patel P, Rofsky N, Lenkinski R, Genega E, Madabhushi A. Proc SPIE Int Soc Opt Eng. 2011 Mar 4;7963:79630U.
  20. Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer. Xiao G, Bloch BN, Chappelow J, Genega EM, Rofsky NM, Lenkinski RE, Tomaszewski J, Feldman MD, Rosen M, Madabhushi A. Comput Med Imaging Graph. 2011 Oct-Dec;35(7-8):568-78. doi: 10.1016/j.compmedimag.2010.12.003. Epub 2011 Jan 21.