Image-Guided Procedures, Robotic Interventions, and Modeling

Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomy

[+] Author Affiliations
Geert J. S. Litjens, Henkjan J. Huisman, Joyce G. R. Bomers

Radboud University Medical Center, Department of Radiology, Nijmegen 6525GA, The Netherlands

Robin M. Elliott, Satish Viswanath, Anant Madabhushi

Case Western Reserve University, Department of Biomedical Engineering, Cleveland, Ohio 44106, United States

Natalie Nc. Shih, Michael D. Feldman

University of Pennsylvania, Department of Pathology and Laboratory Medicine, Philadelphia, Pennsylvania 19104, United States

Jurgen J. Fütterer

Radboud University Medical Center, Department of Radiology, Nijmegen 6525GA, The Netherlands

University of Twente, Institute for Biomedical Technology and Technical Medicine, Enschede 7522NB, The Netherlands

J. Med. Imag. 1(3), 035001 (Oct 27, 2014). doi:10.1117/1.JMI.1.3.035001
History: Received March 31, 2014; Revised August 13, 2014; Accepted September 23, 2014
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Abstract.  Laser interstitial thermotherapy (LITT) is a relatively new focal therapy technique for the ablation of localized prostate cancer. In this study, for the first time, we are integrating ex vivo pathology and magnetic resonance imaging (MRI) to assess the imaging characteristics of prostate cancer and treatment changes following LITT. Via a unique clinical trial, which gave us the availability of ex vivo histology and pre- and post-LITT MRIs, (1) we investigated the imaging characteristics of treatment effects and residual disease, and (2) evaluated treatment-induced feature changes in the ablated area relative to the residual disease. First, a pathologist annotated the ablated area and the residual disease on the ex vivo histology. Subsequently, we transferred the annotations to the post-LITT MRI using a semi-automatic elastic registration. The pre- and post-LITT MRIs were registered and features were extracted. A scoring metric based on the change in median pre- and post-LITT feature values was introduced, which allowed us to identify the most treatment responsive features. Our results show that (1) image characteristics for treatment effects and residual disease are different, and (2) the change of feature values between pre- and post-LITT MRIs can be a quantitative biomarker for treatment response. Finally, using feature change improved discrimination between the residual disease and treatment effects.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Geert J. S. Litjens ; Henkjan J. Huisman ; Robin M. Elliott ; Natalie Nc. Shih ; Michael D. Feldman, et al.
"Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomy", J. Med. Imag. 1(3), 035001 (Oct 27, 2014). ; http://dx.doi.org/10.1117/1.JMI.1.3.035001


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