Computer-Assisted Quantitative Evaluation of Therapeutic Responses for Lymphoma Using Serial PET/CT Imaging
Received 2 September 2009; accepted 27 October 2009. published online 11 January 2010.
Rationale and Objectives
Molecular imaging modalities such as positron emission tomography (PET)/computed tomography (CT) have emerged as an essential diagnostic tool for monitoring treatment response in lymphoma patients. However, quantitative assessment of treatment outcomes from serial scans is often difficult, laborious, and time consuming. Automatic quantization of longitudinal PET/CT scans provides more efficient and comprehensive quantitative evaluation of cancer therapeutic responses. This study develops and validates a Longitudinal Image Navigation and Analysis (LINA) system for this quantitative imaging application.
Materials and Methods
LINA is designed to automatically construct longitudinal correspondence along serial images of individual patients for changes in tumor volume and metabolic activity via regions of interest (ROI) segmented from a given time point image and propagated into the space of all follow-up PET/CT images. We applied LINA retrospectively to nine lymphoma patients enrolled in an immunotherapy clinical trial conducted at the Center for Cell and Gene Therapy, Baylor College of Medicine. This methodology was compared to the readout by a diagnostic radiologist, who manually measured the ROI metabolic activity as defined by the maximal standardized uptake value (SUVmax).
Results
Quantitative results showed that the measured SUVs obtained from automatic mapping are as accurate as semiautomatic segmentation and consistent with clinical examination findings. The average of relative squared differences of SUVmax between automatic and semiautomatic segmentation was found to be 0.02.
Conclusions
These data support a role for LINA in facilitating quantitative analysis of serial PET/CT images to efficiently assess cancer treatment responses in a comprehensive and intuitive software platform.
aThe Center for Bioengineering and Informatics, The Methodist Hospital and The Methodist Hospital Research Institute, Weill Medical College of Cornell University, 6565 Fannin ST, B5-018, Houston, TX 77030
bDepartment of Radiology, The Methodist Hospital and The Methodist Hospital Research Institute, Weill Medical College of Cornell University, 6565 Fannin ST, B5-018, Houston, TX 77030
cDepartment of Pediatrics, Section of Hematology/Oncology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX
ABSTRACT