Pathology-validated PET image data sets and their role in PET segmentation

Abstract

Positron emission tomography (PET)/computed tomography has recently been finding broader application for the diagnosis, treatment and therapy assessment of malignant disease. Accurate definition of the tumor border is extremely important for the success of localized tumor therapies. PET promises to provide the metabolically active tumor volume and, at present, it is used for target definition in a variety of tumors. This process is, however, subject to uncertainties of different origin. Resolving these uncertainties is challenging, since validating PET images and segmentation contours against tumor pathology is experimentally difficult. In addition to accurate lesion contouring, this challenges validation of PET tracers and investigations of tumor functional heterogeneity. In this paper, we briefly review the present studies providing PET image data sets with pathology validation. We focus on the specimen handling techniques aimed at achieving higher geometrical accuracy of the pathology-derived ''ground truth''. We also summarize the main findings obtained for the PET segmentation techniques which have been tested with the help of these data sets. Finally, we provide a critical summary of the current state of the art in pathological validation of PET images and briefly discuss future possibilities in this direction.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

“…While these errors can potentially limit the validity of the comparison, histopathological validation is an important part of thorough PET‐AS evaluation. At present, there are several datasets in which effort was made to minimize these errors . Examples are: the lung tumor dataset from the MAASTRO (Maastricht Radiation Oncology) team with pathology‐validated maximum diameters, the tumor datasets used in the study from the Jefferson Medical College (max.…”

“…Despite the challenges with respect to the accuracy of the reference contours, these pathology‐validated images provide an important test for PET‐AS methods. This justifies the need for further improvement of the current experimental approaches, as well as development of new techniques to improve the accuracy of histopathological validation …”

Feasibility of In Situ, High-Resolution Correlation of Tracer Uptake with Histopathology by Quantitative Autoradiography of Biopsy Specimens Obtained Under 18F-FDG PET/CT Guidance

“…Accurate registration between pathology and PET is, however, often prevented by deformation of the excised specimens and by the poor spatial resolution of PET. One of the recent investigations based on laryngeal lesion excision (20) reports a 3.3-mm registration inaccuracy between the specimen and PET “in the cartilage skeleton.” This estimate does not account for possible changes in tumor metabolism over the time between the PET scan and surgery, which may extend to more than 2 wk (7,20). …”

“…PET–histopathology correlations have been investigated previously for several tumor types as reviewed elsewhere (7). Most of these studies were performed to evaluate PET image segmentation for radiation therapy, where accurate delineation of the tumor boundary is essential.…”

Primary lung tumor segmentation from PET–CT volumes with spatial–topological constraint

“…Accurate segmentation and delineation of lung tumors are required for radiation therapy and surgical planning. For radiation therapy, the aim was to deliver, with high precision, the appropriate dose to the most metabolically active region of the tumor volume [3] while minimizing the radiation dose to surrounding tissue.…”