Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images

Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications

The current standard of Response Evaluation Criteria in Solid Tumors (RECIST)-based tumor response evaluation is limited in its ability to accurately monitor treatment response. Radiomics, an approach involving computerized extraction of several quantitative imaging features, has shown promise in predicting as well as monitoring response to therapy. In this article, we provide a brief overview of radiomic approaches and the various analytical methods and techniques, specifically in the context of predicting and monitoring treatment response for non-small cell lung cancer (NSCLC). We briefly summarize some of the various types of radiomic features, including tumor shape and textural patterns, both within the tumor and within the adjacent tumor microenvironment. Additionally, we also discuss work in delta-radiomics or change in radiomic features (e.g., texture within the nodule) across longitudinally interspersed images in time for monitoring changes in therapy. We discuss the utility of these approaches for NSCLC, specifically the role of radiomics as a prognostic marker for treatment effectiveness and early therapy response, including chemoradiation, immunotherapy, and trimodality therapy.

Evaluation of localized region-based segmentation algorithms for CT-based delineation of organs at risk in radiotherapy

Background and purpose

In radiation therapy, defining the precise borders of cancerous tissues and adjacent normal organs has a significant effect on the therapy outcome. Deformable models offer a unique and robust approach to medical image segmentation. The objective of this study was to investigate the reliability of segmenting organs-at-risk (OARs) using three well-known local region-based level-set techniques.

Methods and materials

A total of 1340 non-enhanced and enhanced planning computed tomography (CT) slices of eight OARs (the bladder, rectum, kidney, clavicle, humeral head, femoral head, spinal cord, and lung) were segmented by using local region-based active contour, local Chan-Vese, and local Gaussian distribution models. Quantitative metrics, namely Hausdorff Distance (HD), Mean Absolute Distance (MAD), Dice coefficient (DC), Percentage Volume Difference (PVD) and Absolute Volumetric Difference (AVD), were adopted to measure the correspondence between detected contours and the manual references drawn by experts.

Results

The results showed the feasibility of using local region-based active contour methods for defining six of the OARs (the bladder, kidney, clavicle, humeral head, spinal cord, and lung) when adequate intensity information is available. While the most accurate results were achieved for lung (DC = 0.94) and humeral head (DC = 0.92), a poor level of agreement (DC < 0.7) was obtained for both rectum and femur.

Conclusion

Incorporating local statistical information in level set methods yields to satisfactory results of OARs delineation when adequate intensity information exists between the organs. However, the complexity of adjacent organs and the lack of distinct boundaries would result in a considerable segmentation error.

Radiotherapy dose-distribution to the perirectal fat space (PRS) is related to gastrointestinal control-related complications

Traditionally rectal symptoms following pelvic/prostate radiotherapy are correlated to the dosimetry of the anorectum or a substructure of this. It has been suggested that the perirectal fat space (PRS) surrounding the rectum may also be relevant. This study considers the delineation and dosimetry of the PRS related to both rectal bleeding and control-related toxicity. Initially, a case-control cohort of 100 patients from the RADAR study were chosen based on presence/absence of rectal control-related toxicity. Automated contouring was developed to delineate the PRS. 79 of the 100 auto-segmentations were considered successful. Balanced case-control cohorts were defined from these cases. Atlas of Complication Incidence (ACI) were generated to relate the DVH of the PRS with specific rectal symptoms; rectal bleeding and control-related symptoms (LENT/SOM). ACI demonstrated that control-related symptoms were related to the dose distribution to the PRS which was confirmed with Wilcoxon rank sum test (p < 0.05). To the authors knowledge this is the first study implicating the dose distribution to the PRS to the incidence of control-related symptoms of rectal toxicity.