A Modality-Adaptive Method for Segmenting Brain Tumors and Organs-at-Risk in Radiation Therapy Planning

In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation with a new spatial regularization model of tumor shape using convolutional restricted Boltzmann machines. We demonstrate experimentally that the method is able to adapt to image acquisitions that differ substantially from any available training data, ensuring its applicability across treatment sites; that its tumor segmentation accuracy is comparable to that of the current state of the art; and that it captures most organs-at-risk sufficiently well for radiation therapy planning purposes. The proposed method may be a valuable step towards automating the delineation of brain tumors and organs-at-risk in glioblastoma patients undergoing radiation therapy.Comment: corrected one referenc

A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning

In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation with a new spatial regularization model of tumor shape using convolutional restricted Boltzmann machines. We demonstrate experimentally that the method is able to adapt to image acquisitions that differ substantially from any available training data, ensuring its applicability across treatment sites; that its tumor segmentation accuracy is comparable to that of the current state of the art; and that it captures most organs-at-risk sufficiently well for radiation therapy planning purposes. The proposed method may be a valuable step towards automating the delineation of brain tumors and organs-at-risk in glioblastoma patients undergoing radiation therapy

Impact of [18F]-fluoro-ethyl-tyrosine PET imaging on target definition for radiation therapy of high-grade glioma

Background.We sought to assess the impact of amino-acid 18F-fluoro-ethyl-tyrosine (FET) positron emission tomography (PET) on the volumetric target definition for radiation therapy of high-grade glioma versus the current standard using MRI alone. Specifically, we investigated the influence of tumor grade, MR-defined tumor volume, and the extent of surgical resection on PET positivity. Methods. Fifty-four consecutive high-grade glioma patients (World Health Organization grades III–IV) with confirmed histology were scanned using FET-PET/CT and T1 and T2/fluid attenuated inversion recovery MRI. Gross tumor volume and clinical target volumes (CTVs) were defined in a blinded fashion based on MRI and subsequently PET, and volumetric analysis was performed. The extent of the surgical resection was reviewed using postoperative MRI. Results. Overall, for90 % of the patients, the PET-positive volumes were encompassed by T1 MRI with contrast-defined tumor plus a 20-mm margin. The tumor volume defined by PET was larger for glioma grade IV (P,.001) and smaller for patients with more ex-tensive surgical resection (P .004). The margin required to be added to the MRI-defined tumor in order to fully encompass the FET-PET positive volume tended to be larger for grade IV tumors (P .018). Conclusion. With an unchanged CTV margin and by including FET-PET for gross tumor volume definition, the CTV will increase mod-erately for most patients, and quite substantially for a minority of patients. Patients with grade IV gliomawere found to be the primar