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Defining internal target volume using positron emission tomography for radiation therapy planning of moving lung tumors.

ABSTRACT: Substantial disagreement exists over appropriate PET segmentation techniques for non-small cell lung cancer. Currently, no segmentation algorithm explicitly considers tumor motion in determining tumor borders. We developed an automatic PET segmentation model as a function of target volume, motion extent, and source-to-background ratio (the VMSBR model). The purpose of this work was to apply the VMSBR model and six other segmentation algorithms to a sample of lung tumors. PET and 4D CT were performed in the same imaging session for 23 patients (24 tumors) for radiation therapy planning. Internal target volumes (ITVs) were autosegmented on maximum intensity projection (MIP) of cine CT. ITVs were delineated on PET using the following methods: 15%, 35%, and 42% of maximum activity concentration, standardized uptake value (SUV) of 2.5 g/mL, 15% of mean activity concentration plus background, a linear function of mean SUV, and the VMSBR model. Predicted threshold values from each method were compared to measured optimal threshold values, and resulting volume magnitudes were compared to cine-CT-derived ITV. Correlation between predicted and measured threshold values ranged from slopes of 0.29 for the simplest single-threshold techniques to 0.90 for the VMSBR technique. R2 values ranged from 0.07 for the simplest single-threshold techniques to 0.86 for the VMSBR technique. The VMSBR segmentation technique that included volume, motion, and source-to-background ratio, produced accurate ITVs in patients when compared with cine-CT-derived ITV.

SUBMITTER: Riegel AC

PROVIDER: S-EPMC5711243 | biostudies-other | 2014 Jan

REPOSITORIES: biostudies-other

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Defining internal target volume using positron emission tomography for radiation therapy planning of moving lung tumors.

Riegel Adam C AC Bucci M Kara MK Mawlawi Osama R OR Ahmad Moiz M Luo Dershan D Chandler Adam A Pan Tinsu T

Journal of applied clinical medical physics 20140106 1

Substantial disagreement exists over appropriate PET segmentation techniques for non-small cell lung cancer. Currently, no segmentation algorithm explicitly considers tumor motion in determining tumor borders. We developed an automatic PET segmentation model as a function of target volume, motion extent, and source-to-background ratio (the VMSBR model). The purpose of this work was to apply the VMSBR model and six other segmentation algorithms to a sample of lung tumors. PET and 4D CT were perfo ...[more]

PMID: 24423860

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Project description:PurposeTo investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone- and positron emission tomography (PET)-CT-based delineations.Methods and materialsSeven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT ("clinical standard"), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed.ResultsComputed tomography- and MRI-based tumor volumes normalized relative to PET-CT-based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10-5 to 3.82 × 10-9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI).ConclusionsAlthough MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.

Project description:Fluorine-18-fluoro-2-deoxy-D-glucose (FDG) is widely used as positron-emission-tomography (PET) radiotracer for the detection and staging of human cancer. Tumor uptake of FDG varies substantially between different cancer types and between patients with the same tumor type. The molecular basis for this heterogeneity is unknown. Using cancer cell lines and primary human tumors of distinct histologic origins, we here show that increased FDG uptake is universally associated with coordinate upregulation of genes within the glycolysis, pentose-phosphate, and other related metabolic pathways. In primary human breast cancers, this FDG signature shows significant overlap with established breast cancer signatures for the “basal-like” disease subtype and “poor prognosis”. FDG high breast cancer showed significantly more gene copy number alterations genome wide than FDG low cancers. About 50 % of primary breast cancers with high FDG uptake and FDG gene expression signature show DNA copy gain encompassing the c-myc gene locus and express gene sets regulated by the transcription factor MYC. Our data shows that FDG-PET marks a distinct subset of “basal-like” human breast cancer which is characterized by MYC and prognostically unfavorable gene expression signatures, suggesting that FDG-PET imaging may be useful to risk-stratify patients with locally advanced breast cancer. Our general strategy to identify molecular determinants of FDG-retention through a genome-wide approach consisted of FDG uptake measurements in cancer cell lines and primary human tumors, the selection of samples with particularly high versus low FDG-retention, and subsequent pathway-based analysis of RNA expression data collected from these samples. Cell line RNA was extracted from a 10 cm plate seeded simultaneously and at the same density as the wells for FDG-uptake assays. For primary human tumor samples, RNA was extracted from macrodissected frozen tumor tissue. All cell line RNA samples and the astrocytoma RNA aliquots were hybridized to Affymetrix U133 Plus 2.0 arrays. All primary breast cancer RNA samples were hybridized to Affymetrix U133A arrays.

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Dataset Information

Defining internal target volume using positron emission tomography for radiation therapy planning of moving lung tumors.

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Defining internal target volume using positron emission tomography for radiation therapy planning of moving lung tumors.

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