Noninvasive Evaluation of Microscopic Tumor Extensions Using Standardized Uptake Value and Metabolic Tumor Volume in Non-Small-Cell Lung Cancer

Xue, Min; Sun, Xia; Mu, Dianbin; Xing, Ligang; Ma, Li; Zhang, Baijiang; Zhao, Shuqiang; Yang, Guoren; Kong, Feng-Ming; Yu, Jinming

doi:10.1016/j.ijrobp.2010.10.064

Cited by 36 publications

(34 citation statements)

References 17 publications

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“…Prognostic values of MTV and TLG were previously reported in NSCLC patients, mostly only in operable or with stage I-III patients [16][17][18]. To the best of our knowledge, this is the second report regarding prognostic value of MTV in stage IV NSCLC patients.…”

Section: Discussionmentioning

confidence: 64%

“…Recently, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been reported as additional diagnostic and prognostic imaging biomarkers for maximum SUV (SUVmax) [13][14][15]. MTV and TLG are valuable markers in the prediction of prognosis in NSCLC patients, mostly in operable or up to stage III patients [16][17][18]. Liao et al [16] reported that whole-body measurement of MTV successfully predicted survival in stage IV NSCLC.…”

Section: Introductionmentioning

confidence: 99%

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Metabolic Tumor Volume Measured by F-18 FDG PET/CT can Further Stratify the Prognosis of Patients with Stage IV Non-Small Cell Lung Cancer

Yoo

Kim

Chong

et al. 2012

Nucl Med Mol Imaging

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Purpose This study aimed to further stratify prognostic factors in patients with stage IV non-small cell lung cancer (NSCLC) by measuring their metabolic tumor volume (MTV) using F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). Materials and MethodsThe subjects of this retrospective study were 57 patients with stage IV NSCLC. MTV, total lesion glycolysis (TLG), and maximum standardized uptake value (SUVmax) were measured on F-18 FDG PET/CT in both the primary lung lesion as well as metastatic lesions in torso. Optimal cutoff values of PET parameters were measured by receiver operating characteristic (ROC) curve analysis. Kaplan-Meier survival curves were used for evaluation of progression-free survival (PFS). The univariate and multivariate Cox proportional hazards models were used to select the significant prognostic factors. Results Univariate analysis showed that both MTV and TLG of primary lung lesion (MTV-lung and TLG-lung) were significant factors for prediction of PFS (P<0.001, P00.038, respectively). Patients showing lower values of MTV-lung and TLG-lung than the cutoff values had significantly longer mean PFS than those with higher values. Hazard ratios (95 % confidence interval) of MTV-lung and

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Section: Discussionmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Metabolic Tumor Volume Measured by F-18 FDG PET/CT can Further Stratify the Prognosis of Patients with Stage IV Non-Small Cell Lung Cancer

Yoo

Kim

Chong

et al. 2012

Nucl Med Mol Imaging

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“…These studies have common steps that are discussed below by tumor location: specimen fixation (for all except one), registration of the specimen with the images, and deformation corrections for some of them (Table 2). Such are the PSPVs generated by Daisne et al [25], Caldas-Magalhaes et al [26], Stroom et al [27], Van Loon et al [28], Yu et al [29], Meng et al [30], Schaefer et al [31], Dahele et al [32], Wanet et al [33], Zhang et al [34], and Roels et al [35]. After this, we provide an overview of the volumetric studies.…”

Section: Available Data Setsmentioning

confidence: 93%

“…They reported a reduction to 82 ± 10 % of the original tumor volumes (range, 62-100 %) before and after fixation with formalin. Meng et al [30], in a follow-up study, fixed the specimens in formalin and subsequently sliced them to obtain wholemount, H&E-stained slides after which they examined the ME. They did not correct for shrinkage as a result of fixation with formalin even though they had measured this in their previous study [29] and point that it may affect ME max .…”

Section: Non-small-cell Lung Cancer (Nsclc)mentioning

confidence: 99%

“…They also found that GTV PET (automatically delineated using a 42 % threshold of the maximum SUV) as well as GTV CT accurately represent the Clinical Target Volume determined from pathology, CTV path , for patients with low risk of ME, but that both GTV CT and GTV PET underestimate CTV path for patients with high risk of ME, on average by 19.2 and 26.7 mm, respectively. Meng et al [30] determined the maximal ME from all islets for each patient without considering direction. They found that ME max was significantly correlated with SUV max and the metabolic tumor volume (MTV).…”

Section: Microscopic Tumor Extensionsmentioning

confidence: 99%

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

Kirov

Fanchon

2014

Clin Transl Imaging

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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.

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Exploring trade‐offs in treatment planning for brain tumor cases with a probabilistic definition of the clinical target volume

et al. 2022

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This study demonstrates how a novel probabilistic clinical target volume (CTV) concept-the clinical target distribution (CTD)-can be used to navigate the trade-off between target coverage and organ sparing with a semi-interactive treatment planning approach. Methods: Two probabilistic treatment planning methods are presented that use tumor probabilities to balance tumor control with organ-at-risk (OAR) sparing. The first method explores OAR dose reduction by systematically discarding x% of CTD voxels with an unfavorable dose-to-probability ratio from the minimum dose coverage objective. The second method sequentially expands the target volume from the GTV edge, calculating the CTD coverage versus OAR sparing trade-off after dosing each expansion. Each planning method leads to estimated levels of tumor control under specific statistical models of tumor infiltration: an independent tumor islets model and contiguous circumferential tumor growth model. The methods are illustrated by creating proton therapy treatment plans for two glioblastoma patients with the clinical goal of sparing the hippocampus and brainstem. For probabilistic plan evaluation, the concept of a dose-expected-volume histogram is introduced, which plots the dose to the expected tumor volume ⟨v⟩ considering tumor probabilities. Results: Both probabilistic planning approaches generate a library of treatment plans to interactively navigate the planning trade-offs. In the first probabilistic approach, a significant reduction of hippocampus dose could be achieved by excluding merely 1% of CTD voxels without compromising expected tumor control probability (TCP) or CTD coverage: the hippocampus D 2% dose reduces with 9.5 and 5.3 Gy for Patient 1 and 2, while the TCP loss remains below 1%. Moreover, discarding up to 10% of the CTD voxels does not significantly diminish the expected CTD dose, even though evaluation with a binary volume suggests poor CTD coverage. In the second probabilistic approach, the expected CTD D ⟨98%⟩ and TCP depend more strongly on the extent of the high-dose region: the target volume margin cannot be reduced by more than 2 mm if one aims at keeping the expected CTD D ⟨98%⟩ loss and TCP loss under 1 Gy and 2%, respectively. Therefore, there is less potential for improved OAR sparing without compromising TCP or expected CTD coverage. Conclusions: This study proposes and implements treatment planning strategies to explore trade-offs using tumor probabilities.

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Noninvasive Evaluation of Microscopic Tumor Extensions Using Standardized Uptake Value and Metabolic Tumor Volume in Non-Small-Cell Lung Cancer

Cited by 36 publications

References 17 publications

Metabolic Tumor Volume Measured by F-18 FDG PET/CT can Further Stratify the Prognosis of Patients with Stage IV Non-Small Cell Lung Cancer

Metabolic Tumor Volume Measured by F-18 FDG PET/CT can Further Stratify the Prognosis of Patients with Stage IV Non-Small Cell Lung Cancer

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

Exploring trade‐offs in treatment planning for brain tumor cases with a probabilistic definition of the clinical target volume

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