Impact of 4D-18FDG-PET/CT imaging on target volume delineation in SBRT patients with central versus peripheral lung tumors. Multi-reader comparative study

Chirindel, Alin; Adebahr, S.; Schuster, D.; Schimek-Jasch, Tanja; Schanne, Daniel H.; Nemer, U.; Mix, Michael; Meyer, Philipp T.; Grosu, Anca‐Ligia; Brunner, Thomas; Nestle, Ursula

doi:10.1016/j.radonc.2015.05.019

Cited by 35 publications

(19 citation statements)

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“…In the context of stereotactic body radiotherapy (SBRT), it has been shown that it may be useful to derive respiratory correlated target volumes from gated (4D) PET/CT scans in addition to 4D‐CTs . However, the current common practice still is to segment the PET volume integrated over the scan time.…”

Section: Discussion Of Segmentation Limitations Dependencies and Immentioning

confidence: 99%

“…[227][228][229] In the context of stereotactic body radiotherapy (SBRT), it has been shown that it may be useful to derive respiratory correlated target volumes from gated (4D) PET/CT scans in addition to 4D-CTs. 228,230,231 However, the current common practice still is to segment the PET volume integrated over the scan time. If PET-AS algorithms are evaluated on clinical images against the activity as seen in the uncorrected PET image, endpoint a) as described in section 4.A, the potential effect of breathing motion in these images is disregarded.…”

Section: E Effect Of Motionmentioning

confidence: 99%

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

et al. 2017

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Purpose The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application. Approach A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed. Findings A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol. Conclusions Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to ...

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Section: Discussion Of Segmentation Limitations Dependencies and Immentioning

confidence: 99%

Section: E Effect Of Motionmentioning

confidence: 99%

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

et al. 2017

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“…PET derived ITVs, mean 8.6 cm 3 compared to 6.2 cm 3 for 11 peripherally based lesions [19]. However, all the 4D PET/CT PTVs for the peripheral lesions were incorporated into the PTVs derived from CT. and a 4D PET/CT MIP [16].…”

Section: I) Impact On Gtvmentioning

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Effectiveness of Respiratory-gated Positron Emission Tomography/Computed Tomography for Radiotherapy Planning in Patients with Lung Carcinoma – A Systematic Review

et al. 2018

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The use of 4D PET/CT leads to differences in target volume delineation compared with 3D PET/CT. These differences vary depending upon technique and the clinical impact currently remains uncertain. Correlation of pretreatment target volumes generated at 3D and 4D PET/CT with postsurgical histology would be ideal but technically challenging. Evaluation of patient outcomes based on 3D versus 4D PET/CT derived treatment volumes warrants further investigation.

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“…The simplest approach involves utilizing an internal target volume. [12][13][14][15][16] For tumours near the apex of the lung where motion is minimal, this approach may be adequate. However, for tumours near the diaphragm, the internal target volume dimensions can be significant, resulting in the irradiation of a relatively large volume of healthy lung.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

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et al. 2016

The British Journal of Radiology

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Objective: To evaluate a template-based matching algorithm on single-energy (SE) and dual-energy (DE) radiographs for markerless localization of lung tumours. Methods: A total of 74 images from 17 patients with Stages IA-IV lung cancer were considered. At the time of radiotherapy treatment, gated end-expiration SE radiographs were obtained at 60 and 120 kVp at different gantry angles (33°anterior and 41°oblique), from which soft-tissue-enhanced DE images were created. A template-based matching algorithm was used to localize individual tumours on both SE and DE radiographs. Tumour centroid co-ordinates obtained from the template-matching software on both SE and DE images were compared with co-ordinates defined by physicians.Results: The template-based matching algorithm was able to successfully localize the gross tumor volume within 5 mm on 70% (52/74) of the SE images vs 91% (66/ 74) of the DE images (p , 0.01). The mean vector differences between the co-ordinates of the template matched by the algorithm and the co-ordinates of the physician-defined ground truth were 3.2 6 2.8 mm for SE images vs 2.3 6 1.7 mm for DE images (p 5 0.03). Conclusion: Template-based matching on DE images was more accurate and precise than using SE images. Advances in knowledge: This represents, to the authors' knowledge, the largest study evaluating template matching on clinical SE and DE images, considering not only anterior gantry angles but also oblique angles, suggesting a novel lung tumour matching technique using DE subtraction that is reliable, accurate and precise.

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Impact of 4D-18FDG-PET/CT imaging on target volume delineation in SBRT patients with central versus peripheral lung tumors. Multi-reader comparative study

Cited by 35 publications

References 25 publications

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

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

Effectiveness of Respiratory-gated Positron Emission Tomography/Computed Tomography for Radiotherapy Planning in Patients with Lung Carcinoma – A Systematic Review

Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

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