Frontiers in planning optimization for lung SBRT

Giglioli, F.R.; Clemente, Stefania; Esposito, Marco; Fiandra, C.; Marino, C.; Russo, S.; Strigari, Lidia; Villaggi, E.; Stasi, M.; Mancosu, P.

doi:10.1016/j.ejmp.2017.05.064

Cited by 28 publications

(16 citation statements)

References 82 publications

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“…Twenty‐four papers/reviews/letters have been published on top 50% ranking Radiation Oncology journals in 2014–2019 period, 18–40 with authors list selected according to Vancouver recommendations. In detail, 15 full papers 19–23,28–32,34–36,38,40 .…”

Section: Resultsmentioning

confidence: 99%

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Lean Thinking to manage a national working group on physics aspects of Stereotactic Body Radiation Therapy

Mancosu

Russo

Antonucci³

et al. 2021

Medical Physics

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To report how the adoption of a Lean Thinking mindset in the management of a national working group (WG) on the physics of stereotactic body radiation therapy (SBRT) contributed to achieve SBRT standardization objectives. Methods: Vision for the WG has been established as fragmentation reduction and process harmonization enhancement in SBRT for Italian centers. Two main research themes of the technical aspects of SBRT emerged as areas with major standardization improvement needs, small field dosimetry and SBRT planning comparisons, to be investigated through multi-institutional studies. The management of the WG leveraged on the Lean concept of fostering self-organization in a non-hierarchical environment. Four progressive involvement levels were defined for each study. No specific "scientific" preexperience was required to propose and coordinate a project, just requiring a voluntary commitment. People engagement was measured in terms of number of published articles. The standardization goals have been conducted through a simplified "5S" (Sort, Set in Order, Shine, Standardize, and Sustain) methodology, first considering a phase of awareness (the first three "S"), then identifying and implementing standardization actions (the last two "S"). Results: Since the beginning, 157 medical physicists joined the AIFM/SBRT-WG. Twenty-four papers/reviews/letters have been published in the period 2014-2019 on major radiation oncology journals, authored by >100 physicists (>50% working in small hospitals). Six over 12 first authors worked in peripheral/small hospitals, with no prior publication as first author. These studies contributed to the awareness and standardization phases for both small-field dosimetry and planning. In particular, errors in small-field measurements in 8% of centers were detected thanks to a generalized output factor curve in function of the effective field size created by averaging data available from different Linacs. Furthermore, planner's experience in SBRT was correlated with dosimetric parameters in the awareness phase; while sharing median dose volume histograms (DVHs) reduced variability among centers while keeping the same level of plan complexity. Finally, all the dosimetric parameters statistically significant to the planner experience during the awareness phase, were no longer significantly different in the standardization phase. Conclusions: The experience of our SBRT-WG has shown how a Lean Thinking mindset could foster the SBRT procedure standardization and spread the physics of SBRT knowledge, enhancing personal growth. Our expectation is to inspire other scientific societies that have to deal with fragmented contexts or pursue processes harmonization through Lean principles.

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Section: Resultsmentioning

confidence: 99%

“…In detail, 15 full papers 19–23,28–32,34–36,38,40 . 5 reviews, 18,27,33,37,41 1 editorial, 25 and 3 letters to the editor 24,26,39 were published. A total of more than 100 medical physicists were authors of at least one article, showing high level of members’ engagement.…”

Section: Resultsmentioning

confidence: 99%

Lean Thinking to manage a national working group on physics aspects of Stereotactic Body Radiation Therapy

Mancosu

Russo

Antonucci³

et al. 2021

Medical Physics

Self Cite

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“…The planning CT images used in this study were acquired under a free-breathing condition due to small tumor motion or patient's performance status. Patients' breathing motions or tumor motion may influence the accuracy at all steps of the treatment process due to image blurring, dose blurring, interplay effects [33,34]. In particular, the image blurring effect, which causes ambiguous outlines of tumors, could affect the segmentation accuracy of the automated frameworks.…”

Section: Discussionmentioning

confidence: 99%

Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy

et al. 2017

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The aim of this study was to investigate the impact of pixel-based machine learning (ML) techniques, i.e., fuzzy-c-means clustering method (FCM), and the artificial neural network (ANN) and support vector machine (SVM), on an automated framework for delineation of gross tumor volume (GTV) regions of lung cancer for stereotactic body radiation therapy. The morphological and metabolic features for GTV regions, which were determined based on the knowledge of radiation oncologists, were fed on a pixel-by-pixel basis into the respective FCM, ANN, and SVM ML techniques. Then, the ML techniques were incorporated into the automated delineation framework of GTVs followed by an optimum contour selection (OCS) method, which we proposed in a previous study. The three-ML-based frameworks were evaluated for 16 lung cancer cases (six solid, four ground glass opacity (GGO), six part-solid GGO) with the datasets of planning computed tomography (CT) and F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT images using the three-dimensional Dice similarity coefficient (DSC). DSC denotes the degree of region similarity between the GTVs contoured by radiation oncologists and those estimated using the automated framework. The FCM-based framework achieved the highest DSCs of 0.79±0.06, whereas DSCs of the ANN-based and SVM-based frameworks were 0.76±0.14 and 0.73±0.14, respectively. The FCM-based framework provided the highest segmentation accuracy and precision without a learning process (lowest calculation cost). Therefore, the FCM-based framework can be useful for delineation of tumor regions in practical treatment planning.

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“…The most prevalent attitude is to obtain an inhomogeneous dose distribution with hot spots inside the GTV, because it delivers a larger dose to the PTV while sparing the normal lung more effectively. 25 Moreover, inhomogeneity with high doses inside GTV hypothetically can contribute to control hypoxic areas and improve LC. There is experimental evidence that suggests unique extra tumoricidal mechanism at high doses (e.g.…”

Section: What Dose Distribution Best Correlates With Lc and Os?mentioning

confidence: 99%

Dose prescription in SBRT for early-stage non-small cell lung cancer: are we all speaking the same language?

Merlotti

Bonomo

Ragona

et al. 2020

Tumori

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Introduction: Stereotactic body radiation therapy is increasingly used in the treatment of early-stage lung cancers. Guidelines provide indications regarding the constraints to the organs at risk (OARs) and the minimum coverage of the planning target volume but do not suggest optimal dose distribution. Data on dose distribution from the different published series are not comparable due to different prescription modalities and reported dose parameters. Methods: We conducted a review of the published data on dose prescription, focusing on the role of homogeneity on local tumor control, and present suggestions on how to specify and report the prescriptions to permit comparisons between studies or between cases from different centers. Conclusions: To identify the dose-prescription modality that better correlates with oncologic outcomes, future studies should guarantee a close uniformity of dose distribution between cases and complete dose parameters reporting for treatment volumes and OARs.

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Frontiers in planning optimization for lung SBRT

Cited by 28 publications

References 82 publications

Lean Thinking to manage a national working group on physics aspects of Stereotactic Body Radiation Therapy

Lean Thinking to manage a national working group on physics aspects of Stereotactic Body Radiation Therapy

Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy

Dose prescription in SBRT for early-stage non-small cell lung cancer: are we all speaking the same language?

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