Automatic planning of the lower extremities for total marrow irradiation using volumetric modulated arc therapy

Lambri, Nicola; Dei, Damiano; Hernández, Víctor; Castiglioni, Isabella; Clerici, Elena; Crespi, Leonardo; Philippis, Chiara De; Loiacono, Daniele; Navarria, Pierina; Reggiori, G.; Rusconi, Roberto; Tomatis, S.; Bramanti, Stefania; Scorsetti, Marta; Mancosu, P.

doi:10.1007/s00066-022-02014-0

Cited by 8 publications

(11 citation statements)

References 32 publications

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“…Furthermore, automation tools could help reduce the workload as showed in our recent study for the planning of the TMLI lower extremities. 34 The most significant differences in Q1Gap, MeanTGI, and MCS were found between the PRO3 and PO phase (and between PRO3 and RP + PO), which indicates that the optimization algorithm had a great impact in the resulting plan complexity. RP, which uses PO as underlying algorithm, did not show any significant improvement with respect to the plain PO phase.…”

Section: Discussionmentioning

confidence: 93%

“…A new center with limited experience should consider the planning task may take longer. Furthermore, automation tools could help reduce the workload as showed in our recent study for the planning of the TMLI lower extremities 34 …”

Section: Discussionmentioning

confidence: 93%

“…Artificial intelligence (AI) tools could speed up the clinical process necessary for delivering TMLI, and to make the treatment more accessible to centers with little to no experience with the irradiation of the whole body. To this aim, the AuToMI project was created to develop AI algorithms to assist the medical physicists and clinicians in their work, from target and OARs contouring to plan optimization 34 . This study was conducted as an exploratory analysis on historical data of the AuToMI project's database.…”

Section: Discussionmentioning

confidence: 99%

“…To this aim, the AuToMI project was created to develop AI algorithms to assist the medical physicists and clinicians in their work, from target and OARs contouring to plan optimization. 34 This study was conducted as an exploratory analysis on historical data of the AuToMI project's database.…”

Section: Discussionmentioning

confidence: 99%

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Evaluation of plan complexity and dosimetric plan quality of total marrow and lymphoid irradiation using volumetric modulated arc therapy

Lambri

Dei

Hernández

et al. 2023

J Applied Clin Med Phys

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Purpose To assess the impact of the planner's experience and optimization algorithm on the plan quality and complexity of total marrow and lymphoid irradiation (TMLI) delivered by means of volumetric modulated arc therapy (VMAT) over 2010–2022 at our institute. Methods Eighty‐two consecutive TMLI plans were considered. Three complexity indices were computed to characterize the plans in terms of leaf gap size, irregularity of beam apertures, and modulation complexity. Dosimetric points of the target volume (D2%) and organs at risk (OAR) (Dmean) were automatically extracted to combine them with plan complexity and obtain a global quality score (GQS). The analysis was stratified based on the different optimization algorithms used over the years, including a knowledge‐based (KB) model. Patient‐specific quality assurance (QA) using Portal Dosimetry was performed retrospectively, and the gamma agreement index (GAI) was investigated in conjunction with plan complexity. Results Plan complexity significantly reduced over the years (r = −0.50, p < 0.01). Significant differences in plan complexity and plan dosimetric quality among the different algorithms were observed. Moreover, the KB model allowed to achieve significantly better dosimetric results to the OARs. The plan quality remained similar or even improved during the years and when moving to a newer algorithm, with GQS increasing from 0.019 ± 0.002 to 0.025 ± 0.003 (p < 0.01). The significant correlation between GQS and time (r = 0.33, p = 0.01) indicated that the planner's experience was relevant to improve the plan quality of TMLI plans. Significant correlations between the GAI and the complexity metrics (r = −0.71, p < 0.01) were also found. Conclusion Both the planner's experience and algorithm version are crucial to achieve an optimal plan quality in TMLI plans. Thus, the impact of the optimization algorithm should be carefully evaluated when a new algorithm is introduced and in system upgrades. Knowledge‐based strategies can be useful to increase standardization and improve plan quality of TMLI treatments.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Evaluation of plan complexity and dosimetric plan quality of total marrow and lymphoid irradiation using volumetric modulated arc therapy

Lambri

Dei

Hernández

et al. 2023

J Applied Clin Med Phys

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“…This work is part of the AuToMI project, which was created to guide centers which are going to introduce TMI/TMLI in their clinic, as well as to implement automated tools to streamline the TMI/TMLI treatment planning [ 28 , 29 , 30 ]. The results presented here will be used to design an improved version of the immobilization frame, which will include a dedicated cushion for the feet.…”

Section: Discussionmentioning

confidence: 99%

Impact of the Extremities Positioning on the Set-Up Reproducibility for the Total Marrow Irradiation Treatment

et al. 2023

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Total marrow (lymph node) irradiation (TMI/TMLI) delivery requires more time than standard radiotherapy treatments. The patient’s extremities, through the joints, can experience large movements. The reproducibility of TMI/TMLI patients’ extremities was evaluated to find the best positioning and reduce unwanted movements. Eighty TMI/TMLI patients were selected (2013–2022). During treatment, a cone-beam computed tomography (CBCT) was performed for each isocenter to reposition the patient. CBCT-CT pairs were evaluated considering: (i) online vector shift (OVS) that matched the two series; (ii) residual vector shift (RVS) to reposition the patient’s extremities; (iii) qualitative agreement (range 1–5). Patients were subdivided into (i) arms either leaning on the frame or above the body; (ii) with or without a personal cushion for foot positioning. The Mann-Whitney test was considered (p < 0.05 significant). Six-hundred-twenty-nine CBCTs were analyzed. The median OVS was 4.0 mm, with only 1.6% of cases ranked < 3, and 24% of RVS > 10 mm. Arms leaning on the frame had significantly smaller RVS than above the body (median: 8.0 mm/6.0 mm, p < 0.05). Using a personal cushion for the feet significantly improved the RVS than without cushions (median: 8.5 mm/1.8 mm, p < 0.01). The role and experience of the radiotherapy team are fundamental to optimizing the TMI/TMLI patient setup.

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Deep learning‐based optimization of field geometry for total marrow irradiation delivered with volumetric modulated arc therapy

Lambri,

Longari,

Loiacono

et al. 2024

Medical Physics

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BackgroundTotal marrow (lymphoid) irradiation (TMI/TMLI) is a radiotherapy treatment used to selectively target the bone marrow and lymph nodes in conditioning regimens for allogeneic hematopoietic stem cell transplantation. A complex field geometry is needed to cover the large planning target volume (PTV) of TMI/TMLI with volumetric modulated arc therapy (VMAT). Five isocenters and ten overlapping fields are needed for the upper body, while, for patients with large anatomical conformation, two specific isocenters are placed on the arms. The creation of a field geometry is clinically challenging and is performed by a medical physicist (MP) specialized in TMI/TMLI.PurposeTo develop convolutional neural networks (CNNs) for automatically generating the field geometry of TMI/TMLI.MethodsThe dataset comprised 117 patients treated with TMI/TMLI between 2011 and 2023 at our Institute. The CNN input image consisted of three channels, obtained by projecting along the sagittal plane: (1) average CT pixel intensity within the PTV; (2) PTV mask; (3) brain, lungs, liver, bowel, and bladder masks. This “averaged” frontal view combined the information analyzed by the MP when setting the field geometry in the treatment planning system (TPS). Two CNNs were trained to predict the isocenters coordinates and jaws apertures for patients with (CNN‐1) and without (CNN‐2) isocenters on the arms. Local optimization methods were used to refine the models output based on the anatomy of the patient. Model evaluation was performed on a test set of 15 patients in two ways: (1) by computing the root mean squared error (RMSE) between the CNN output and ground truth; (2) with a qualitative assessment of manual and generated field geometries—scale: 1 = not adequate, 4 = adequate—carried out in blind mode by three MPs with different expertise in TMI/TMLI. The Wilcoxon signed‐rank test was used to evaluate the independence of the given scores between manual and generated configurations (p < 0.05 significant).ResultsThe average and standard deviation values of RMSE for CNN‐1 and CNN‐2 before/after local optimization were 15 ± 2/13 ± 3 mm and 16 ± 2/18 ± 4 mm, respectively. The CNNs were integrated into a planning automation software for TMI/TMLI such that the MPs could analyze in detail the proposed field geometries directly in the TPS. The selection of the CNN model to create the field geometry was based on the PTV width to approximate the decision process of an experienced MP and provide a single option of field configuration. We found no significant differences between the manual and generated field geometries for any MP, with median values of 4 versus 4 (p = 0.92), 3 versus 3 (p = 0.78), 4 versus 3 (p = 0.48), respectively. Starting from October 2023, the generated field geometry has been introduced in our clinical practice for prospective patients.ConclusionsThe generated field geometries were clinically acceptable and adequate, even for an MP with high level of expertise in TMI/TMLI. Incorporating the knowledge of the MPs into the development cycle was crucial for optimizing the models, especially in this scenario with limited data.

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Automatic planning of the lower extremities for total marrow irradiation using volumetric modulated arc therapy

Cited by 8 publications

References 32 publications

Evaluation of plan complexity and dosimetric plan quality of total marrow and lymphoid irradiation using volumetric modulated arc therapy

Evaluation of plan complexity and dosimetric plan quality of total marrow and lymphoid irradiation using volumetric modulated arc therapy

Impact of the Extremities Positioning on the Set-Up Reproducibility for the Total Marrow Irradiation Treatment

Deep learning‐based optimization of field geometry for total marrow irradiation delivered with volumetric modulated arc therapy

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