Adaptive radiation therapy: When, how and what are the benefits that literature provides?

Avgousti, R.; Antypas, Christos; Armpilia, Christina; Simopoulou, Foteini; Liakouli, Zoi; Karaiskos, P.; Kouloulias, Vassilis; Kyrodimos, Euthimios; Moulopoulos, Lia A.; Zygogianni, Anna

doi:10.1016/j.canrad.2021.08.023

Cited by 13 publications

(15 citation statements)

References 106 publications

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“…Therefore, it is more advantageous to treat patients with a moderate bladder protocol to ensure treatment repeatability and reduce toxicity (24,25). Although there was no significant difference in the rectum D mean between planned doses and merged CBCT-based accumulated doses (P<0.05), the has been reported as beneficial for patients with various diseases (26)(27)(28).…”

Section: Discussionmentioning

confidence: 98%

Dosimetric impacts of cone-beam computed tomography (CBCT)-based anatomic changes in intensity-modulated radiotherapy for cervical cancer

Yang¹,

Zhao²,

He³

et al. 2022

Ann Transl Med

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Background: To evaluate the effects of dose to tumors and organs at risk (OARs) on inter-fractional anatomic changes.Methods: We evaluated nine patients with cervical cancer treated with intensity-modulated radiotherapy (IMRT) (45 Gy in 25 fractions) using kV cone-beam computed tomography (CBCT) image guidance once or twice a week before treatment. For each patient, the original plan on the computed tomography (CT) image was copied to merged images, and then the fractional doses were calculated. Subsequently, deformable accumulated doses were obtained by summing the fractional absolute doses into a single dose in MIM Maestro software. The volume changes in the target and OARs were compared between the original CT and merged CBCT images, and the differences in the fractional and accumulated doses were also evaluated.Results: Sixty-nine merged CBCT images were obtained and analyzed in this study. For the target areas, the volume changes in the clinical target volume (CTV) and planning target volume (PTV) reached −18.05% and −24.11% at most, respectively. The fractional D 2% of the CTV and PTV was generally higher than the original plans, and the accumulated deviations were 2.27%±0.82% (P<0.01) and 2.42%±1.28% (P<0.01), respectively. The fractional D 98% of the PTV was underdosed up to 18.28% for 78% of patients, and the accumulated deviations were −2.06% to −17.29% (P<0.05). For the OARs, the bladder volume changes were the most dramatic, reducing up to 93.60%. The fractional Dmean and D 2cc of the bladder were generally higher than the original plans, and there were significant differences in their accumulated values (P<0.05).There was no obvious trend of rectal volume change with −69.65% to 74.20%. The rectum D mean and D 2cc of the accumulated were not significantly different from the planned dose (P>0.05).Conclusions: For patients with cervical cancer, the changes in bladder and rectal volume were greater than in the target volume. Although the volume changes in the bladder and rectum had no significant effect on D 98% of the CTV and PTV, they had a significant effect on their own D 2cc and the D 2% of the CTV and PTV.More attention should be paid to the volume changes in the bladder and rectum in clinical work.

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Section: Discussionmentioning

confidence: 98%

Dosimetric impacts of cone-beam computed tomography (CBCT)-based anatomic changes in intensity-modulated radiotherapy for cervical cancer

Yang¹,

Zhao²,

He³

et al. 2022

Ann Transl Med

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“…In the current literature, adaptation in radiotherapy for head and neck cancer seems quite timely and promising, especially in the era of image-guided radiotherapy. In a review study, Avgousti et al [ 37 ] evaluating 85 articles related to adaptive RT as an attempt to classify criteria for adaption, reported that the current thresholds which lead to replanning might be anatomical deviations > 1 cm in the external contour, average weight loss > 10%, violation in the dose coverage of the targets > 5%, and violation in the dose of the peripherals. However, beyond the expert opinion, a machine learning procedure seems more than necessary for routing clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Early Prediction of Planning Adaptation Requirement Indication Due to Volumetric Alterations in Head and Neck Cancer Radiotherapy: A Machine Learning Approach

Iliadou

Kakkos

Karaiskos

et al. 2022

Cancers

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Background: During RT cycles, the tumor response pattern could affect tumor coverage and may lead to organs at risk of overdose. As such, early prediction of significant volumetric changes could therefore reduce potential radiation-related adverse effects. Nevertheless, effective machine learning approaches based on the radiomic features of the clinically used CBCT images to determine the tumor volume variations due to RT not having been implemented so far. Methods: CBCT images from 40 HN cancer patients were collected weekly during RT treatment. From the obtained images, the Clinical Target Volume (CTV) and Parotid Glands (PG) regions of interest were utilized to calculate 104 delta-radiomics features. These features were fed on a feature selection and classification procedure for the early prediction of significant volumetric alterations. Results: The proposed framework was able to achieve 0.90 classification performance accuracy while detecting a small subset of discriminative characteristics from the 1st week of RT. The selected features were further analyzed regarding their effects on temporal changes in anatomy and tumor response modeling. Conclusion: The use of machine learning algorithms offers promising perspectives for fast and reliable early prediction of large volumetric deviations as a result of RT treatment, exploiting hidden patterns in the overall anatomical characteristics.

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“…[10][11][12][13][14][15] Several trials have identified weight loss in HNC patients as an important risk factor for geometric shifts of TVs and OAR during treatment and as a main indication for replanning. [16][17][18][19] There is a widely acknowledged concern that TVs may experience dose inhomogeneities, creating cold spots that have been associated with worse local control in non-randomized cohorts. 20,21 If ART could address these inhomogeneities, the occurrence of cold spots could be minimized, potentially leading to a reduction of in-field failure rates.…”

Section: During Radiotherapy and Their Dosimetric Consequencesmentioning

confidence: 99%

Adaptive radiotherapy for head and neck cancer: Pitfalls and possibilities from the radiation oncologist's point of view

Nuyts,

Bollen,

Eisbruch

et al. 2024

Cancer Medicine

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BackgroundPatients with head and neck cancer (HNC) may experience substantial anatomical changes during the course of radiotherapy treatment. The implementation of adaptive radiotherapy (ART) proves effective in managing the consequent impact on the planned dose distribution.MethodsThis narrative literature review comprehensively discusses the diverse strategies of ART in HNC and the documented dosimetric and clinical advantages associated with these approaches, while also addressing the current challenges for integration of ART into clinical practice.Results and ConclusionAlthough based on mainly non‐randomized and retrospective trials, there is accumulating evidence that ART has the potential to reduce toxicity and improve quality of life and tumor control in HNC patients treated with RT. However, several questions remain regarding accurate patient selection, the ideal frequency and timing of replanning, and the appropriate way for image registration and dose calculation. Well‐designed randomized prospective trials, with a predetermined protocol for both image registration and dose summation, are urgently needed to further investigate the dosimetric and clinical benefits of ART.

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Adaptive radiation therapy: When, how and what are the benefits that literature provides?

Cited by 13 publications

References 106 publications

Dosimetric impacts of cone-beam computed tomography (CBCT)-based anatomic changes in intensity-modulated radiotherapy for cervical cancer

Dosimetric impacts of cone-beam computed tomography (CBCT)-based anatomic changes in intensity-modulated radiotherapy for cervical cancer

Early Prediction of Planning Adaptation Requirement Indication Due to Volumetric Alterations in Head and Neck Cancer Radiotherapy: A Machine Learning Approach

Adaptive radiotherapy for head and neck cancer: Pitfalls and possibilities from the radiation oncologist's point of view

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