Adaptive Radiotherapy in Head and Neck Cancer Using Volumetric Modulated Arc Therapy

Buciuman, Nikolett; Marcu, Loredana G.

doi:10.3390/jpm12050668

Cited by 9 publications

(6 citation statements)

References 28 publications

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“…Rezultate našeg istraživanja prate i objavljeni rezultati studije autora Buciuman-a i saradnika, koji ističu da je većina ispitanika sa karcinomom glave i vrata bila muškog spola te da je reskeniranje i replaniranje izvršeno nakon 16 frakcija tretmana. Reskeniranje je izvedeno nakon slikovne verifikacije CBCT-om, kada je uočen gubitak tjelesne težine pacijenta, nemogućnosti preklapanja referentne i terapijske slike ili uslijed otežanog pozicioniranja pacijenta (9).…”

Section: Zaključakunclassified

Procjena terapijske tačnosti radioterapije karcinoma glave i vrata vođene kompjuterizovanom tomografijom konusnog snopa

Muratović¹,

Smajlbegović

Tinjak

et al. 2022

isnn.26373297.

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ABSTRACT Uvod: Karcinom glave i vrata čini 3-5 % svih malignih oboljenja, koji je većinom zastupljen kod muškaraca. Napretkom radioterapije omogućen je optimalniji pristup u liječenju karcinoma glave i vrata, sa poboljšanim ishodom liječenja. Primjena savremenih imidžing tehnika u verifikaciji preciznosti tretmana znatno je promijenila tok radioterapije u liječenju malignih bolesti u smislu eskalacije doze na ciljni volumen uz veću poštedu zdravih struktura. Svrha rada je dokazati značaj i ulogu slikovne verifikacije CBCT imidžing metodom u preciznosti liječenja i kontroli tumora tokom tretmana. Materijal i metode: Istraživanje je provedeno prospektivno u trajanju od 6 mjeseci, na Klinici za onkologiju, Kliničkog centra Univerziteta u Sarajevu. U studiju je uključeno 30 pacijenata sa karcinomom glave i vrata, kod kojih je primjenom slikovne verifikacije CBCT-om uočen gubitak tjelesne težine ili promjena ciljnog volumena. Pacijenti su zračeni VMAT tehnikom na linearnom akceleratoru TrueBeam. Rezultati: Rezultati istraživanja su pokazali da je većina pacijenata bila muškog spola (19), starije životne dobi, sa karcinom larinksa koji je bio prisutan u čak 11 ispitanika. Jači nusefekti bili su prisutni samo kod 3,33% pacijenata, a najzastupljenije neželjene reakcije bile su blaga promuklost, suhoća usta, zamor, otežano gutanje. Od ukupnog broja pacijenata, kod 16 pacijenata uočeno je smanjenje volumena targeta koji je inicijalno prosječno iznosio 80,16 cm3, dok je nakon prosječno 18 frakcija zračenja iznosio 77,58 cm3, što je sigifikanto statistički dokazano (p= 0,007). Utvrđeno je smanjenje volumena lijeve parotidne žlijezde nakon reskeniranja u odnosu na inicijalnu vrijednost (17.37±7.55/16.93±7.06 cm3). Kod svih pacijenata na CBCT volumetrijskim slikama uočen je gubitak tjelesne težine. Zaključak: Radioterapija karcinoma glave i vrata jedan je od učinkovitih modaliteta liječenja, koji moće biti praćen određenim neželjenim reakcijama. Primjena IGRT-a na osnovu kompjuterizirane tomografije konusnog snopa (CBCT), uveliko doprinosi peciznoj isporuci propisane doze zračenja, uz smanjenu toksičnost tretmana. Volumetrijski prikaz anatomskih struktura CBCT metodom, omogućio je da se promijeni tok kursa radioterapije u smislu prilagođavanja PTV margina u toku tretmana, odnosno primjenu adaptivne radioterapije.

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Section: Zaključakunclassified

Procjena terapijske tačnosti radioterapije karcinoma glave i vrata vođene kompjuterizovanom tomografijom konusnog snopa

Muratović¹,

Smajlbegović

Tinjak

et al. 2022

isnn.26373297.

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“…According to estimates from the Global Cancer Observatory, the overall incidence of HNC is on an ongoing upward trajectory, with predictions indicating an increase of 30% by the end of 2030 [1,2]. Due to the presence of multiple critical organs at risk (OARs) close to the treatment volume, radiation therapy commonly utilizes techniques such as intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) [3]. These advanced techniques enable precise targeting of the treatment volume while minimizing radiation exposure to surrounding critical structures.…”

Section: Introductionmentioning

confidence: 99%

Supervised deep learning-based synthetic computed tomography from kilovoltage cone-beam computed tomography images for adaptive radiation therapy in head and neck cancer

Khamfongkhruea,

Prakarnpilas,

Thongsawad

et al. 2024

Radiat Oncol J

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Purpose: To generate and investigate a supervised deep learning algorithm for creating synthetic computed tomography (sCT) images from kilovoltage cone-beam CT (kV-CBCT) images for adaptive radiation therapy (ART) in head and neck cancer (HNC). Materials and Methods:This study generated the supervised U-Net deep learning model using 3,491 image pairs from planning CT (pCT) and kV-CBCT datasets obtained from 40 HNC patients. The dataset was split into 80% for training and 20% for testing. The evaluation of the sCT images compared to pCT images focused on three aspects: Hounsfield units accuracy, assessed using mean absolute error (MAE) and root mean square error (RMSE); image quality, evaluated using the peak signal-tonoise ratio (PSNR) and structural similarity index (SSIM) between sCT and pCT images; and dosimetric accuracy, encompassing 3D gamma passing rates for dose distribution and percentage dose difference. Results: MAE, RMSE, PSNR, and SSIM showed improvements from their initial values of 53. 15 ± 40.09, 153.99 ± 79.78, 47.91 ± 4.98 dB, and 0.97 ± 0.02 to 41.47 ± 30.59, 130.39 ± 78.06, 49.93 ± 6.00 dB, and 0.98 ± 0.02, respectively. Regarding dose evaluation, 3D gamma passing rates for dose distribution within sCT images under 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria, yielded passing rates of 92.1% ± 3.8%, 93.8% ± 3.0%, and 96.9% ± 2.0%, respectively. The sCT images exhibited minor variations in the percentage dose distribution of the investigated target and structure volumes. However, it is worth noting that the sCT images exhibited anatomical variations when compared to the pCT images. Conclusion: These findings highlight the potential of the supervised U-Net deep learningmodel in generating kV-CBCT-based sCT images for ART in patients with HNC.

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“…Adaptive radiotherapy (ART), a paradigm which allows adaptation of treatment plans based on patients' latest anatomy (Yan et al 1997), is recognized for ensuring an optimal target coverage and minimal dose to organs at risk (OARs). This is especially beneficial for cancer sites which involves considerable anatomical changes throughout the radiotherapy course, such as head and neck (H&N) cancer (Schwartz et al 2013, Buciuman and Marcu 2022, Avkshtol et al 2023, lung cancer (Agarwal et al 2020, Møller et al 2022, Hoppen et al 2023, prostate cancer (Nijkamp et al 2008, Christiansen et al 2022, Waters et al 2024 In this context, deformable image registration (DIR) plays an important role by revealing information about the transformation between images taken at different time point during the treatment course. There are three major DIR applications in ART, namely, contour propagation, dose accumulation (Rigaud et al 2019), and synthetic CT generation for dose calculation (Irmak et al 2020, Sheikh et al 2022.…”

Section: Introductionmentioning

confidence: 99%

Deformable anthropomorphic pelvis phantom for dose accumulation verification

Wong,

Koh,

Lew

et al. 2024

Phys. Med. Biol.

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Objective: The validation of deformable image registration (DIR) for contour propagation is often done using contour-based metrics. Meanwhile, dose accumulation requires evaluation of voxel mapping accuracy, which might not be accurately represented by contour-based metrics. By fabricating a deformable anthropomorphic pelvis phantom, we aim to (1) quantify the voxel mapping accuracy for various deformation scenarios, in high- and low-contrast regions, and (2) identify any correlation between Dice similarity coefficient (DSC), a commonly used contour-based metric, and the voxel mapping accuracy for each organ.Approach: Four organs, i.e., pelvic bone, prostate, bladder and rectum, were 3D printed using PLA and a Polyjet digital material, and assembled. The latter three were implanted with glass bead and CT markers within or on their surfaces. Four deformation scenarios were simulated by varying the bladder and rectum volumes. For each scenario, nine DIRs with different parameters were performed on RayStation v10B. The voxel mapping accuracy was quantified by finding the discrepancy between true and mapped marker positions, termed the target registration error (TRE). Pearson correlation test was done between the DSC and mean TRE for each organ. Main results: For the first time, we fabricated a deformable phantom purely from 3D printing, which successfully reproduced realistic anatomical deformations. Overall, the voxel mapping accuracy dropped with increasing deformation magnitude, but improved when more organs were used to guide the DIR or limit the registration region. DSC was found to be a good indicator of voxel mapping accuracy for prostate and rectum, but a comparatively poorer one for bladder. DSC>0.85/0.90 was established as the threshold of mean TRE≤0.3 cm for rectum/prostate. For bladder, extra metrics in addition to DSC should be considered. Significance: This work presented a 3D printed phantom, which enabled quantification of voxel mapping accuracy and evaluation of correlation between DSC and voxel mapping accuracy.

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Adaptive Radiotherapy in Head and Neck Cancer Using Volumetric Modulated Arc Therapy

Cited by 9 publications

References 28 publications

Procjena terapijske tačnosti radioterapije karcinoma glave i vrata vođene kompjuterizovanom tomografijom konusnog snopa

Procjena terapijske tačnosti radioterapije karcinoma glave i vrata vođene kompjuterizovanom tomografijom konusnog snopa

Supervised deep learning-based synthetic computed tomography from kilovoltage cone-beam computed tomography images for adaptive radiation therapy in head and neck cancer

Deformable anthropomorphic pelvis phantom for dose accumulation verification

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