PROSTAT KANSERİNİN HACİMSEL MODÜLASYONLU ARK TEDAVİSİ İLE RADYOTERAPİSİNDE BİLGİ TABANLI PLANLAMA YÖNTEMLERİNİN KULLANILDIĞI KLİNİK ÇALIŞMALARIN DEĞERLENDİRİLMESİ
Yıl 2023,
, 67 - 77, 03.04.2023
Şeyda Kınay
,
Doğukan Akçay
,
Cenk Umay
,
Barbaros Aydın
,
Dilara Gülşan
,
Kadir Akgüngör
,
Ayşe Nur Demiral
Öz
Bilgi Tabanlı Planlama (“Knowledge Based Planningˮ-KBP), klinik olarak kabul edilebilir Yoğunluk Ayarlı Radyoterapi (“Intensity Modulated Radiotherapy”-IMRT) ve Hacimsel Modülasyonlu Ark Tedavisi (“Volumetric Modulated Arc Therapy”-VMAT) planlarını minimum iş akışıyla optimize etmek için bilgi tabanlı modeller (“Knowledge Based Model”–KBM) kullanarak plan kalitesini standart hale getirmeyi amaçlar. KBP, Risk Altındaki Organlar (‟Organ at Risk”-OAR) için ulaşılabilir Doz-Volüm Histogramı (DVH)’nı tahmin eder ve her bir yeni hasta için ideal optimizasyon hedefleri sağlar. KBP modeli, plan kalitesini iyileştirir, plan tutarlılığını koruyarak planlayıcılar arası değişkenliği azaltır ve simülasyondan tedavi başlangıcına dek geçen süreyi kısaltır.
Bu derlemede prostat kanserinin VMAT tekniği ile tedavisinde KBP tabanlı yöntemlerin kullanıldığı klinik çalışmaların sonuçları incelendi. “Knowledge-based treatment planning”, “prostate cancer”, “VMAT” anahtar kelimeleri kullanılarak “PubMed” tarama motorunda “Clinical Trial” kategorisindeki İngilizce olarak yayınlanmış makalelerin taranması sonucu ulaşılan beş adet çalışma derleme kapsamına alındı.
Bu klinik çalışmaların tümünde temelde KBP modelinin dozimetrik ve mekanik performansını değerlendirmek ve optimize etmek istenmiştir. Bu nedenle her bir kliniğin deneyimine göre hazırlanan manuel planlar, KBP ile oluşturulan otomatik planlar ile karşılaştırılmıştır. Prostat kanserinin VMAT planlamasında KBP kullanımı, doğrulama çalışmalarında, güçlü bir şekilde performans göstermiştir. KBP yöntemleri, plan kalitesi açısından genellikle uzman seviyesindeki planlayıcılara eşdeğerdir ancak ön sonuçlar, önemli ölçüde daha gelişmiş olduklarını göstermektedir. Hedef volüm ile örtüşen OAR volümlerinin dikkate alındığı KBP modellerinin örtüşme volüm histogramı (“overlap volüme histogram”-OVH) rehberliğinde daha hassas ve doğru doz tahminleri yapabileceği düşünülmektedir. KBP yöntemlerinin uygulaması sırasında dozimetrik ve mekanik performansın yanı sıra hastaya özgü kalite güvenirliğini (“Quality Assurance” –QA) doğrulamak da çok önemlidir.
Kaynakça
- Referans1 Intensity Modulated Radiation Therapy Collaborative Working Group. Intensity-modulated radiotherapy: current status and issues of interest. Int J Radiat Oncol Biol Phys. 2001;51(4):880-914.
- Referans2 Batumalai V, Jameson MG, Forstner DF, Vial P, Holloway LC. How important is dosimetrist experience for intensity modulated radiation therapy? A comparative analysis of a head and neck case. Pract Radiat Oncol. 2013; 3:e99–e106.
- Referans3 Berry SL, Ma R, Boczkowski A, Jackson A, Zhang P, Hunt M. Evaluating inter‐campus plan consistency using a knowledge based planning model. Radiat Oncol. 2016;120(2):349–355.
- Referans4 Moore KL, Schmidt R, Moiseenko V, Olsen LA, Tan J, Xiao Y, et al. Quantifying Unnecessary Normal Tissue Complication Risks due to Suboptimal Planning: A Secondary Study of RTOG 0126. Int J Radiat Oncol Biol Phys. 2015;92(2):228-35.
- Referans5 Nelms BE, Robinson G, Markham J, Velasco K, Boyd S, Narayan S, et al. Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems. Pract Radiat Oncol. 2012; 2(4):296–305.
- Referans6 Fogliata A, Reggiori G, Stravato A, Lobefalo F , Franzese C, Franceschini D, et al. RapidPlan head and neck model: the objectives and possible clinical benefit. Radiat Oncol. 2017;12:73.
- Referans7 Chang AT, Hung AW, Cheung FW, Lee MC, Chan OS, Philips H, et al. Comparison of Planning Quality and Efficiency Between Conventional and Knowledge-based Algorithms in Nasopharyngeal Cancer Patients Using Intensity Modulated Radiation Therapy. Int J Radiat Oncol Biol Phys 2016;95: 981-90.
- Referans8 Fogliata A, Nicolini G, Clivio A, Vanetti E, Laksar S, Tozzi A, et al. A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers. Radiat Oncol. 2015;10(1):220.
- Referans9 Vanderstraeten B, Goddeeris B, Vandecasteele K, Eijkeren M, Wagter C, Lievens Y. Automated instead of manual treatment planning? A plan comparison based on dose‐volume statistics and clinical preference. Int J Radiat Oncol Biol Phys. 2018;102:443–450.
- Referans10 Li N, Carmona R, Sirak I, Kasaova L, Followill D , Michalski J, et al. Highly efficient training, refinement, and validation of a knowledge‐based planning quality‐control system for radiation therapy clinical trials. Int J Radiat Oncol Biol Phys. 2017;97(1):164–172.
- Referans11 Lian J, Yuan L, Ge Y, Chera BS, Yoo DP, Chang S, et al. Modeling the dosimetry of organ-at-risk in head and neck IMRT planning: an intertechnique and interinstitutional study. Med Phys. 2013;40(12):121704.
- Referans12 Chanyavanich V, Das SK, Lee WR, Lo JY. Knowledge-based IMRT treatment planning for prostate cancer. Med Phys. 2011;38(5):2515-22.
- Referans13 Craft DL, Hong TS, Shih HA, Bortfeld TR. Improved planning time and plan quality through multicriteria optimization for intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys 2012;82(1):e83–90.
- Referans14 Voet PWJ, Breedveld S, Dirkx MLP, Levendag PC, Heijmen BJM. Integrated multicriterial optimization of beam angles and intensity profiles for coplanar and noncoplanar head and neck IMRT and implications for VMAT. Med Phys 2012;39(8):4858–65.
- Referans15 Zhu X, Ge Y, Li T, Thongphiew D, Yin FF, Wu QJ. A planning quality evaluation tool for prostate
adaptive IMRT based on machine learning. Med Phys. 2011;38(2):719–26.
- Referans16 Good D, Lo J, Lee WR, Wu QJ, Yin FF and Das SK. A knowledge-based approach to improving and homogenizing intensity modulated radiation therapy planning quality among treatment centers: an example application to prostate cancer planning Int J Radiat Oncol Biol Phys. 2013;87(1):176-81.
- Referans17 Moore KL, Brame RS, Low DA, Mutic S. Experience-based quality control of clinical intensity-modulated radiotherapy planning. Int J Radiat Oncol Biol Phys. 2011;81(2):545-51.
- Referans18 Tol JP, Delaney AR, Dahele M, Slotman BJ, Verbakel WF. Evaluation of a knowledge-based planning solution for head and neck cancer. Int J Radiat Oncol Biol Phys. 2015;91(3):612–20.
- Referans19 Wu H, Jiang F, Yue H, Li S, Zhang Y. A dosimetric evaluation of knowledgebased VMAT planning with simultaneous integrated boosting for rectal cancer patients. J Appl Clin Med Phys. 2016;17(6):78–85.
- Referans20 Kubo K, Monzen H, Ishii K, Tamura M, Kawamorita R, Sumida I, et al. Dosimetric comparison of RapidPlan and manually optimized plans in volumetric modulated arc therapy for prostate cancer. Phys Med. 2017;44: 199–204.
- Referans21 Ueda Y, Fukunaga J, Kamima T, Adachi Y, Nakamatsu K and Monzen H. Evaluation of multiple institutions’ models for knowledge-based planning of volumetric modulated arc therapy (VMAT) for prostate cancer. Radiat Oncol. 2018;13(1):46.
- Referans22 Heijmen B, Voet P, Fransen D, Penninkhof J, Milder M, Akhiat H, et al. Fully automated, multi-criterial planning for Volumetric Modulated Arc Therapy – An international multi-center validation for prostate cancer. Radiother Oncol. 2018; 128(2): 343–348.
- Referans23 Wall PDH, Carver RL and Fontenot JD. An improved distance-to-dose correlation for predicting bladder and rectum dose-volumes in knowledge-based VMAT planning for prostate cancer. Phys Med Biol. 2017; 63(1): 015035.
- Referans24 Tamura M, Monzen H, Matsumoto K, Kubo K, Otsuka M, Inada M, et al. Mechanical performance of a commercial knowledge-basedVMAT planning for prostate cancer. Radiat Oncol. 2018;13(1):163.
- Referans25 Wall PDH, Fontenot JD. Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge‐based VMAT planning technique. J Appl Clin Med Phys. 2019; 1–9.
- Referans26 Wu B, Pang D, Simari P, Taylor R, Sanguineti G, McNutt T. Using overlap volume histogram and IMRT plan data to guide and automate VMAT planning: a head‐and‐neck case study. Med Phys. 2013;40(2):021714.
- Referans27 Wu B, Ricchetti F, Sanguineti G, Kazhdan M, Simari P, Chuang M, et al. Patient geometry‐driven information retrieval for IMRT treatment plan quality control. Med Phys. 2009;36:5497–5505.
- Referans28 Wu B, Ricchetti F, Sanguineti G, Kazhdan M, Simari P, Jacques R, et al. Data‐driven approach to generating achievable dose‐volume histogram objectives in intensity‐ modulated radiotherapy planning. Int J Radiat Oncol Biol Phys. 2011;79:1241–1247.
EVALUATION OF CLINICAL STUDIES USING KNOWLEDGE BASED PLANNING METHODS IN THE RADIOTHERAPY OF PROSTATE CANCER WITH VOLUMETRIC MODULATED ARC THERAPY
Yıl 2023,
, 67 - 77, 03.04.2023
Şeyda Kınay
,
Doğukan Akçay
,
Cenk Umay
,
Barbaros Aydın
,
Dilara Gülşan
,
Kadir Akgüngör
,
Ayşe Nur Demiral
Öz
Knowledge-Based Planning (KBP) aims standardizing plan quality using models (Knowledge-Based Model (KBM)) to optimize clinically acceptable Intensity Modulated Radiotherapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT) plans with minimum workflow. KBP predicts the achievable Dose-Volume Histogram (DVH) for Organ at Risk (OAR) and provides ideal optimization targets for each new patient. The KBP model improves plan quality, maintains plan consistency through reducing inter-planner variability, and shortens the time from simulation to treatment initiation.
In this review, we assessed the results of clinical trials using the KBP-based methods in the treatment of prostate cancer with the VMAT technique. Five studies, which were reached using the keywords “knowledge-based treatment planning”, “prostate cancer”, and “VMAT” and published in English in the category of “Clinical Trial” in the “PubMed” search engine, were included in the review.
All of these clinical trials aimed to evaluate the dosimetric and mechanical performance of the KBP model and to optimize it. For this reason, manual plans prepared according to the experience of each clinic were compared with automatic plans created by KBP. The use of KBP in VMAT planning of prostate cancer has shown strong performance in validation studies. KBP methods are generally equivalent to expert-level planners in terms of plan quality, however preliminary results show that they are significantly more advanced. It is considered that KBP models which take into account OAR volumes overlapping with target volume are able to make more sensitive and accurate dose estimations under the guidance of the Overlap Volume Histogram (OVH). It is very important to verify patient-specific Quality Assurance (QA) as well as dosimetric and mechanical performance in KBP methods.
Kaynakça
- Referans1 Intensity Modulated Radiation Therapy Collaborative Working Group. Intensity-modulated radiotherapy: current status and issues of interest. Int J Radiat Oncol Biol Phys. 2001;51(4):880-914.
- Referans2 Batumalai V, Jameson MG, Forstner DF, Vial P, Holloway LC. How important is dosimetrist experience for intensity modulated radiation therapy? A comparative analysis of a head and neck case. Pract Radiat Oncol. 2013; 3:e99–e106.
- Referans3 Berry SL, Ma R, Boczkowski A, Jackson A, Zhang P, Hunt M. Evaluating inter‐campus plan consistency using a knowledge based planning model. Radiat Oncol. 2016;120(2):349–355.
- Referans4 Moore KL, Schmidt R, Moiseenko V, Olsen LA, Tan J, Xiao Y, et al. Quantifying Unnecessary Normal Tissue Complication Risks due to Suboptimal Planning: A Secondary Study of RTOG 0126. Int J Radiat Oncol Biol Phys. 2015;92(2):228-35.
- Referans5 Nelms BE, Robinson G, Markham J, Velasco K, Boyd S, Narayan S, et al. Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems. Pract Radiat Oncol. 2012; 2(4):296–305.
- Referans6 Fogliata A, Reggiori G, Stravato A, Lobefalo F , Franzese C, Franceschini D, et al. RapidPlan head and neck model: the objectives and possible clinical benefit. Radiat Oncol. 2017;12:73.
- Referans7 Chang AT, Hung AW, Cheung FW, Lee MC, Chan OS, Philips H, et al. Comparison of Planning Quality and Efficiency Between Conventional and Knowledge-based Algorithms in Nasopharyngeal Cancer Patients Using Intensity Modulated Radiation Therapy. Int J Radiat Oncol Biol Phys 2016;95: 981-90.
- Referans8 Fogliata A, Nicolini G, Clivio A, Vanetti E, Laksar S, Tozzi A, et al. A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers. Radiat Oncol. 2015;10(1):220.
- Referans9 Vanderstraeten B, Goddeeris B, Vandecasteele K, Eijkeren M, Wagter C, Lievens Y. Automated instead of manual treatment planning? A plan comparison based on dose‐volume statistics and clinical preference. Int J Radiat Oncol Biol Phys. 2018;102:443–450.
- Referans10 Li N, Carmona R, Sirak I, Kasaova L, Followill D , Michalski J, et al. Highly efficient training, refinement, and validation of a knowledge‐based planning quality‐control system for radiation therapy clinical trials. Int J Radiat Oncol Biol Phys. 2017;97(1):164–172.
- Referans11 Lian J, Yuan L, Ge Y, Chera BS, Yoo DP, Chang S, et al. Modeling the dosimetry of organ-at-risk in head and neck IMRT planning: an intertechnique and interinstitutional study. Med Phys. 2013;40(12):121704.
- Referans12 Chanyavanich V, Das SK, Lee WR, Lo JY. Knowledge-based IMRT treatment planning for prostate cancer. Med Phys. 2011;38(5):2515-22.
- Referans13 Craft DL, Hong TS, Shih HA, Bortfeld TR. Improved planning time and plan quality through multicriteria optimization for intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys 2012;82(1):e83–90.
- Referans14 Voet PWJ, Breedveld S, Dirkx MLP, Levendag PC, Heijmen BJM. Integrated multicriterial optimization of beam angles and intensity profiles for coplanar and noncoplanar head and neck IMRT and implications for VMAT. Med Phys 2012;39(8):4858–65.
- Referans15 Zhu X, Ge Y, Li T, Thongphiew D, Yin FF, Wu QJ. A planning quality evaluation tool for prostate
adaptive IMRT based on machine learning. Med Phys. 2011;38(2):719–26.
- Referans16 Good D, Lo J, Lee WR, Wu QJ, Yin FF and Das SK. A knowledge-based approach to improving and homogenizing intensity modulated radiation therapy planning quality among treatment centers: an example application to prostate cancer planning Int J Radiat Oncol Biol Phys. 2013;87(1):176-81.
- Referans17 Moore KL, Brame RS, Low DA, Mutic S. Experience-based quality control of clinical intensity-modulated radiotherapy planning. Int J Radiat Oncol Biol Phys. 2011;81(2):545-51.
- Referans18 Tol JP, Delaney AR, Dahele M, Slotman BJ, Verbakel WF. Evaluation of a knowledge-based planning solution for head and neck cancer. Int J Radiat Oncol Biol Phys. 2015;91(3):612–20.
- Referans19 Wu H, Jiang F, Yue H, Li S, Zhang Y. A dosimetric evaluation of knowledgebased VMAT planning with simultaneous integrated boosting for rectal cancer patients. J Appl Clin Med Phys. 2016;17(6):78–85.
- Referans20 Kubo K, Monzen H, Ishii K, Tamura M, Kawamorita R, Sumida I, et al. Dosimetric comparison of RapidPlan and manually optimized plans in volumetric modulated arc therapy for prostate cancer. Phys Med. 2017;44: 199–204.
- Referans21 Ueda Y, Fukunaga J, Kamima T, Adachi Y, Nakamatsu K and Monzen H. Evaluation of multiple institutions’ models for knowledge-based planning of volumetric modulated arc therapy (VMAT) for prostate cancer. Radiat Oncol. 2018;13(1):46.
- Referans22 Heijmen B, Voet P, Fransen D, Penninkhof J, Milder M, Akhiat H, et al. Fully automated, multi-criterial planning for Volumetric Modulated Arc Therapy – An international multi-center validation for prostate cancer. Radiother Oncol. 2018; 128(2): 343–348.
- Referans23 Wall PDH, Carver RL and Fontenot JD. An improved distance-to-dose correlation for predicting bladder and rectum dose-volumes in knowledge-based VMAT planning for prostate cancer. Phys Med Biol. 2017; 63(1): 015035.
- Referans24 Tamura M, Monzen H, Matsumoto K, Kubo K, Otsuka M, Inada M, et al. Mechanical performance of a commercial knowledge-basedVMAT planning for prostate cancer. Radiat Oncol. 2018;13(1):163.
- Referans25 Wall PDH, Fontenot JD. Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge‐based VMAT planning technique. J Appl Clin Med Phys. 2019; 1–9.
- Referans26 Wu B, Pang D, Simari P, Taylor R, Sanguineti G, McNutt T. Using overlap volume histogram and IMRT plan data to guide and automate VMAT planning: a head‐and‐neck case study. Med Phys. 2013;40(2):021714.
- Referans27 Wu B, Ricchetti F, Sanguineti G, Kazhdan M, Simari P, Chuang M, et al. Patient geometry‐driven information retrieval for IMRT treatment plan quality control. Med Phys. 2009;36:5497–5505.
- Referans28 Wu B, Ricchetti F, Sanguineti G, Kazhdan M, Simari P, Jacques R, et al. Data‐driven approach to generating achievable dose‐volume histogram objectives in intensity‐ modulated radiotherapy planning. Int J Radiat Oncol Biol Phys. 2011;79:1241–1247.