1
|
Nenoff L, Amstutz F, Murr M, Archibald-Heeren B, Fusella M, Hussein M, Lechner W, Zhang Y, Sharp G, Vasquez Osorio E. Review and recommendations on deformable image registration uncertainties for radiotherapy applications. Phys Med Biol 2023; 68:24TR01. [PMID: 37972540 PMCID: PMC10725576 DOI: 10.1088/1361-6560/ad0d8a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 10/30/2023] [Accepted: 11/15/2023] [Indexed: 11/19/2023]
Abstract
Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.
Collapse
Affiliation(s)
- Lena Nenoff
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
- OncoRay—National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden—Rossendorf, Dresden Germany
- Helmholtz-Zentrum Dresden—Rossendorf, Institute of Radiooncology—OncoRay, Dresden, Germany
| | - Florian Amstutz
- Department of Physics, ETH Zurich, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland
| | - Martina Murr
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
| | | | - Marco Fusella
- Department of Radiation Oncology, Abano Terme Hospital, Italy
| | - Mohammad Hussein
- Metrology for Medical Physics, National Physical Laboratory, Teddington, United Kingdom
| | - Wolfgang Lechner
- Department of Radiation Oncology, Medical University of Vienna, Austria
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Greg Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Eliana Vasquez Osorio
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| |
Collapse
|
2
|
Qin A, Chen S, Liang J, Snyder M, Yan D. Evaluation of DIR schemes on tumor/organ with progressive shrinkage: accuracy of tumor/organ internal tissue tracking during the radiation treatment. Radiother Oncol 2022; 173:170-178. [PMID: 35667570 DOI: 10.1016/j.radonc.2022.05.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 05/31/2022] [Accepted: 05/31/2022] [Indexed: 11/19/2022]
Abstract
PURPOSE Accuracy of intratumoral treatment dose accumulation and response assessment highly depends on the accuracy of a DIR method. However, achievable accuracy of the existing DIR methods for tumor/organ with large and progressive shrinkage during the radiotherapy course have not been explored. This study aimed to use a bio-tissue phantom to quantify the achievable accuracy of different DIR schemes. MATERIALS /METHODS A fresh porcine liver was used for phantom material. Sixty gold markers were implanted on the surface and inside of the liver. To simulate the progressive radiation-induced tumor/organ shrinkage, the phantom was heated using a microwave oven incrementally from 30s to 200s in 8 phases. For each phase, the phantom was scanned by CT. Two extra image sets were generated from the original images: 1) the image set with overriding the high-density gold markers (feature image); 2) the image set with overriding the entire phantom to the mean soft tissue intensity (featureless image). Ten DIR schemes were evaluated to mimic clinical treatment situations of tumor/critical organ with respect to their surface and internal condition of image features, availability of intermediate feedback images and DIR methods. The internal marker's positions were utilized to evaluate DIR accuracy quantified by target registration error (TRE). RESULTS Volume reduction was about 20% ∼ 40% of the initial volume after 90s ∼ 200s of the heating. Without image features on the surface and inside of the phantom, the hybrid-DIR (image-based DIR followed by biomechanical model-based refinement) with the surface constraint achieved the registration TRE from 2.6 ± 1.2mm to 5.3 ± 2.6mm proportional to the %volume shrinkage. Meanwhile, the hybrid-DIR with the surface-marker constraint achieved the TRE from 2.4 ± 1.2mm to 2.6 ± 1.0mm. If both the surface and internal image features would be viable on the feedback images, the achievable accuracy could be minimal with the TRE from 1.6±0.9mm to 1.9 ± 1.2mm. CONCLUSIONS Standard DIR methods cannot guarantee intratumoral tissue registration accuracy for tumor/organ with large progressive shrinkage. Achievable accuracy with using the hybrid DIR method is highly dependent on the surface registration accuracy. If the surface registration mean TRE can be controlled within 2mm, the mean TRE of internal tissue can be controlled within 3mm.
Collapse
Affiliation(s)
- An Qin
- Dept. of Radiation Oncology, Beaumont Health System, Royal Oak, United States
| | - Shupeng Chen
- Dept. of Radiation Oncology, Beaumont Health System, Royal Oak, United States
| | - Jian Liang
- Dept. of Radiation Oncology, Beaumont Health System, Royal Oak, United States
| | - Michael Snyder
- Dept. of Radiation Oncology, Beaumont Health System, Royal Oak, United States
| | - Di Yan
- Dept. of Radiation Oncology, Beaumont Health System, Royal Oak, United States; Radiation Oncology, Huaxi Hospitals & Medical School, Chengdu, China.
| |
Collapse
|
3
|
Sato K, Yamashiro A, Koyama T. [Material Investigation for the Development of Non-rigid Phantoms for CT-MRI Image Registration]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2022; 78:615-624. [PMID: 35569958 DOI: 10.6009/jjrt.2022-1241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE In radiotherapy, deformable image registration (DIR) has been frequently used in different imaging examinations in recent years. However, no phantom has been established for quality assurance for DIR. In order to develop a non-rigid phantom for accuracy control between CT and MRI images, we investigated the suitability of 3D printing materials and gel materials in this study. METHODS We measured CT values, T1 values, T2 values, and the proton densities of 31 3D printer materials-purchased from three manufacturers-and one gel material. The dice coefficient after DIR was calculated for the CT-MRI images using a prototype phantom made of a gel material compatible with CT-MRI. RESULTS The CT number of the 3D printing materials ranged from -6.8 to 146.4 HU. On MRI, T1 values were not measurable in most cases, whereas T2 values were not measurable in all cases; proton density (PD) ranged from 2.51% to 4.9%. The gel material had a CT number of 111.16 HU, T1 value of 813.65 ms, and T2 value of 27.19 ms. The prototype phantom was flexible, and the usefulness of DIR with CT and MRI images was demonstrated using this phantom. CONCLUSION The CT number and T1 and T2 values of the gel material are close to those of the human body and may therefore be developed as a DIR verification phantom between CT and MRI. These findings may contribute to the development of non-rigid phantoms for DIR in the future.
Collapse
Affiliation(s)
- Kazuki Sato
- Department of Radiology, Nagano Red Cross Hospital
| | - Akihiro Yamashiro
- Department of Radiology, Nagano Red Cross Hospital.,Division of Health Sciences, Graduate School of Medical Sciences, Kanazawa University
| | - Tomio Koyama
- Department of Radiation Oncology, Nagano Red Cross Hospital
| |
Collapse
|
4
|
Shao HC, Huang X, Folkert MR, Wang J, Zhang Y. Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio). Med Phys 2021; 48:7790-7805. [PMID: 34632589 DOI: 10.1002/mp.15275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 10/01/2021] [Accepted: 10/02/2021] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Recently, two-dimensional-to-three-dimensional (2D-3D) deformable registration has been applied to deform liver tumor contours from prior reference images onto estimated cone-beam computed tomography (CBCT) target images to automate on-board tumor localizations. Biomechanical modeling has also been introduced to fine-tune the intra-liver deformation-vector-fields (DVFs) solved by 2D-3D deformable registration, especially at low-contrast regions, using tissue elasticity information and liver boundary DVFs. However, the caudal liver boundary shows low contrast from surrounding tissues in the cone-beam projections, which degrades the accuracy of the intensity-based 2D-3D deformable registration there and results in less accurate boundary conditions for biomechanical modeling. We developed a deep-learning (DL)-based method to optimize the liver boundary DVFs after 2D-3D deformable registration to further improve the accuracy of subsequent biomechanical modeling and liver tumor localization. METHODS The DL-based network was built based on the U-Net architecture. The network was trained in a supervised fashion to learn motion correlation between cranial and caudal liver boundaries to optimize the liver boundary DVFs. Inputs of the network had three channels, and each channel featured the 3D DVFs estimated by the 2D-3D deformable registration along one Cartesian direction (x, y, z). To incorporate patient-specific liver boundary information into the DVFs, the DVFs were masked by a liver boundary ring structure generated from the liver contour of the prior reference image. The network outputs were the optimized DVFs along the liver boundary with higher accuracy. From these optimized DVFs, boundary conditions were extracted for biomechanical modeling to further optimize the solution of intra-liver tumor motion. We evaluated the method using 34 liver cancer patient cases, with 24 for training and 10 for testing. We evaluated and compared the performance of three methods: 2D-3D deformable registration, 2D-3D-Bio (2D-3D deformable registration with biomechanical modeling), and DL-Bio (DL model prediction with biomechanical modeling). The tumor localization errors were quantified through calculating the center-of-mass-errors (COMEs), DICE coefficients, and Hausdorff distance between deformed liver tumor contours and manually segmented "gold-standard" contours. RESULTS The predicted DVFs by the DL model showed improved accuracy at the liver boundary, which translated into more accurate liver tumor localizations through biomechanical modeling. On a total of 90 evaluated images and tumor contours, the average (± sd) liver tumor COMEs of the 2D-3D, 2D-3D-Bio, and DL-Bio techniques were 4.7 ± 1.9 mm, 2.9 ± 1.0 mm, and 1.7 ± 0.4 mm. The corresponding average (± sd) DICE coefficients were 0.60 ± 0.12, 0.71 ± 0.07, and 0.78 ± 0.03; and the average (± sd) Hausdorff distances were 7.0 ± 2.6 mm, 5.4 ± 1.5 mm, and 4.5 ± 1.3 mm, respectively. CONCLUSION DL-Bio solves a general correlation model to improve the accuracy of the DVFs at the liver boundary. With improved boundary conditions, the accuracy of biomechanical modeling can be further increased for accurate intra-liver low-contrast tumor localization.
Collapse
Affiliation(s)
- Hua-Chieh Shao
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Xiaokun Huang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Michael R Folkert
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jing Wang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - You Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| |
Collapse
|
5
|
Hamming-Vrieze O, van Kranen S, Walraven I, Navran A, Al-Mamgani A, Tesselaar M, van den Brekel M, Sonke JJ. Deterioration of Intended Target Volume Radiation Dose Due to Anatomical Changes in Patients with Head-and-Neck Cancer. Cancers (Basel) 2021; 13:cancers13174253. [PMID: 34503061 PMCID: PMC8428222 DOI: 10.3390/cancers13174253] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/11/2021] [Accepted: 08/18/2021] [Indexed: 11/16/2022] Open
Abstract
Delivered radiation dose can differ from intended dose. This study quantifies dose deterioration in targets, identifies predictive factors, and compares dosimetric to clinical patient selection for adaptive radiotherapy in head-and-neck cancer patients. One hundred and eighty-eight consecutive head-and-neck cancer patients treated up to 70 Gy were analyzed. Daily delivered dose was calculated, accumulated, and compared to the planned dose. Cutoff values (1 Gy/2 Gy) were used to assess plan deterioration in the highest/lowest dose percentile (D1/D99). Differences in clinical factors between patients with/without dosimetric deterioration were statistically tested. Dosimetric deterioration was evaluated in clinically selected patients for adaptive radiotherapy with CBCT. Respectively, 16% and 4% of patients had deterioration over 1 Gy in D99 and D1 in any of the targets, this was 5% (D99) and 2% (D1) over 2 Gy. Factors associated with deterioration of D99 were higher baseline weight/BMI, weight gain early in treatment, and smaller PTV margins. The sensitivity of visual patient selection with CBCT was 22% for detection of dosimetric changes over 1 Gy. Large dose deteriorations in targets occur in a minority of patients. Clinical prediction based on patient characteristics or CBCT is challenging and dosimetric selection tools seem warranted to identify patients in need for ART, especially in treatment with small PTV margins.
Collapse
Affiliation(s)
- Olga Hamming-Vrieze
- Department of Radiation Oncology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; (S.v.K.); (I.W.); (A.N.); (A.A.-M.); (J.-J.S.)
- Correspondence:
| | - Simon van Kranen
- Department of Radiation Oncology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; (S.v.K.); (I.W.); (A.N.); (A.A.-M.); (J.-J.S.)
| | - Iris Walraven
- Department of Radiation Oncology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; (S.v.K.); (I.W.); (A.N.); (A.A.-M.); (J.-J.S.)
| | - Arash Navran
- Department of Radiation Oncology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; (S.v.K.); (I.W.); (A.N.); (A.A.-M.); (J.-J.S.)
| | - Abrahim Al-Mamgani
- Department of Radiation Oncology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; (S.v.K.); (I.W.); (A.N.); (A.A.-M.); (J.-J.S.)
| | - Margot Tesselaar
- Department of Medical Oncology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands;
| | - Michiel van den Brekel
- Department of Head and Neck Surgery, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands;
| | - Jan-Jakob Sonke
- Department of Radiation Oncology, Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; (S.v.K.); (I.W.); (A.N.); (A.A.-M.); (J.-J.S.)
| |
Collapse
|
6
|
Bjarnason TA, Rees R, Kainz J, Le LH, Stewart EE, Preston B, Elbakri I, Fife IAJ, Lee T, Gagnon IMB, Arsenault C, Therrien P, Kendall E, Tonkopi E, Cottreau M, Aldrich JE. An international survey on the clinical use of rigid and deformable image registration in radiotherapy. J Appl Clin Med Phys 2020; 21:10-24. [PMID: 32915492 PMCID: PMC7075391 DOI: 10.1002/acm2.12957] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 01/13/2020] [Accepted: 05/14/2020] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES Rigid image registration (RIR) and deformable image registration (DIR) are widely used in radiotherapy. This project aims to capture current international approaches to image registration. METHODS A survey was designed to identify variations in use, resources, implementation, and decision-making criteria for clinical image registration. This was distributed to radiotherapy centers internationally in 2018. RESULTS There were 57 responses internationally, from the Americas (46%), Australia/New Zealand (32%), Europe (12%), and Asia (10%). Rigid image registration and DIR were used clinically for computed tomography (CT)-CT registration (96% and 51%, respectively), followed by CT-PET (81% and 47%), CT-CBCT (84% and 19%), CT-MR (93% and 19%), MR-MR (49% and 5%), and CT-US (9% and 0%). Respondent centers performed DIR using dedicated software (75%) and treatment planning systems (29%), with 84% having some form of DIR software. Centers have clinically implemented DIR for atlas-based segmentation (47%), multi-modality treatment planning (65%), and dose deformation (63%). The clinical use of DIR for multi-modality treatment planning and accounting for retreatments was considered to have the highest benefit-to-risk ratio (69% and 67%, respectively). CONCLUSIONS This survey data provides useful insights on where, when, and how image registration has been implemented in radiotherapy centers around the world. DIR is mainly in clinical use for CT-CT (51%) and CT-PET (47%) for the head and neck (43-57% over all use cases) region. The highest benefit-risk ratio for clinical use of DIR was for multi-modality treatment planning and accounting for retreatments, which also had higher clinical use than for adaptive radiotherapy and atlas-based segmentation.
Collapse
Affiliation(s)
- Thorarin A. Bjarnason
- Medical ImagingInterior Health AuthorityKelownaBCCanada
- RadiologyUniversity of British ColumbiaVancouverBCCanada
- PhysicsUniversity of British Columbia OkanaganKelownaBCCanada
| | - Robert Rees
- Occupational Health & SafetyYukon Workers' Compensation Health and Safety BoardWhitehorseYKCanada
| | - Judy Kainz
- Workers' Safety and Compensation Commission for Northwest Territories and NunavutYellowknifeNTCanada
| | - Lawrence H. Le
- Diagnostic ImagingAlberta Health ServicesCalgaryABCanada
- Radiology and Diagnostic ImagingUniversity of AlbertaEdmontonABCanada
| | | | - Brent Preston
- Radiation Safety UnitGovernment of SaskatchewanSaskatoonSKCanada
| | - Idris Elbakri
- Cancer Care ManitobaWinnipegMBCanada
- Physics and AstronomyUniversity of ManitobaWinnipegMBCanada
- RadiologyUniversity of ManitobaWinnipegMBCanada
| | - Ingvar A. J. Fife
- Cancer Care ManitobaWinnipegMBCanada
- Physics and AstronomyUniversity of ManitobaWinnipegMBCanada
- RadiologyUniversity of ManitobaWinnipegMBCanada
| | - Ting‐Yim Lee
- St Joseph’s Health Care LondonLondonONCanada
- Lawson Research InstituteLondonONCanada
- Medical ImagingMedical Biophysics, OncologyRobarts Research InstituteUniversity of Western OntarioLondonONCanada
| | | | - Clément Arsenault
- Hôpital Dr Georges–L. DumontCentre d'Oncologie Dr Léon–RichardMonctonNBCanada
| | | | | | - Elena Tonkopi
- Nova Scotia Health AuthorityHalifaxNSCanada
- Diagnostic RadiologyDalhousie UniversityHalifaxNSCanada
- Radiation OncologyDalhousie UniversityHalifaxNSCanada
| | | | | |
Collapse
|
7
|
Sugawara Y, Kadoya N, Kotabe K, Nakajima Y, Ikeda R, Tanabe S, Ohashi H, Jingu K. Development of a dynamic deformable thorax phantom for the quality management of deformable image registration. Phys Med 2020; 77:100-107. [PMID: 32823209 DOI: 10.1016/j.ejmp.2020.08.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 08/07/2020] [Accepted: 08/07/2020] [Indexed: 11/26/2022] Open
Abstract
The purpose of this study was to develop a novel dynamic deformable thorax phantom for deformable image registration (DIR) quality assurance (QA) and to verify as a tool for commissioning and DIR QA. The phantom consists of a base phantom, an inner phantom, and a motor-derived piston. The base phantom is an acrylic cylinder phantom with a diameter of 180 mm. The inner phantom consists of deformable, 20 mm thick disk-shaped sponges. To evaluate the physical characteristics of the phantom, we evaluated its image quality and deformation. DIR accuracies were evaluated using the three types of commercially DIR software (MIM, RayStation, and Velocity AI) to test the feasibility of this phantom. We used different DIR parameters to test the impact of parameters on DIR accuracy in various phantom settings. To evaluate DIR accuracy, a target registration error (TRE) was calculated using the anatomical landmark points. The three locations (i.e., distal, middle, and proximal positions) had different displacement amounts. This result indicated that the inner phantom was not moved but deformed. In cases with different phantom settings and marker settings, the ranges of the average TRE were 0.63-15.60 mm (MIM). In cases with different DIR parameters settings, the ranges of the average TRE were as follows: 0.73-7.10 mm (MIM), 8.25-8.66 mm (RayStation), and 8.26-8.43 mm (Velocity). These results suggest that our phantom could evaluate the detailed DIR behaviors with TRE. Therefore, this is indicative of the potential usefulness of our phantom in DIR commissioning and QA.
Collapse
Affiliation(s)
- Yasuharu Sugawara
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Miyagi, Japan; Department of Radiology, Center Hospital of National Center for Global Health and Medicine, Tokyo, Japan
| | - Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Miyagi, Japan.
| | - Kazuki Kotabe
- Department of Radiology, Center Hospital of National Center for Global Health and Medicine, Tokyo, Japan
| | - Yujiro Nakajima
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Miyagi, Japan; Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | - Ryutaro Ikeda
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Miyagi, Japan; Department of Radiology, Ishinomaki Red-Cross Hospital, Miyagi, Japan
| | - Shunpei Tanabe
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Miyagi, Japan
| | - Haruna Ohashi
- Course of Radiological Technology, Health Sciences, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Keiichi Jingu
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Miyagi, Japan
| |
Collapse
|
8
|
Kadoya N, Kito S, Kurooka M, Saito M, Takemura A, Tohyama N, Tominaga M, Nakajima Y, Fujita Y, Miyabe Y. Factual survey of the clinical use of deformable image registration software for radiotherapy in Japan. JOURNAL OF RADIATION RESEARCH 2019; 60:546-553. [PMID: 31125076 PMCID: PMC6640912 DOI: 10.1093/jrr/rrz034] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 02/24/2019] [Indexed: 05/02/2023]
Abstract
Deformable image registration (DIR) has recently become commercially available in the field of radiotherapy. However, there was no detailed information regarding the use of DIR software at each medical institution. Thus, in this study, we surveyed the status of the clinical use of DIR software for radiotherapy in Japan. The Japan Society of Medical Physics and the Japanese Society for Radiation Oncology mailing lists were used to announce this survey. The questionnaire was created by investigators working under the research grant of the Japanese Society for Radiation Oncology (2017-2018) and intended for the collection of information regarding the use of DIR in radiotherapy. The survey was completed by 161 institutions in Japan. The survey results showed that dose accumulation was the most frequent purpose for which DIR was used in clinical practice (73%). Various commissioning methods were performed, although they were not standardized. Qualitative evaluation with actual patient images was the most commonly used method (28%), although 30% of the total number of responses (42% of institutions) reported that they do not perform commissioning. We surveyed the current status of clinical use of DIR software for radiotherapy in Japan for the first time. Our results indicated that a certain number of institutions used DIR software for clinical practice, and various commissioning methods were performed, although they were not standardized. Taken together, these findings highlight the need for a technically unified approach for commissioning and quality assurance for the use of DIR software in Japan.
Collapse
Affiliation(s)
- Noriyuki Kadoya
- Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan
- Corresponding author. Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, 980-8574 Japan. Tel: +81-22-717-7312; Fax: +81-22-717-7316; E-mail:
| | - Satoshi Kito
- Department of Radiotherapy, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | | | - Masahide Saito
- Department of Radiology, University of Yamanashi, Yamanashi, Japan
| | - Akihiro Takemura
- Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | - Naoki Tohyama
- Department of Radiation Oncology, Tokyo Bay Advanced Imaging and Radiation Oncology Clinic Makuhari, Chiba, Japan
| | - Masahide Tominaga
- Department of Therapeutic Radiology, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
| | - Yujiro Nakajima
- Department of Radiotherapy, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan
| | - Yukio Fujita
- Department of Radiological Sciences, Faculty of Health Sciences, Komazawa University, Tokyo, Japan
| | - Yuki Miyabe
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, Kyoto, Japan
| |
Collapse
|
9
|
Head and Neck Cancer Adaptive Radiation Therapy (ART): Conceptual Considerations for the Informed Clinician. Semin Radiat Oncol 2019; 29:258-273. [PMID: 31027643 DOI: 10.1016/j.semradonc.2019.02.008] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
For nearly 2 decades, adaptive radiation therapy (ART) has been proposed as a method to account for changes in head and neck tumor and normal tissue to enhance therapeutic ratios. While technical advances in imaging, planning and delivery have allowed greater capacity for ART delivery, and a series of dosimetric explorations have consistently shown capacity for improvement, there remains a paucity of clinical trials demonstrating the utility of ART. Furthermore, while ad hoc implementation of head and neck ART is reported, systematic full-scale head and neck ART remains an as yet unreached reality. To some degree, this lack of scalability may be related to not only the complexity of ART, but also variability in the nomenclature and descriptions of what is encompassed by ART. Consequently, we present an overview of the history, current status, and recommendations for the future of ART, with an eye toward improving the clarity and description of head and neck ART for interested clinicians, noting practical considerations for implementation of an ART program or clinical trial. Process level considerations for ART are noted, reminding the reader that, paraphrasing the writer Elbert Hubbard, "Art is not a thing, it is a way."
Collapse
|