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Alfishawy MM, Kany AI, Elshahat KM. Impact of flattening filter-free beams on remaining volume at risk in lung cancer treatment. RADIATION AND ENVIRONMENTAL BIOPHYSICS 2024; 63:455-464. [PMID: 38762614 DOI: 10.1007/s00411-024-01073-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 05/09/2024] [Indexed: 05/20/2024]
Abstract
Modern radiotherapy machines offer a new modality, like flattening filter-free beam (FFF), which is used especially in stereotactic body radiation therapy (SBRT) to reduce treatment time. The remaining volume at risk (RVR) is known as undefined normal tissue, and assists in evaluating late effects such as carcinogenesis. This study aimed to compare the effects of flattening and un-flattened beams on RVR in lung cancer treated by conventional doses using volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT). Twenty-three lung cancer patients with a prescribed dose of 60 Gy delivered in 30 fractions were selected retrospectively. Four treatment plans were generated for each case (VMAT FF, VMAT FFF, IMRT FF and IMRT FFF). Mean doses to RVR and volumes that received low doses (V15Gy, V10Gy and V5Gy) were introduced as RVR evaluation parameters. Variance percentage comparison between flattening filter (FF) and FFF for the RVR evaluation parameters gave 2.38, 1.10, 1.80 and 2.22 for VMAT, and 1.73, 1.18, 1.62 and 1.81 for IMRT. In contrast, VMAT and IMRT RVR evaluation parameters resulted in variance percentage differences of 10.29, 5.02, - 8.84 and - 4.82 for FF, and 11.18, 4.96, - 8.59 and - 4.48for FFF. It is concluded that in terms of RVR evaluation parameters, FFF is clinically beneficial compared to FF for RVR, due to the decrease in mean RVR dose and low-dose irradiated RVR volume. Furthermore, VMAT is preferred in the mean RVR dose and V15Gy, while IMRT is better in V10Gy and V5Gy for RVR.
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Affiliation(s)
| | - Amr Ismail Kany
- Radiation Physics, Faculty of Science, Al -Azhar University, Cairo, Egypt
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2
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Miles E, Wadsley J, Diez P, Patel R, Gwynne S. The National Radiotherapy Trials Quality Assurance Group - Driving up Quality in Clinical Research and Clinical Care. Clin Oncol (R Coll Radiol) 2024; 36:273-277. [PMID: 38360487 DOI: 10.1016/j.clon.2024.01.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 01/22/2024] [Accepted: 01/26/2024] [Indexed: 02/17/2024]
Affiliation(s)
- E Miles
- National Radiotherapy Trials Quality Assurance (RTTQA) Group, UK; Mount Vernon Cancer Centre, Northwood, UK.
| | - J Wadsley
- Weston Park Cancer Centre, Sheffield, UK
| | - P Diez
- National Radiotherapy Trials Quality Assurance (RTTQA) Group, UK; Mount Vernon Cancer Centre, Northwood, UK
| | - R Patel
- National Radiotherapy Trials Quality Assurance (RTTQA) Group, UK; Mount Vernon Cancer Centre, Northwood, UK
| | - S Gwynne
- National Radiotherapy Trials Quality Assurance (RTTQA) Group, UK; South West Wales Cancer Centre, Swansea, UK; Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK
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3
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Brooks C, Miles E, Hoskin PJ. Radiotherapy trial quality assurance processes: a systematic review. Lancet Oncol 2024; 25:e104-e113. [PMID: 38423056 DOI: 10.1016/s1470-2045(23)00625-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/05/2023] [Accepted: 11/28/2023] [Indexed: 03/02/2024]
Abstract
Quality assurance remains a neglected component of many trials, particularly for technical interventions, such as surgery and radiotherapy, for which quality of treatment is an important component in defining outcomes. We aimed to evaluate evidence for the processes used in radiotherapy quality assurance of clinical trials. A systematic review was undertaken focusing on use of a pre-trial outlining benchmark case and subsequent on-trial individual case reviews of outlining for recruited patients. These pre-trial and on-trial checks are used to ensure consistency and standardisation of treatment for each patient recruited to the trial by confirming protocol compliance. Non-adherence to the trial protocol has been shown to have a negative effect on trial outcomes. 29 studies published between January, 2000, and December, 2022, were identified that reported on either outlining benchmark case results or outlining individual case review results, or both. The trials identified varied in their use of radiotherapy quality assurance practices and reporting of outcomes was inconsistent. Deviations from trial protocols were frequent, particularly regarding outlining. Studies correlating benchmark case results with on-trial individual case reviews provided mixed results, meaning firm conclusions could not be drawn regarding the influence of the pre-trial benchmark case on subsequent on-trial performance. The optimal radiotherapy quality assurance processes were unclear, and there was little evidence available. Improved reporting of outcomes from radiotherapy quality assurance programmes is needed to develop an evidence base for the optimal approach to radiotherapy quality assurance in trials.
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Affiliation(s)
- Chloe Brooks
- National Radiotherapy Trials Quality Assurance Group (RTTQA), National Institute for Health and Care Research, Mount Vernon Cancer Centre, Northwood, UK.
| | - Elizabeth Miles
- National Radiotherapy Trials Quality Assurance Group (RTTQA), National Institute for Health and Care Research, Mount Vernon Cancer Centre, Northwood, UK
| | - Peter J Hoskin
- Mount Vernon Cancer Centre and Division of Cancer Sciences, University of Manchester, Manchester, UK
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4
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Kraja F, Kauweloa K, Ganju RG, Hoover AC. Impact of bowel space contouring variability on radiation dose and volume assessments in treatment planning for gynaecologic cancers. J Med Radiat Sci 2023; 70:417-423. [PMID: 37394743 PMCID: PMC10715335 DOI: 10.1002/jmrs.703] [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: 12/21/2022] [Accepted: 06/20/2023] [Indexed: 07/04/2023] Open
Abstract
INTRODUCTION Correlations between radiation dose/volume measures and small bowel (SB) toxicity are inconsistent in the medical literature. We assessed the impact of inter-provider variation in bowel bag contouring technique on estimates of radiation dose received by the SB during pelvic radiotherapy. METHODS Ten radiation oncologists contoured rectum, bladder and bowel bags on treatment planning computed tomography (CT) scans of two patients receiving adjuvant radiation for endometrial cancer. A radiation plan was generated for each patient and used to determine the radiation dose/volume for each organ. Kappa statistics were applied to assess the inter-provider contouring agreement, and Levene test evaluated the homogeneity of variance for radiation dose/volume metrics, including the V45Gy (cm3 ). RESULTS The bowel bag showed greater variation in radiation dose/volume estimates compared to the bladder and rectum. The V45Gy ranged from 163 to 384 cm3 for data set A and 109 to 409 cm3 for dataset B. Kappa values were 0.82/0.83, 0.92/0.92 and 0.94/0.86 for the bowel bag, rectum, and bladder on data sets A/B, demonstrating lower inter-provider agreement for bowel bag compared with bladder and rectum. CONCLUSION Inter-provider contouring variability is more significant for the bowel bag than the rectum and bladder, with an associated greater variability in dose and volume estimates during radiation planning.
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Affiliation(s)
- Fatjona Kraja
- Department of OncologyUniversity Hospital Centre Mother TeresaTiranaAlbania
| | - Kevin Kauweloa
- Department of Radiation OncologyQueen's Medical CentreHonoluluHawaiiUSA
| | | | - Andrew C. Hoover
- Department of Radiation OncologyUniversity of Kansas Cancer Centre, Kansas University Medical CentreKansas CityKansasUSA
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5
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Kraja F, Kauweloa K, Ganju RG, Hoover AC. Impact of bowel space contouring variability on radiation dose and volume assessments in treatment planning for gynaecologic cancers. J Med Radiat Sci 2023. [DOI: doi.org/10.1002/jmrs.703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/20/2023] [Indexed: 09/03/2023] Open
Abstract
AbstractIntroductionCorrelations between radiation dose/volume measures and small bowel (SB) toxicity are inconsistent in the medical literature. We assessed the impact of inter‐provider variation in bowel bag contouring technique on estimates of radiation dose received by the SB during pelvic radiotherapy.MethodsTen radiation oncologists contoured rectum, bladder and bowel bags on treatment planning computed tomography (CT) scans of two patients receiving adjuvant radiation for endometrial cancer. A radiation plan was generated for each patient and used to determine the radiation dose/volume for each organ. Kappa statistics were applied to assess the inter‐provider contouring agreement, and Levene test evaluated the homogeneity of variance for radiation dose/volume metrics, including the V45Gy (cm3).ResultsThe bowel bag showed greater variation in radiation dose/volume estimates compared to the bladder and rectum. The V45Gy ranged from 163 to 384 cm3 for data set A and 109 to 409 cm3 for dataset B. Kappa values were 0.82/0.83, 0.92/0.92 and 0.94/0.86 for the bowel bag, rectum, and bladder on data sets A/B, demonstrating lower inter‐provider agreement for bowel bag compared with bladder and rectum.ConclusionInter‐provider contouring variability is more significant for the bowel bag than the rectum and bladder, with an associated greater variability in dose and volume estimates during radiation planning.
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Affiliation(s)
- Fatjona Kraja
- Department of Oncology University Hospital Centre Mother Teresa Tirana Albania
| | - Kevin Kauweloa
- Department of Radiation Oncology Queen's Medical Centre Honolulu Hawaii USA
| | | | - Andrew C. Hoover
- Department of Radiation Oncology University of Kansas Cancer Centre, Kansas University Medical Centre Kansas City Kansas USA
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6
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Gifford R, Jhawar SR, Krening S. Deep Learning Architecture to Improve Edge Accuracy of Auto-Contouring for Head and Neck Radiotherapy. Diagnostics (Basel) 2023; 13:2159. [PMID: 37443553 DOI: 10.3390/diagnostics13132159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 06/16/2023] [Accepted: 06/22/2023] [Indexed: 07/15/2023] Open
Abstract
Deep learning (DL) methods have shown great promise in auto-segmentation problems. However, for head and neck cancer, we show that DL methods fail at the axial edges of the gross tumor volume (GTV) where the segmentation is dependent on information closer to the center of the tumor. These failures may decrease trust and usage of proposed auto-contouring systems. To increase performance at the axial edges, we propose the spatially adjusted recurrent convolution U-Net (SARC U-Net). Our method uses convolutional recurrent neural networks and spatial transformer networks to push information from salient regions out to the axial edges. On average, our model increased the Sørensen-Dice coefficient (DSC) at the axial edges of the GTV by 11% inferiorly and 19.3% superiorly over a baseline 2D U-Net, which has no inherent way to capture information between adjacent slices. Over all slices, our proposed architecture achieved a DSC of 0.613, whereas a 3D and 2D U-Net achieved a DSC of 0.586 and 0.540, respectively. SARC U-Net can increase accuracy at the axial edges of GTV contours while also increasing accuracy over baseline models, creating a more robust contour.
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Affiliation(s)
- Ryan Gifford
- Department of Integrated Systems Engineering, The Ohio State University, 1971 Neil Ave, Columbus, OH 43210, USA
| | - Sachin R Jhawar
- Comprehensive Cancer Center, Department of Radiation Oncology, The Ohio State University, 410 W 10th Ave, Columbus, OH 43210, USA
| | - Samantha Krening
- Department of Integrated Systems Engineering, The Ohio State University, 1971 Neil Ave, Columbus, OH 43210, USA
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Adjogatse D, Petkar I, Reis Ferreira M, Kong A, Lei M, Thomas C, Barrington SF, Dudau C, Touska P, Guerrero Urbano T, Connor SEJ. The Impact of Interactive MRI-Based Radiologist Review on Radiotherapy Target Volume Delineation in Head and Neck Cancer. AJNR Am J Neuroradiol 2023; 44:192-198. [PMID: 36702503 PMCID: PMC9891322 DOI: 10.3174/ajnr.a7773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 12/31/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND PURPOSE Peer review of head and neck cancer radiation therapy target volumes by radiologists was introduced in our center to optimize target volume delineation. Our aim was to assess the impact of MR imaging-based radiologist peer review of head and neck radiation therapy gross tumor and nodal volumes, through qualitative and quantitative analysis. MATERIALS AND METHODS Cases undergoing radical radiation therapy with a coregistered MR imaging, between April 2019 and March 2020, were reviewed. The frequency and nature of volume changes were documented, with major changes classified as per the guidance of The Royal College of Radiologists. Volumetric alignment was assessed using the Dice similarity coefficient, Jaccard index, and Hausdorff distance. RESULTS Fifty cases were reviewed between April 2019 and March 2020. The median age was 59 years (range, 29-83 years), and 72% were men. Seventy-six percent of gross tumor volumes and 41.5% of gross nodal volumes were altered, with 54.8% of gross tumor volume and 66.6% of gross nodal volume alterations classified as "major." Undercontouring of soft-tissue involvement and unidentified lymph nodes were predominant reasons for change. Radiologist review significantly altered the size of both the gross tumor volume (P = .034) and clinical target tumor volume (P = .003), but not gross nodal volume or clinical target nodal volume. The median conformity and surface distance metrics were the following: gross tumor volume Dice similarity coefficient = 0.93 (range, 0.82-0.96), Jaccard index = 0.87 (range, 0.7-0.94), Hausdorff distance = 7.45 mm (range, 5.6-11.7 mm); and gross nodular tumor volume Dice similarity coefficient = 0.95 (0.91-0.97), Jaccard index = 0.91 (0.83-0.95), and Hausdorff distance = 20.7 mm (range, 12.6-41.6). Conformity improved on gross tumor volume-to-clinical target tumor volume expansion (Dice similarity coefficient = 0.93 versus 0.95, P = .003). CONCLUSIONS MR imaging-based radiologist review resulted in major changes to most radiotherapy target volumes and significant changes in volume size of both gross tumor volume and clinical target tumor volume, suggesting that this is a fundamental step in the radiotherapy workflow of patients with head and neck cancer.
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Affiliation(s)
- D Adjogatse
- From the Departments of Oncology (D.A., I.P., M.R.F., A.K., M.L., T.G.U.)
- School of Biomedical Engineering and Imaging Sciences (D.A., C.T., S.E.J.C.)
| | - I Petkar
- From the Departments of Oncology (D.A., I.P., M.R.F., A.K., M.L., T.G.U.)
| | - M Reis Ferreira
- From the Departments of Oncology (D.A., I.P., M.R.F., A.K., M.L., T.G.U.)
| | - A Kong
- From the Departments of Oncology (D.A., I.P., M.R.F., A.K., M.L., T.G.U.)
| | - M Lei
- From the Departments of Oncology (D.A., I.P., M.R.F., A.K., M.L., T.G.U.)
| | - C Thomas
- Medical Physics (C.T.)
- School of Biomedical Engineering and Imaging Sciences (D.A., C.T., S.E.J.C.)
| | - S F Barrington
- King's College London and Guy's and St Thomas' PET Centre (S.F.B.), School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, London, UK
| | - C Dudau
- Radiology (C.D., P.T., S.E.J.C.), Guy's and St Thomas' National Health Service Foundation Trust, London, UK
- Department of Neurororadiology (C.D., S.E.J.C.), King's College Hospital, London, UK
| | - P Touska
- Radiology (C.D., P.T., S.E.J.C.), Guy's and St Thomas' National Health Service Foundation Trust, London, UK
| | - T Guerrero Urbano
- From the Departments of Oncology (D.A., I.P., M.R.F., A.K., M.L., T.G.U.)
- Faculty of Dentistry, Oral and Craniofacial Sciences (T.G.U.), King's College London, London, UK
| | - S E J Connor
- Radiology (C.D., P.T., S.E.J.C.), Guy's and St Thomas' National Health Service Foundation Trust, London, UK
- School of Biomedical Engineering and Imaging Sciences (D.A., C.T., S.E.J.C.)
- Department of Neurororadiology (C.D., S.E.J.C.), King's College Hospital, London, UK
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Mohamed AA, Risse K, Schmitz L, Schlenter M, Chughtai A, Ivanciu M, Eble MJ. Clinical validation of a semi‐automated segmentation algorithm for target volume definition on planning
CT
and
CBCT
in stereotactic body radiotherapy (
SBRT
) for peripheral lung lesions. J Med Radiat Sci 2022; 70 Suppl 2:37-47. [PMID: 36424343 PMCID: PMC10122930 DOI: 10.1002/jmrs.637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 11/14/2022] [Indexed: 11/27/2022] Open
Abstract
INTRODUCTION Stereotactic body radiotherapy (SBRT) is an ablative method for lung malignancies. Here, the definition of the gross target volume (GTV) is subject to interobserver variation. In this study, we aimed to evaluate the interobserver variability during SBRT and its dosimetric impact, as well as to introduce a semi-automated delineation tool for both planning computer tomography (P-CT) and cone beam CT (CBCT) to help to standardise GTV delineation and adaptive volume-change registration. METHODS The interobserver variation of GTV manual contours from five physicians was analysed in 15 patients after lung SBRT on free breathing (FB) P-CT (n = 15) and CBCT (n = 90) before and after each fraction. The dosimetric impact from interobserver variations of GTV based on the original treatment plan was analysed. Next, the accuracy of an in-house easy-to-use semi-automated-segmentation algorithm for pulmonary lesions was compared with gold standard contours in FB P-CT and CBCT, as well as 4D P-CT of additional 10 patients. RESULTS The interobserver variability in manual contours resulted in violations of dose coverage of the planning target volume (PTV), which, in turn, resulted in compromised tumour control probability in contours from four physicians. The validation of the semi-automated delineation algorithm using thorax phantom led to a highly reliable accuracy in defining GTVs. Comparing the unsupervised auto-contours with the gold standard delineation revealed high equal high concordance for FB P-CT, 4D P-CT and CBCT, with a DSC of 0.83, 0.76 and 0.8, respectively. The supervised use of the semi-automated delineation tool improved its accuracy, with DSCs of 0.86, 0.86 and 0.8 for FB P-CT, 4D P-CT and CBCT, respectively. The use of the algorithm was associated with a significantly shorter working time. The semi-automated delineation tool can accurately register volume changes in CBCTs. CONCLUSION The segmentation algorithm provides a reliable, standardised and time-saving alternative for manual delineation in lung SBRT in P-CT and CBCT.
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Affiliation(s)
- Ahmed Allam Mohamed
- Department of Radiation Oncology RWTH Aachen University Aachen Germany
- Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD) Aachen Germany
| | - Kathrin Risse
- Department of Radiation Oncology RWTH Aachen University Aachen Germany
- Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD) Aachen Germany
| | - Laura Schmitz
- Department of Radiation Oncology RWTH Aachen University Aachen Germany
- Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD) Aachen Germany
| | - Marsha Schlenter
- Department of Radiation Oncology RWTH Aachen University Aachen Germany
- Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD) Aachen Germany
| | - Ahmed Chughtai
- Department of Radiation Oncology RWTH Aachen University Aachen Germany
- Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD) Aachen Germany
| | - Maria Ivanciu
- Department of Radiation Oncology RWTH Aachen University Aachen Germany
- Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD) Aachen Germany
| | - Michael J. Eble
- Department of Radiation Oncology RWTH Aachen University Aachen Germany
- Center for Integrated Oncology Aachen, Bonn, Cologne and Duesseldorf (CIO ABCD) Aachen Germany
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Shen J, Zhang F, Di M, Shen J, Wang S, Chen Q, Chen Y, Liu Z, Lian X, Ma J, Pang T, Dong T, Wang B, Guan Q, He L, Zhang Y, Liang H. Clinical target volume automatic segmentation based on lymph node stations for lung cancer with bulky lump lymph nodes. Thorac Cancer 2022; 13:2897-2903. [PMID: 36085253 PMCID: PMC9575127 DOI: 10.1111/1759-7714.14638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 08/18/2022] [Accepted: 08/21/2022] [Indexed: 11/30/2022] Open
Abstract
Background The lack of standardized delineation of lymph node station in lung cancer radiotherapy leads to nonstandard clinical target volume (CTV) contouring, especially in patients with bulky lump gross target volume lymph nodes (GTVnd). This study defines lymph node region boundaries in radiotherapy for lung cancer and automatically contours lymph node stations based on the International Association for the Study of Lung Cancer (IASLC) lymph node map. Methods Computed tomography (CT) scans of 200 patients with small cell lung cancer were collected. The lymph node zone boundaries were defined based on the IASLC lymph node map, with adjustments to meet radiotherapy requirements. Contours of lymph node stations were confirmed by two experienced oncologists. A model (DiUNet) was constructed by incorporating the contours of GTVnd to precisely contour the boundaries. Quantitative evaluation metrics and clinical evaluations were conducted. Results The mean 3D Dice similarity coefficient (Dice similarity coefficient) values of DiUNet in most lymph node stations was greater than 0.7, 98.87% of the lymph node station slices are accepted. The mean DiUNet score was not significantly different from that of the man contoured in the evaluation of lymph node stations and CTV. Conclusion This is the first study to propose a method that automatically contours lymph node regions station by station based on the IASLC lymph node map with bulky lump GTVnd. Delineation of lymph node stations based on the DiUNet model is a promising strategy to obtain accuracy and efficiency for CTV delineation in lung cancer patients, especially for bulky lump GTVnd.
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Affiliation(s)
- Jie Shen
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Fuquan Zhang
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Mingyi Di
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Jing Shen
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | | | - Qi Chen
- MedMind Technology Co, Ltd., Beijing, China
| | - Yu Chen
- MedMind Technology Co, Ltd., Beijing, China
| | - Zhikai Liu
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Xin Lian
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Jiabin Ma
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Tingtian Pang
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Tingting Dong
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Bei Wang
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Qiu Guan
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Lei He
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Yue Zhang
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
| | - Hao Liang
- Department of Radiation Oncology, Peking Union Medical College, Beijing, China
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10
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Assurance qualité de la radiothérapie en recherche clinique. Cancer Radiother 2022; 26:814-817. [DOI: 10.1016/j.canrad.2022.06.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 06/24/2022] [Accepted: 06/28/2022] [Indexed: 11/20/2022]
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11
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Walls GM, Giacometti V, Apte A, Thor M, McCann C, Hanna GG, O'Connor J, Deasy JO, Hounsell AR, Butterworth KT, Cole AJ, Jain S, McGarry CK. Validation of an established deep learning auto-segmentation tool for cardiac substructures in 4D radiotherapy planning scans. Phys Imaging Radiat Oncol 2022; 23:118-126. [PMID: 35941861 PMCID: PMC9356270 DOI: 10.1016/j.phro.2022.07.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 11/10/2022] Open
Abstract
Cardiotoxicity is a common complication of lung cancer radiotherapy. Segmentation of cardiac substructures is time-consuming and challenging. Deep learning segmentation tools can perform this task in 3D and 4D scans. Performance is high when assessed geometrically, dosimetrically and clinically. Auto-segmentation tools may accelerate clinical workflows and enable research.
Background Emerging data suggest that dose-sparing several key cardiac regions is prognostically beneficial in lung cancer radiotherapy. The cardiac substructures are challenging to contour due to their complex geometry, poor soft tissue definition on computed tomography (CT) and cardiorespiratory motion artefact. A neural network was previously trained to generate the cardiac substructures using three-dimensional radiotherapy planning CT scans (3D-CT). In this study, the performance of that tool on the average intensity projection from four-dimensional (4D) CT scans (4D-AVE), now commonly used in lung radiotherapy, was evaluated. Materials and Methods The 4D-AVE of n=20 patients completing radiotherapy for lung cancer 2015–2020 underwent manual and automated cardiac substructure segmentation. Manual and automated substructures were compared geometrically and dosimetrically. Two senior clinicians also qualitatively assessed the auto-segmentation tool’s output. Results Geometric comparison of the automated and manual segmentations exhibited high levels of similarity across parameters, including volume difference (11.8% overall) and Dice similarity coefficient (0.85 overall), and were consistent with 3D-CT performance. Differences in mean (median 0.2 Gy, range −1.6–0.3 Gy) and maximum (median 0.4 Gy, range −2.2–0.9 Gy) doses to substructures were generally small. Nearly all structures (99.5 %) were deemed to be appropriate for clinical use without further editing. Conclusions Cardiac substructure auto-segmentation using a deep learning-based tool trained on a 3D-CT dataset was feasible on the 4D-AVE scan, meaning this tool is suitable for use on 4D-CT radiotherapy planning scans. Application of this tool would increase the practicality of routine clinical cardiac substructure delineation, and enable further cardiac radiation effects research.
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12
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Johnston N, De Rycke J, Lievens Y, van Eijkeren M, Aelterman J, Vandersmissen E, Ponte S, Vanderstraeten B. Dose-volume-based evaluation of convolutional neural network-based auto-segmentation of thoracic organs at risk. Phys Imaging Radiat Oncol 2022; 23:109-117. [PMID: 35936797 PMCID: PMC9352974 DOI: 10.1016/j.phro.2022.07.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 12/19/2022] Open
Abstract
Dice score and Hausdorff distance do not correlate with dose-volume-based results. Auto-contours close to the tumor or in entry/exit beams should be checked. Heart and esophagus must be checked for locally advanced non-small cell lung cancer. Bronchi must be checked for peripheral early-stage non-small cell lung cancer. Every treatment plan still passed the clinical goals for the manual organs at risk.
Background and purpose The geometrical accuracy of auto-segmentation using convolutional neural networks (CNNs) has been demonstrated. This study aimed to investigate the dose-volume impact of differences between automatic and manual OARs for locally advanced (LA) and peripherally located early-stage (ES) non-small cell lung cancer (NSCLC). Material and methods A single CNN was created for automatic delineation of the heart, lungs, main left and right bronchus, esophagus, spinal cord and trachea using 55/10/40 patients for training/validation/testing. Dice score coefficient (DSC) and 95th percentile Hausdorff distance (HD95) were used for geometrical analysis. A new treatment plan based on the auto-segmented OARs was created for each test patient using 3D for ES-NSCLC (SBRT, 3–8 fractions) and IMRT for LA-NSCLC (24–35 fractions). The correlation between geometrical metrics and dose-volume differences was investigated. Results The average (±1 SD) DSC and HD95 were 0.82 ± 0.07 and 16.2 ± 22.4 mm, while the average dose-volume differences were 0.5 ± 1.5 Gy (ES) and 1.5 ± 2.8 Gy (LA). The geometrical metrics did not correlate with the observed dose-volume differences (average Pearson for DSC: −0.27 ± 0.18 (ES) and −0.09 ± 0.12 (LA); HD95: 0.1 ± 0.3 mm (ES) and 0.2 ± 0.2 mm (LA)). Conclusions After post-processing, manual adjustments of automatic contours are only needed for clinically relevant OARs situated close to the tumor or within an entry or exit beam e.g., the heart and the esophagus for LA-NSCLC and the bronchi for ES-NSCLC. The lungs do not need to be checked further in detail.
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Affiliation(s)
- Noémie Johnston
- Centre Hospitalier Universitaire de Liège, Service de Radiothérapie, Liège, Belgium
| | - Jeffrey De Rycke
- Ghent University, Faculty of Medicine and Health Sciences, Department of Human Structure and Repair, Gent, Belgium
| | - Yolande Lievens
- Ghent University, Faculty of Medicine and Health Sciences, Department of Human Structure and Repair, Gent, Belgium
- Ghent University Hospital, Department of Radiotherapy-Oncology, Gent, Belgium
| | - Marc van Eijkeren
- Ghent University, Faculty of Medicine and Health Sciences, Department of Human Structure and Repair, Gent, Belgium
- Ghent University Hospital, Department of Radiotherapy-Oncology, Gent, Belgium
| | - Jan Aelterman
- Ghent University, Department of Physics and Astronomy, Ghent University Centre for X-ray Tomography, Gent, Belgium
- Ghent University, Department TELIN / IMEC, Image Processing Interpretation Group, Gent, Belgium
| | | | - Stephan Ponte
- Centre Hospitalier Universitaire de Liège, Service de Radiothérapie, Liège, Belgium
| | - Barbara Vanderstraeten
- Ghent University, Faculty of Medicine and Health Sciences, Department of Human Structure and Repair, Gent, Belgium
- Ghent University Hospital, Department of Radiotherapy-Oncology, Gent, Belgium
- Corresponding author at: Ghent University Hospital, Department of Radiotherapy-Oncology, RTP Ingang 98, Corneel Heymanslaan 10, B-9000 Gent, Belgium.
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Hoffmann L, Persson G, Nygård L, Nielsen T, Borrisova S, Gaard-Petersen F, Josipovic M, Khalil A, Kjeldsen R, Knap M, Kristiansen C, Møller D, Ottosson W, Sand H, Thing R, Pøhl M, Schytte T. Thorough design and pre-trial quality assurance (QA) decrease dosimetric impact of delineation and dose planning variability in the STRICTLUNG and STARLUNG trials for stereotactic body radiotherapy (SBRT) of central and ultra-central lung tumours. Radiother Oncol 2022; 171:53-61. [DOI: 10.1016/j.radonc.2022.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 03/28/2022] [Accepted: 04/05/2022] [Indexed: 10/18/2022]
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14
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Webster A, McNair HA, Hansen VN, Lewis R, Patel E, Miles E, Hall E, Hafeez S, Huddart R. Recognising the challenges of implementing multi-centre adaptive plan of the day radiotherapy. Tech Innov Patient Support Radiat Oncol 2022; 21:31-35. [PMID: 35198744 PMCID: PMC8841376 DOI: 10.1016/j.tipsro.2022.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/24/2022] [Accepted: 01/26/2022] [Indexed: 11/28/2022] Open
Abstract
Two multicentre adaptive radiotherapy trials utilising Plan of the Day (PoD) with a library of plans were introduced in 35 centres. The common issues that arose from all centres when introducing PoD were collated retrospectively, through reviewing the data pertaining to the pre-trial and on-trial quality assurance programme. It was found that 1,295 issues arose when introducing PoD in outlining, planning, treatment delivery i.e., PoD selection, and in the overall process of delivering PoD. There was no difference in the number of issues that arose from pre-trial to on-trial. Thus, it is recommended that the implementation of PoD is supported by guidance, reviews, and continuous monitoring.
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Affiliation(s)
- Amanda Webster
- National Radiotherapy Trials Quality Assurance Group (RTTQA), University College Hospital (UCLH), London, United Kingdom
| | - Helen A. McNair
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
- The Royal Marsden NHS Foundation Trust, Radiotherapy Department, London, United Kingdom
| | - Vibeke N. Hansen
- Copenhagen University Hospital -Rigshospitalet, Department of Oncology, Copenhagen, Denmark
| | - Rebecca Lewis
- Clinical Trials and Statistics Unit, The Institute of Cancer Research, London, United Kingdom
| | - Emma Patel
- National Radiotherapy Trials Quality Assurance Group (RTTQA), University College Hospital (UCLH), London, United Kingdom
| | - Elizabeth Miles
- National Radiotherapy Trials Quality Assurance Group (RTTQA), Mount Vernon Hospital, Northwood, United Kingdom
| | - Emma Hall
- Clinical Trials and Statistics Unit, The Institute of Cancer Research, London, United Kingdom
| | - Shaista Hafeez
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
- The Royal Marsden NHS Foundation Trust, Radiotherapy Department, London, United Kingdom
| | - Robert Huddart
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
- The Royal Marsden NHS Foundation Trust, Radiotherapy Department, London, United Kingdom
| | - RAIDER, HYBRID Trial Management Groups
- National Radiotherapy Trials Quality Assurance Group (RTTQA), University College Hospital (UCLH), London, United Kingdom
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom
- The Royal Marsden NHS Foundation Trust, Radiotherapy Department, London, United Kingdom
- Copenhagen University Hospital -Rigshospitalet, Department of Oncology, Copenhagen, Denmark
- Clinical Trials and Statistics Unit, The Institute of Cancer Research, London, United Kingdom
- National Radiotherapy Trials Quality Assurance Group (RTTQA), Mount Vernon Hospital, Northwood, United Kingdom
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Chiu K, Hoskin P, Gupta A, Butt R, Terparia S, Codd L, Tsang Y, Bhudia J, Killen H, Kane C, Ghoshray S, Lemon C, Megias D. The quantitative impact of joint peer review with a specialist radiologist in head and neck cancer radiotherapy planning. Br J Radiol 2022; 95:20211219. [PMID: 34918547 PMCID: PMC8822559 DOI: 10.1259/bjr.20211219] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
OBJECTIVES Radiologist input in peer review of head and neck radiotherapy has been introduced as a routine departmental approach. The aim was to evaluate this practice and to quantitatively analyse the changes made. METHODS Patients treated with radical-dose radiotherapy between August and November 2020 were reviewed. The incidence of major and minor changes, as defined by The Royal College of Radiologists guidance, was prospectively recorded. The amended radiotherapy volumes were compared with the original volumes using Jaccard Index (JI) to assess conformity; Geographical Miss Index (GMI) for undercontouring; and Hausdorff Distance (HD) between the volumes. RESULTS In total, 73 out of 87 (84%) patients were discussed. Changes were recommended in 38 (52%) patients: 30 had ≥1 major change, eight had minor changes only. There were 99 amended volumes: The overall median JI, GMI and HD was 0.91 (interquartile range [IQR]=0.80-0.97), 0.06 (IQR = 0.02-0.18) and 0.42 cm (IQR = 0.20-1.17 cm), respectively. The nodal gross-tumour-volume (GTVn) and therapeutic high-dose nodal clinical-target-volume (CTVn) had the biggest magnitude of changes: The median JI, GMI and HD of GTVn was 0.89 (IQR = 0.44-0.95), 0.11 (IQR = 0.05-0.51), 3.71 cm (IQR = 0.31-6.93 cm); high-dose CTVn was 0.78 (IQR = 0.59-0.90), 0.20 (IQR = 0.07-0.31) and 3.28 cm (IQR = 1.22-6.18 cm), respectively. There was no observed difference in the quantitative indices of the 85 'major' and 14 'minor' volumes (p = 0.5). CONCLUSIONS Routine head and neck radiologist input in radiotherapy peer review is feasible and can help avoid gross error in contouring. ADVANCES IN KNOWLEDGE The major and minor classifications may benefit from differentiation with quantitative indices but requires correlation from clinical outcomes.
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Affiliation(s)
- Kevin Chiu
- Department of Head & Neck Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Peter Hoskin
- Department of Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Amit Gupta
- Department of Head & Neck Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Roeum Butt
- Department of Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Samsara Terparia
- Department of Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Louise Codd
- Department of Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Yatman Tsang
- Department of Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Jyotsna Bhudia
- Department of Head & Neck Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Helen Killen
- Department of Head & Neck Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Clare Kane
- Department of Head & Neck Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | | | - Catherine Lemon
- Department of Head & Neck Oncology, Mount Vernon Cancer Centre, Northwood, UK
| | - Daniel Megias
- Department of Clinical Oncology, Mount Vernon Cancer Centre, Northwood, UK
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Das IJ, Compton JJ, Bajaj A, Johnstone PA. Intra- and inter-physician variability in target volume delineation in radiation therapy. JOURNAL OF RADIATION RESEARCH 2021:rrab080. [PMID: 34505151 DOI: 10.1093/jrr/rrab080] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/17/2021] [Indexed: 06/13/2023]
Abstract
Reduction in setup errors is advocated through daily imaging and adaptive therapy, where the target volume is drawn daily. Previous studies suggest that inter-physician volume variation is significant (1.5 cm standard deviation [SD]); however, there are limited data for intra-physician consistency in daily target volume delineation, which is investigated in this study. Seven patients with lung cancer were chosen based on the perceived difficulty of contouring their disease, varying from simple parenchymal lung nodules to lesions with extensive adjacent atelectasis. Four physicians delineated the gross tumor volume (GTV) for each patient on 10 separate days to see the intra- and inter-physician contouring. Isocenter coordinates (x, y and z), target volume (cm3), and largest dimensions on anterior-posterior (AP) and lateral views were recorded for each GTV. Our results show that the variability among the physicians was reflected by target volumes ranging from +109% to -86% from the mean while isocenter coordinate changes were minimal; 3.8, 1.7 and 1.9 mm for x, y and z coordinates, respectively. The orthogonal image (AP and lateral) change varied 16.3 mm and 15.0 mm respectively among days and physicians. We conclude than when performing daily imaging, random variability in contouring resulted in isocenter changes up to ±3.8 mm in our study. The shape of the target varied within ±16 mm. This study suggests that when using daily imaging to track isocenter, target volume, or treatment parameters, physicians should be aware of personal variability when considering margins added to the target volume in daily decision making especially for difficult cases.
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Affiliation(s)
- Indra J Das
- Department of Radiation Oncology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Julia J Compton
- Hancock Regional Hospital, Sue Ann Wortman Cancer Center, 801 N State St, Greenfield, IN 46410, USA
| | - Amishi Bajaj
- Department of Radiation Oncology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Peter A Johnstone
- Department of Radiation Oncology, Lee Moffitt Cancer Center, Magnolia Dr, Tampa, FL 33612, USA
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17
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Wong J, Huang V, Giambattista JA, Teke T, Kolbeck C, Giambattista J, Atrchian S. Training and Validation of Deep Learning-Based Auto-Segmentation Models for Lung Stereotactic Ablative Radiotherapy Using Retrospective Radiotherapy Planning Contours. Front Oncol 2021; 11:626499. [PMID: 34164335 PMCID: PMC8215371 DOI: 10.3389/fonc.2021.626499] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 05/14/2021] [Indexed: 12/22/2022] Open
Abstract
PURPOSE Deep learning-based auto-segmented contour (DC) models require high quality data for their development, and previous studies have typically used prospectively produced contours, which can be resource intensive and time consuming to obtain. The aim of this study was to investigate the feasibility of using retrospective peer-reviewed radiotherapy planning contours in the training and evaluation of DC models for lung stereotactic ablative radiotherapy (SABR). METHODS Using commercial deep learning-based auto-segmentation software, DC models for lung SABR organs at risk (OAR) and gross tumor volume (GTV) were trained using a deep convolutional neural network and a median of 105 contours per structure model obtained from 160 publicly available CT scans and 50 peer-reviewed SABR planning 4D-CT scans from center A. DCs were generated for 50 additional planning CT scans from center A and 50 from center B, and compared with the clinical contours (CC) using the Dice Similarity Coefficient (DSC) and 95% Hausdorff distance (HD). RESULTS Comparing DCs to CCs, the mean DSC and 95% HD were 0.93 and 2.85mm for aorta, 0.81 and 3.32mm for esophagus, 0.95 and 5.09mm for heart, 0.98 and 2.99mm for bilateral lung, 0.52 and 7.08mm for bilateral brachial plexus, 0.82 and 4.23mm for proximal bronchial tree, 0.90 and 1.62mm for spinal cord, 0.91 and 2.27mm for trachea, and 0.71 and 5.23mm for GTV. DC to CC comparisons of center A and center B were similar for all OAR structures. CONCLUSIONS The DCs developed with retrospective peer-reviewed treatment contours approximated CCs for the majority of OARs, including on an external dataset. DCs for structures with more variability tended to be less accurate and likely require using a larger number of training cases or novel training approaches to improve performance. Developing DC models from existing radiotherapy planning contours appears feasible and warrants further clinical workflow testing.
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Affiliation(s)
- Jordan Wong
- Radiation Oncology, British Columbia Cancer – Vancouver, Vancouver, BC, Canada
| | - Vicky Huang
- Medical Physics, British Columbia Cancer – Fraser Valley, Surrey, BC, Canada
| | - Joshua A. Giambattista
- Radiation Oncology, Saskatchewan Cancer Agency, Regina, SK, Canada
- Limbus AI Inc, Regina, SK, Canada
| | - Tony Teke
- Medical Physics/Radiation Oncology, British Columbia Cancer – Kelowna, Kelowna, BC, Canada
| | | | | | - Siavash Atrchian
- Medical Physics/Radiation Oncology, British Columbia Cancer – Kelowna, Kelowna, BC, Canada
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18
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Mercieca S, Belderbos JSA, van Herk M. Challenges in the target volume definition of lung cancer radiotherapy. Transl Lung Cancer Res 2021; 10:1983-1998. [PMID: 34012808 PMCID: PMC8107734 DOI: 10.21037/tlcr-20-627] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Radiotherapy, with or without systemic treatment has an important role in the management of lung cancer. In order to deliver the treatment accurately, the clinician must precisely outline the gross tumour volume (GTV), mostly on computed tomography (CT) images. However, due to the limited contrast between tumour and non-malignant changes in the lung tissue, it can be difficult to distinguish the tumour boundaries on CT images leading to large interobserver variation and differences in interpretation. Therefore the definition of the GTV has often been described as the weakest link in radiotherapy with its inaccuracy potentially leading to missing the tumour or unnecessarily irradiating normal tissue. In this article, we review the various techniques that can be used to reduce delineation uncertainties in lung cancer.
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Affiliation(s)
- Susan Mercieca
- Faculty of Health Science, University of Malta, Msida, Malta.,The University of Amsterdam, Amsterdam, The Netherlands
| | - José S A Belderbos
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Marcel van Herk
- University of Manchester, Manchester Academic Health Centre, The Christie NHS Foundation Trust, Manchester, UK
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19
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Alam SR, Li T, Zhang P, Zhang SY, Nadeem S. Generalizable cone beam CT esophagus segmentation using physics-based data augmentation. Phys Med Biol 2021; 66:065008. [PMID: 33535199 DOI: 10.1088/1361-6560/abe2eb] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Automated segmentation of the esophagus is critical in image-guided/adaptive radiotherapy of lung cancer to minimize radiation-induced toxicities such as acute esophagitis. We have developed a semantic physics-based data augmentation method for segmenting the esophagus in both planning CT (pCT) and cone beam CT (CBCT) using 3D convolutional neural networks. One hundred and ninety-one cases with their pCTs and CBCTs from four independent datasets were used to train a modified 3D U-Net architecture and a multi-objective loss function specifically designed for soft-tissue organs such as the esophagus. Scatter artifacts and noises were extracted from week-1 CBCTs using a power-law adaptive histogram equalization method and induced to the corresponding pCT were reconstructed using CBCT reconstruction parameters. Moreover, we leveraged physics-based artifact induction in pCTs to drive the esophagus segmentation in real weekly CBCTs. Segmentations were evaluated using the geometric Dice coefficient and Hausdorff distance as well as dosimetrically using mean esophagus dose and D 5cc. Due to the physics-based data augmentation, our model trained just on the synthetic CBCTs was robust and generalizable enough to also produce state-of-the-art results on the pCTs and CBCTs, achieving Dice overlaps of 0.81 and 0.74, respectively. It is concluded that our physics-based data augmentation spans the realistic noise/artifact spectrum across patient CBCT/pCT data and can generalize well across modalities, eventually improving the accuracy of treatment setup and response analysis.
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Affiliation(s)
- Sadegh R Alam
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America
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20
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Finnegan RN, Orlandini L, Liao X, Yin J, Lang J, Dowling J, Fontanarosa D. Feasibility of using a novel automatic cardiac segmentation algorithm in the clinical routine of lung cancer patients. PLoS One 2021; 16:e0245364. [PMID: 33444379 PMCID: PMC7808597 DOI: 10.1371/journal.pone.0245364] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 12/23/2020] [Indexed: 12/24/2022] Open
Abstract
Incidental radiation exposure to the heart during lung cancer radiotherapy is associated with radiation-induced heart disease and increased rates of mortality. By considering the respiratory-induced motion of the heart it is possible to create a radiotherapy plan that results in a lower overall cardiac dose. This approach is challenging using current clinical practices: manual contouring of the heart is time consuming, and subject to inter- and intra-observer variability. In this work, we investigate the feasibility of our previously developed, atlas-based, automatic heart segmentation tool to delineate the heart in four-dimensional x-ray computed tomography (4D-CT) images. We used a dataset comprising 19 patients receiving radiotherapy for lung cancer, with 4D-CT imaging acquired at 10 respiratory phases and with a maximum intensity projection image generated from these. For each patient, one of four experienced radiation oncologists contoured the heart on each respiratory phase image and the maximum intensity image. Automatic segmentation of the heart on these same patient image sets was achieved using a leave-one-out approach, where for each patient the remaining 18 were used as an atlas set. The consistency of the automatic segmentation relative to manual contouring was evaluated using the Dice similarity coefficient (DSC) and mean absolute surface-to-surface distance (MASD). The DSC and MASD are comparable to inter-observer variability in clinically acceptable whole heart delineations (average DSC > 0.93 and average MASD < 2.0 mm in all the respiratory phases). The comparison between automatic and manual delineations on the maximum intensity images produced an overall mean DSC of 0.929 and a mean MASD of 2.07 mm. The automatic, atlas-based segmentation tool produces clinically consistent and robust heart delineations and is easy to implement in the routine care of lung cancer patients.
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Affiliation(s)
- Robert Neil Finnegan
- Institute of Medical Physics, School of Physics, University of Sydney, Camperdown, New South Wales, Australia
| | - Lucia Orlandini
- Sichuan Cancer Hospital & Institute, Chengdu, China
- Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China
- School of Medicine, University of Electronic Science and Technology of China (UESTC), Chengdu, China
| | - Xiongfei Liao
- Sichuan Cancer Hospital & Institute, Chengdu, China
- Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China
- School of Medicine, University of Electronic Science and Technology of China (UESTC), Chengdu, China
| | - Jun Yin
- Sichuan Cancer Hospital & Institute, Chengdu, China
- Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China
- School of Medicine, University of Electronic Science and Technology of China (UESTC), Chengdu, China
- * E-mail: (JY); (JL)
| | - Jinyi Lang
- Sichuan Cancer Hospital & Institute, Chengdu, China
- Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China
- School of Medicine, University of Electronic Science and Technology of China (UESTC), Chengdu, China
- * E-mail: (JY); (JL)
| | - Jason Dowling
- Institute of Medical Physics, School of Physics, University of Sydney, Camperdown, New South Wales, Australia
- Australian eHealth Research Centre, CSIRO, Herston, Queensland, Australia
| | - Davide Fontanarosa
- Institute of Health Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Queensland, Australia
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21
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Barrett S, Simpkin AJ, Walls GM, Leech M, Marignol L. Geometric and Dosimetric Evaluation of a Commercially Available Auto-segmentation Tool for Gross Tumour Volume Delineation in Locally Advanced Non-small Cell Lung Cancer: a Feasibility Study. Clin Oncol (R Coll Radiol) 2020; 33:155-162. [PMID: 32798158 DOI: 10.1016/j.clon.2020.07.019] [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: 06/15/2020] [Revised: 06/24/2020] [Accepted: 07/24/2020] [Indexed: 12/25/2022]
Abstract
AIMS To quantify the reliability of a commercially available auto-segmentation tool in locally advanced non-small cell lung cancer using serial four-dimensional computed tomography (4DCT) scans during conventionally fractionated radiotherapy. MATERIALS AND METHODS Eight patients with serial 4DCT scans (n = 44) acquired over the course of radiotherapy were assessed. Each 4DCT had a physician-defined primary tumour manual contour (MC). An auto-contour (AC) and a user-adjusted auto-contour (UA-AC) were created for each scan. Geometric agreement of the AC and the UA-AC to the MC was assessed using the dice similarity coefficient (DSC), the centre of mass (COM) shift from the MC and the structure volume difference from the MC. Bland Altman analysis was carried out to assess agreement between contouring methods. Dosimetric reliability was assessed by comparison of planning target volume dose coverage on the MC and UA-AC. The time trend analysis of the geometric accuracy measures from the initial planning scan through to the final scan for each patient was evaluated using a Wilcoxon signed ranks test to assess the reliability of the UA-AC over the duration of radiotherapy. RESULTS User adjustment significantly improved all geometric comparison metrics over the AC alone. Improved agreement was observed in smaller tumours not abutting normal soft tissue and median values for geometric comparisons to the MC for DSC, tumour volume difference and COM offset were 0.80 (range 0.49-0.89), 0.8 cm3 (range 0.0-5.9 cm3) and 0.16 cm (range 0.09-0.69 cm), respectively. There were no significant differences in dose metrics measured from the MC and the UA-AC after Bonferroni correction. Variation in geometric agreement between the MC and the UA-AC were observed over the course of radiotherapy with both DSC (P = 0.035) and COM shift from the MC (ns) worsening. The median tumour volume difference from the MC improved at the later time point. CONCLUSIONS These findings suggest that the UA-AC can produce geometrically and dosimetrically acceptable contours for appropriately selected patients with non-small cell lung cancer. Larger studies are required to confirm the findings.
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Affiliation(s)
- S Barrett
- Applied Radiation Therapy Trinity, Discipline of Radiation Therapy, Trinity College Dublin, Dublin, Ireland.
| | - A J Simpkin
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland
| | - G M Walls
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - M Leech
- Applied Radiation Therapy Trinity, Discipline of Radiation Therapy, Trinity College Dublin, Dublin, Ireland
| | - L Marignol
- Applied Radiation Therapy Trinity, Discipline of Radiation Therapy, Trinity College Dublin, Dublin, Ireland
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22
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Woodford K, Panettieri V, Ruben JD, Davis S, Sim E, Tran Le T, Senthi S. Contrast enhanced oesophageal avoidance for stereotactic body radiotherapy: Barium vs. Gastrografin. Tech Innov Patient Support Radiat Oncol 2019; 12:16-22. [PMID: 32095550 PMCID: PMC7033756 DOI: 10.1016/j.tipsro.2019.10.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2019] [Revised: 10/13/2019] [Accepted: 10/21/2019] [Indexed: 12/25/2022] Open
Abstract
INTRODUCTION SABR may facilitate treatment in a greater proportion of locally-advanced NSCLC patients, just as it has for early-stage disease. The oesophagus is one of the key dose-limiting organs and visualization during IGRT would better ensure toxicity is avoided. As the oesophagus is poorly seen on CBCT, we assessed the extent to which this is improved using two oral contrast agents. MATERIALS & METHODS Six patients receiving radiotherapy for Stage I-III NSCLC were assigned to receive 50 mL Gastrografin or 50 mL barium sulphate prior to simulation and pre-treatment CBCTs. Three additional patients who did not receive contrast were included as a control group. Oesophageal visibility was determined by assessing concordance between six experienced observers in contouring the organ. 36 datasets and 216 contours were analysed. A STAPLE contour was created and compared to each individual contour. Descriptive statistics were used and a Kappa statistic, Dice Coefficient and Hausdorff distance were calculated and compared using a t-test. Contrast-induced artefact was assessed by observer scoring. RESULTS Both contrast agents significantly improved the consistency of oesophagus localisation on CBCT across all comparison metrics compared to CBCTs without contrast. Barium performed significantly better than Gastrografin with improved kappa statistics (p = 0.007), dice coefficients (p < 0.001) and Hausdorff distances (p = 0.002), although at a cost of increased image artefact. DISCUSSION Barium produced lower delineation uncertainties but more image artefact, compared to Gastrografin and no contrast. It is feasible to use oral contrast as a tool in IGRT to help guide clinicians and therapists with online matching and monitoring of the oesophageal position.
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Affiliation(s)
- Katrina Woodford
- Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria, Australia
- Department of Surgery, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Vanessa Panettieri
- Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria, Australia
- Department of Medical Imaging and Radiation Sciences, School of Biomedical Sciences, Monash University, Clayton, Victoria, Australia
| | - Jeremy D Ruben
- Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria, Australia
- Department of Surgery, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Sidney Davis
- Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria, Australia
- Department of Surgery, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Esther Sim
- Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria, Australia
| | - Trieumy Tran Le
- Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria, Australia
| | - Sashendra Senthi
- Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria, Australia
- Department of Surgery, Central Clinical School, Monash University, Melbourne, Victoria, Australia
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Provision of Organ at Risk Contouring Guidance in UK Radiotherapy Clinical Trials. Clin Oncol (R Coll Radiol) 2019; 32:e60-e66. [PMID: 31607614 DOI: 10.1016/j.clon.2019.09.054] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 08/12/2019] [Accepted: 09/03/2019] [Indexed: 01/01/2023]
Abstract
AIMS Accurate delineation of organs at risk (OAR) is vital to the radiotherapy planning process. Inaccuracies in OAR delineation arising from imprecise anatomical definitions may affect plan optimisation and risk inappropriate dose delivery to normal tissues. The aim of this study was to review the provision of OAR contouring guidance in National Institute of Health Research Clinical Research Network (NIHR CRN) portfolio clinical trials. MATERIALS AND METHODS The National Radiotherapy Quality Trials Assurance (RTTQA) Group carried out a two-round Delphi assessment to determine which OAR descriptions provided optimal guidance. RESULTS Eighty-four clinical trials involving radiotherapy quality assurance were identified as either in recruitment or in setup within the NIHR CRN portfolio. Fifty-nine trials mandated OAR contouring. In total there were 412 OAR; 171 were uniquely named; 159 OAR had more than one name associated with a single structure, with the greatest nomenclature variation seen for the femoral head ± neck, the parotid gland, and bowel. The two-round Delphi assessment determined 42 OAR descriptions as providing optimal contouring guidance. CONCLUSIONS This study identified the need for OAR nomenclature and contouring guidance consistency across clinical trials. In response to this study and in conjunction with the Global Quality Assurance of Radiation Therapy Clinical Trials Harmonisation Group, the RTTQA Group is in collaboration with international partners to provide consensus recommendations for OAR delineation in clinical trials.
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