1
|
Court LE, Aggarwal A, Jhingran A, Naidoo K, Netherton T, Olanrewaju A, Peterson C, Parkes J, Simonds H, Trauernicht C, Zhang L, Beadle BM. Artificial Intelligence-Based Radiotherapy Contouring and Planning to Improve Global Access to Cancer Care. JCO Glob Oncol 2024; 10:e2300376. [PMID: 38484191 PMCID: PMC10954080 DOI: 10.1200/go.23.00376] [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: 10/03/2023] [Revised: 11/22/2023] [Accepted: 01/22/2024] [Indexed: 03/19/2024] Open
Abstract
PURPOSE Increased automation has been identified as one approach to improving global cancer care. The Radiation Planning Assistant (RPA) is a web-based tool offering automated radiotherapy (RT) contouring and planning to low-resource clinics. In this study, the RPA workflow and clinical acceptability were assessed by physicians around the world. METHODS The RPA output for 75 cases was reviewed by at least three physicians; 31 radiation oncologists at 16 institutions in six countries on five continents reviewed RPA contours and plans for clinical acceptability using a 5-point Likert scale. RESULTS For cervical cancer, RPA plans using bony landmarks were scored as usable as-is in 81% (with minor edits 93%); using soft tissue contours, plans were scored as usable as-is in 79% (with minor edits 96%). For postmastectomy breast cancer, RPA plans were scored as usable as-is in 44% (with minor edits 91%). For whole-brain treatment, RPA plans were scored as usable as-is in 67% (with minor edits 99%). For head/neck cancer, the normal tissue autocontours were acceptable as-is in 89% (with minor edits 97%). The clinical target volumes (CTVs) were acceptable as-is in 40% (with minor edits 93%). The volumetric-modulated arc therapy (VMAT) plans were acceptable as-is in 87% (with minor edits 96%). For cervical cancer, the normal tissue autocontours were acceptable as-is in 92% (with minor edits 99%). The CTVs for cervical cancer were scored as acceptable as-is in 83% (with minor edits 92%). The VMAT plans for cervical cancer were acceptable as-is in 99% (with minor edits 100%). CONCLUSION The RPA, a web-based tool designed to improve access to high-quality RT in low-resource settings, has high rates of clinical acceptability by practicing clinicians around the world. It has significant potential for successful implementation in low-resource clinics.
Collapse
Affiliation(s)
| | - Ajay Aggarwal
- Guy's and St Thomas Hospitals, London, United Kingdom
| | - Anuja Jhingran
- University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | | | | | | | | | | | - Lifei Zhang
- University of Texas MD Anderson Cancer Center, Houston, TX
| | | |
Collapse
|
2
|
Hendriks P, van Dijk KM, Boekestijn B, Broersen A, van Duijn-de Vreugd JJ, Coenraad MJ, Tushuizen ME, van Erkel AR, van der Meer RW, van Rijswijk CS, Dijkstra J, de Geus-Oei LF, Burgmans MC. Intraprocedural assessment of ablation margins using computed tomography co-registration in hepatocellular carcinoma treatment with percutaneous ablation: IAMCOMPLETE study. Diagn Interv Imaging 2024; 105:57-64. [PMID: 37517969 DOI: 10.1016/j.diii.2023.07.002] [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: 03/27/2023] [Revised: 06/20/2023] [Accepted: 07/18/2023] [Indexed: 08/01/2023]
Abstract
PURPOSE The primary objective of this study was to determine the feasibility of ablation margin quantification using a standardized scanning protocol during thermal ablation (TA) of hepatocellular carcinoma (HCC), and a rigid registration algorithm. Secondary objectives were to determine the inter- and intra-observer variability of tumor segmentation and quantification of the minimal ablation margin (MAM). MATERIALS AND METHODS Twenty patients who underwent thermal ablation for HCC were included. There were thirteen men and seven women with a mean age of 67.1 ± 10.8 (standard deviation [SD]) years (age range: 49.1-81.1 years). All patients underwent contrast-enhanced computed tomography examination under general anesthesia directly before and after TA, with preoxygenated breath hold. Contrast-enhanced computed tomography examinations were analyzed by radiologists using rigid registration software. Registration was deemed feasible when accurate rigid co-registration could be obtained. Inter- and intra-observer rates of tumor segmentation and MAM quantification were calculated. MAM values were correlated with local tumor progression (LTP) after one year of follow-up. RESULTS Co-registration of pre- and post-ablation images was feasible in 16 out of 20 patients (80%) and 26 out of 31 tumors (84%). Mean Dice similarity coefficient for inter- and intra-observer variability of tumor segmentation were 0.815 and 0.830, respectively. Mean MAM was 0.63 ± 3.589 (SD) mm (range: -6.26-6.65 mm). LTP occurred in four out of 20 patients (20%). The mean MAM value for patients who developed LTP was -4.00 mm, as compared to 0.727 mm for patients who did not develop LTP. CONCLUSION Ablation margin quantification is feasible using a standardized contrast-enhanced computed tomography protocol. Interpretation of MAM was hampered by the occurrence of tissue shrinkage during TA. Further validation in a larger cohort should lead to meaningful cut-off values for technical success of TA.
Collapse
Affiliation(s)
- Pim Hendriks
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands.
| | - Kiki M van Dijk
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands
| | - Bas Boekestijn
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands
| | - Alexander Broersen
- LKEB Laboratory of Clinical and Experimental Imaging, Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands
| | | | - Minneke J Coenraad
- Department of Gastroenterology and Hepatology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Maarten E Tushuizen
- Department of Gastroenterology and Hepatology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Arian R van Erkel
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands
| | - Rutger W van der Meer
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands
| | | | - Jouke Dijkstra
- LKEB Laboratory of Clinical and Experimental Imaging, Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands
| | - Lioe-Fee de Geus-Oei
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands; Biomedical Photonic Imaging Group, TechMed Centre, University of Twente, 7522 NB, Enschede, the Netherlands; Department of Radiation Science & Technology, Delft University of Technology, 2628 CD, Delft, the Netherlands
| | - Mark C Burgmans
- Department of Radiology, Leiden University Medical Center, 2333 ZA, Leiden, the Netherlands
| |
Collapse
|
3
|
Nagami N, Arimura H, Nojiri J, Yunhao C, Ninomiya K, Ogata M, Oishi M, Ohira K, Kitamura S, Irie H. Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images. Phys Eng Sci Med 2023; 46:83-97. [PMID: 36469246 DOI: 10.1007/s13246-022-01202-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022]
Abstract
The aim of this study was to develop dual segmentation models for poorly and well-differentiated hepatocellular carcinoma (HCC), using two-step transfer learning (TSTL) based on dynamic contrast-enhanced (DCE) computed tomography (CT) images. From 2013 to 2019, DCE-CT images of 128 patients with 80 poorly differentiated and 48 well-differentiated HCCs were selected at our hospital. In the first transfer learning (TL) step, a pre-trained segmentation model with 192 CT images of lung cancer patients was retrained as a poorly differentiated HCC model. In the second TL step, a well-differentiated HCC model was built from a poorly differentiated HCC model. The average three-dimensional Dice's similarity coefficient (3D-DSC) and 95th-percentile of the Hausdorff distance (95% HD) were mainly employed to evaluate the segmentation accuracy, based on a nested fourfold cross-validation test. The DSC denotes the degree of regional similarity between the HCC reference regions and the regions estimated using the proposed models. The 95% HD is defined as the 95th-percentile of the maximum measures of how far two subsets of a metric space are from each other. The average 3D-DSC and 95% HD were 0.849 ± 0.078 and 1.98 ± 0.71 mm, respectively, for poorly differentiated HCC regions, and 0.811 ± 0.089 and 2.01 ± 0.84 mm, respectively, for well-differentiated HCC regions. The average 3D-DSC for both regions was 1.2 times superior to that calculated without the TSTL. The proposed model using TSTL from the lung cancer dataset showed the potential to segment poorly and well-differentiated HCC regions on DCE-CT images.
Collapse
Affiliation(s)
- Noriyuki Nagami
- Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-Ku, Fukuoka City, Fukuoka, 812-8582, Japan
- Department of Radiology, Saga University Hospital, 5-1-1, Nabeshima, Saga City, Saga, 849-8501, Japan
| | - Hidetaka Arimura
- Division of Medical Quantum Science, Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-Ku, Fukuoka City, Fukuoka, 812-8582, Japan.
| | - Junichi Nojiri
- Medical Corporation Kouhoukai, Takagi Hospital, 141-11, Sakemi, Okawa City, Fukuoka, 831-0016, Japan
- Department of Radiology, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, Saga City , Saga, 849-8501, Japan
| | - Cui Yunhao
- Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-Ku, Fukuoka City, Fukuoka, 812-8582, Japan
| | - Kenta Ninomiya
- Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-Ku, Fukuoka City, Fukuoka, 812-8582, Japan
| | - Manabu Ogata
- Department of Radiology, Saga University Hospital, 5-1-1, Nabeshima, Saga City, Saga, 849-8501, Japan
| | - Mitsutoshi Oishi
- Department of Radiology, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, Saga City , Saga, 849-8501, Japan
| | - Keiichi Ohira
- Department of Radiology, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, Saga City , Saga, 849-8501, Japan
| | - Shigetoshi Kitamura
- Department of Radiology, Saga University Hospital, 5-1-1, Nabeshima, Saga City, Saga, 849-8501, Japan
| | - Hiroyuki Irie
- Department of Radiology, Faculty of Medicine, Saga University, 5-1-1, Nabeshima, Saga City , Saga, 849-8501, Japan
| |
Collapse
|
4
|
Xiao X, Zhao J, Li S. Task relevance driven adversarial learning for simultaneous detection, size grading, and quantification of hepatocellular carcinoma via integrating multi-modality MRI. Med Image Anal 2022; 81:102554. [DOI: 10.1016/j.media.2022.102554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 07/12/2022] [Accepted: 07/18/2022] [Indexed: 11/26/2022]
|
5
|
Duan J, Qiu Q, Zhu J, Shang D, Dou X, Sun T, Yin Y, Meng X. Reproducibility for Hepatocellular Carcinoma CT Radiomic Features: Influence of Delineation Variability Based on 3D-CT, 4D-CT and Multiple-Parameter MR Images. Front Oncol 2022; 12:881931. [PMID: 35494061 PMCID: PMC9047864 DOI: 10.3389/fonc.2022.881931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 03/21/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose Accurate lesion segmentation is a prerequisite for radiomic feature extraction. It helps to reduce the features variability so as to improve the reporting quality of radiomics study. In this research, we aimed to conduct a radiomic feature reproducibility test of inter-/intra-observer delineation variability in hepatocellular carcinoma using 3D-CT images, 4D-CT images and multiple-parameter MR images. Materials and Methods For this retrospective study, 19 HCC patients undergoing 3D-CT, 4D-CT and multiple-parameter MR scans were included in this study. The gross tumor volume (GTV) was independently delineated twice by two observers based on contrast-enhanced computed tomography (CECT), maximum intensity projection (MIP), LAVA-Flex, T2W FRFSE and DWI-EPI images. We also delineated the peritumoral region, which was defined as 0 to 5 mm radius surrounding the GTV. 107 radiomic features were automatically extracted from CECT images using 3D-Slicer software. Quartile coefficient of dispersion (QCD) and intraclass correlation coefficient (ICC) were applied to assess the variability of each radiomic feature. QCD<10% and ICC≥0.75 were considered small variations and excellent reliability. Finally, the principal component analysis (PCA) was used to test the feasibility of dimensionality reduction. Results For tumor tissues, the numbers of radiomic features with QCD<10% indicated no obvious inter-/intra-observer differences or discrepancies in 3D-CT, 4D-CT and multiple-parameter MR delineation. However, the number of radiomic features (mean 89) with ICC≥0.75 was the highest in the multiple-parameter MR group, followed by the 3DCT group (mean 77) and the MIP group (mean 73). The peritumor tissues also showed similar results. A total of 15 and 7 radiomic features presented excellent reproducibility and small variation in tumor and peritumoral tissues, respectively. Two robust features showed excellent reproducibility and small variation in tumor and peritumoral tissues. In addition, the values of the two features both represented statistically significant differences among tumor and peritumoral tissues (P<0.05). The PCA results indicated that the first seven principal components could preserve at least 90% of the variance of the original set of features. Conclusion Delineation on multiple-parameter MR images could help to improve the reproducibility of the HCC CT radiomic features and weaken the inter-/intra-observer influence.
Collapse
Affiliation(s)
- Jinghao Duan
- School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, China
- Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Qingtao Qiu
- Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jian Zhu
- Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Dongping Shang
- Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xue Dou
- Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Tao Sun
- Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Yong Yin
- Department of Radiotherapy, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xiangjuan Meng
- Department of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, Jinan, China
- *Correspondence: Xiangjuan Meng,
| |
Collapse
|
6
|
A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems. Int J Biomed Imaging 2019; 2019:1464592. [PMID: 31582963 PMCID: PMC6748179 DOI: 10.1155/2019/1464592] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 05/15/2019] [Accepted: 06/26/2019] [Indexed: 11/17/2022] Open
Abstract
For complex segmentation tasks, the achievable accuracy of fully automated systems is inherently limited. Specifically, when a precise segmentation result is desired for a small amount of given data sets, semi-automatic methods exhibit a clear benefit for the user. The optimization of human computer interaction (HCI) is an essential part of interactive image segmentation. Nevertheless, publications introducing novel interactive segmentation systems (ISS) often lack an objective comparison of HCI aspects. It is demonstrated that even when the underlying segmentation algorithm is the same throughout interactive prototypes, their user experience may vary substantially. As a result, users prefer simple interfaces as well as a considerable degree of freedom to control each iterative step of the segmentation. In this article, an objective method for the comparison of ISS is proposed, based on extensive user studies. A summative qualitative content analysis is conducted via abstraction of visual and verbal feedback given by the participants. A direct assessment of the segmentation system is executed by the users via the system usability scale (SUS) and AttrakDiff-2 questionnaires. Furthermore, an approximation of the findings regarding usability aspects in those studies is introduced, conducted solely from the system-measurable user actions during their usage of interactive segmentation prototypes. The prediction of all questionnaire results has an average relative error of 8.9%, which is close to the expected precision of the questionnaire results themselves. This automated evaluation scheme may significantly reduce the resources necessary to investigate each variation of a prototype's user interface (UI) features and segmentation methodologies.
Collapse
|
7
|
Successful integration of radiation oncology in preclinical medical education : Experiences with an interdisciplinary training project. Strahlenther Onkol 2019; 195:1104-1109. [PMID: 31309265 DOI: 10.1007/s00066-019-01492-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Accepted: 06/27/2019] [Indexed: 01/20/2023]
Abstract
PURPOSE Modern impartation of both anatomic and radiation oncology (RO) knowledge in medical education enables a transfer of preclinical knowledge to clinical practice, which may be addressed by multidisciplinary concepts. The faculty's "Anatomy and imaging" course attempts to integrate RO, radiology and nuclear medicine into the preclinical curriculum. The present analysis focuses on the description of the course concept and discusses the potential didactic impact of the implementation of RO. METHODS In total 5 semester cohorts have undertaken the course since the introduction of RO in the winter semester of 2015/2016 with 682 students participating. It is designed as a small group circuit training with a teaching content of 8 h daily. Course evaluation was performed on a 100-item Likert scale. RESULTS General evaluation showed an average of 9.3-12.7 on a Likert scale (0 being the best, 100 being the worst grade). Use of media, relevance for medical training, gain of interest in medicine in general and overall satisfaction with the course received excellent mean values. For RO, there was a high degree of consent with the following statements: "the course was well organized", "subjects and presentation were well-structured", "topics were well chosen", "the time for exercises was sufficient" and "teaching by student tutors and physicians was adequate". CONCLUSION The present evaluation demonstrates the feasibility of introducing RO in the preclinical part of medical education. The course concept shows excellent results in evaluation and may help in broadening RO knowledge and in recruiting new doctoral candidates and residents.
Collapse
|
8
|
Kristensen I, Nilsson K, Agrup M, Belfrage K, Embring A, Haugen H, Svärd AM, Knöös T, Nilsson P. A dose based approach for evaluation of inter-observer variations in target delineation. Tech Innov Patient Support Radiat Oncol 2017; 3-4:41-47. [PMID: 32095566 PMCID: PMC7033785 DOI: 10.1016/j.tipsro.2017.10.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 10/06/2017] [Accepted: 10/09/2017] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND AND PURPOSE Substantial inter-observer variations in target delineation have been presented previously. Target delineation for paediatric cases is difficult due to the small number of children, the variation in paediatric targets, the number of study protocols, and the individual patient's specific needs and demands. Uncertainties in target delineation might lead to under-dosage or over-dosage. The aim of this work is to apply the concept of a consensus volume and good quality treatment plans to visualise and quantify inter-observer target delineation variations in dosimetric terms in addition to conventional geometrically based volume concordance indices. MATERIAL AND METHODS Two paediatric cases were used to demonstrate the potential of adding dose metrics when evaluating target delineation diversity; Hodgkin's disease (case 1) and rhabdomyosarcoma of the parotid gland (case 2). The variability in target delineation (PTV delineations) between six centres was quantified using the generalised conformity index, CIgen, generated for volume overlap. The STAPLE algorithm, as implemented in CERR, was used for both cases to derive a consensus volumes. STAPLE is a probabilistic estimate of the true volume generated from all observers. Dose distributions created by each centre for the original target volumes were then applied to this consensus volume. RESULTS A considerable variation in target segmentation was seen in both cases. For case 1 the variation was 374-960 cm3 (average 669 cm3) and for case 2; 65-126 cm3 (average 109 cm3). CIgen were 0.53 and 0.70, respectively. The DVHs in absolute volume displayed for the delineated target volume as well as for the consensus volume adds information on both "compliant" target volumes as well as outliers which are hidden with just the use of concordance indices. CONCLUSIONS The DVHs in absolute volume add valuable and easily understood information to various indices for evaluating uniformity in target delineation.
Collapse
Affiliation(s)
- Ingrid Kristensen
- Department of Oncology, Clinical Sciences, Lund University, Lund, Sweden
- Department of Haematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Kristina Nilsson
- Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology, Clinical Oncology, Uppsala University Hospital, Uppsala, Sweden
| | - Måns Agrup
- Department of Oncology, Linköping University Hospital, Linköping, Sweden
| | - Karin Belfrage
- Department of Haematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Anna Embring
- Department of Oncology, Karolinska University Hospital, Stockholm, Sweden
| | - Hedda Haugen
- Department of Oncology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anna-Maja Svärd
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Tommy Knöös
- Department of Haematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Department of Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden
| | - Per Nilsson
- Department of Haematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Department of Medical Radiation Physics, Clinical Sciences, Lund University, Lund, Sweden
| |
Collapse
|
9
|
Lacornerie T, Rio E, Mahé MA. [Stereotactic body radiation therapy for hepatic malignancies: Organs at risk, uncertainties margins, doses]. Cancer Radiother 2017; 21:574-579. [PMID: 28844506 DOI: 10.1016/j.canrad.2017.07.028] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Revised: 07/20/2017] [Accepted: 07/22/2017] [Indexed: 11/30/2022]
Abstract
Stereotactic body radiation therapy for primary and metastatic hepatic malignancies can be performed in association and/or as an alternative to surgery and radiofrequency. The consequences of the great number of techniques available are heterogeneity in contouring, dose prescription and in determination of dose constraints for organs at risk. The objective of this paper is to improve the quality and safety and to help the diffusion of this technique for a majority of patients. In 2016, the French Society of Radiation Oncology (SFRO) published guidelines for external radiotherapy and brachytherapy ("Recorad"). This paper is an update of these recommendations considering recent publications.
Collapse
Affiliation(s)
- T Lacornerie
- Service de physique médicale, centre Oscar-Lambret, 3, rue Frédéric-Combemale, 59020 Lille, France.
| | - E Rio
- Service de radiothérapie, institut de cancérologie de l'Ouest René-Gauducheau, boulevard Professeur-Jacques-Monod, 44805 Saint-Herblain, France
| | - M-A Mahé
- Service de radiothérapie, institut de cancérologie de l'Ouest René-Gauducheau, boulevard Professeur-Jacques-Monod, 44805 Saint-Herblain, France
| |
Collapse
|
10
|
Gkika E, Tanadini-Lang S, Kirste S, Holzner PA, Neeff HP, Rischke HC, Reese T, Lohaus F, Duma MN, Dieckmann K, Semrau R, Stockinger M, Imhoff D, Kremers N, Häfner MF, Andratschke N, Nestle U, Grosu AL, Guckenberger M, Brunner TB. Interobserver variability in target volume delineation of hepatocellular carcinoma. Strahlenther Onkol 2017; 193:823-830. [DOI: 10.1007/s00066-017-1177-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2017] [Accepted: 06/22/2017] [Indexed: 12/22/2022]
|
11
|
Aklan B, Hartmann J, Zink D, Siavooshhaghighi H, Merten R, Putz F, Ott O, Fietkau R, Bert C. Regional deep hyperthermia: impact of observer variability in CT-based manual tissue segmentation on simulated temperature distribution. Phys Med Biol 2017; 62:4479-4495. [PMID: 28480870 DOI: 10.1088/1361-6560/aa685b] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The aim of this study was to systematically investigate the influence of the inter- and intra-observer segmentation variation of tumors and organs at risk on the simulated temperature coverage of the target. CT scans of six patients with tumors in the pelvic region acquired for radiotherapy treatment planning were used for hyperthermia treatment planning. To study the effect of inter-observer variation, three observers manually segmented in the CT images of each patient the following structures: fat, muscle, bone and the bladder. The gross tumor volumes (GTV) were contoured by three radiation oncology residents and used as the hyperthermia target volumes. For intra-observer variation, one of the observers of each group contoured the structures of each patient three times with a time span of one week between the segmentations. Moreover, the impact of segmentation variations in organs at risk (OARs) between the three inter-observers was investigated on simulated temperature distributions using only one GTV. The spatial overlap between individual segmentations was assessed by the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Additionally, the temperatures T90/T10 delivered to 90%/10% of the GTV, respectively, were assessed for each observer combination. The results of the segmentation similarity evaluation showed that the DSC of the inter-observer variation of fat, muscle, the bladder, bone and the target was 0.68 ± 0.12, 0.88 ± 0.05, 0.73 ± 0.14, 0.91 ± 0.04 and 0.64 ± 0.11, respectively. Similar results were found for the intra-observer variation. The MSD results were similar to the DSCs for both observer variations. A statistically significant difference (p < 0.05) was found for T90 and T10 in the predicted target temperature due to the observer variability. The conclusion is that intra- and inter-observer variations have a significant impact on the temperature coverage of the target. Furthermore, OARs, such as bone and the bladder, may essentially influence the homogeneity of the simulated target temperature distribution.
Collapse
Affiliation(s)
- Bassim Aklan
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | | | | | | | | | | | | | | | | |
Collapse
|