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Journal articles on the topic 'Target delineation variability'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Kriwanek, Florian, Leo Ulbrich, Wolfgang Lechner, Carola Lütgendorf-Caucig, Stefan Konrad, Cora Waldstein, Harald Herrmann, et al. "Impact of SSTR PET on Inter-Observer Variability of Target Delineation of Meningioma and the Possibility of Using Threshold-Based Segmentations in Radiation Oncology." Cancers 14, no. 18 (September 13, 2022): 4435. http://dx.doi.org/10.3390/cancers14184435.

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Aim: The aim of this study was to assess the effects of including somatostatin receptor agonist (SSTR) PET imaging in meningioma radiotherapy planning by means of changes in inter-observer variability (IOV). Further, the possibility of using threshold-based delineation approaches for semiautomatic tumor volume definition was assessed. Patients and Methods: Sixteen patients with meningioma undergoing fractionated radiotherapy were delineated by five radiation oncologists. IOV was calculated by comparing each delineation to a consensus delineation, based on the simultaneous truth and performance level estimation (STAPLE) algorithm. The consensus delineation was used to adapt a threshold-based delineation, based on a maximization of the mean Dice coefficient. To test the threshold-based approach, seven patients with SSTR-positive meningioma were additionally evaluated as a validation group. Results: The average Dice coefficients for delineations based on MRI alone was 0.84 ± 0.12. For delineation based on MRI + PET, a significantly higher dice coefficient of 0.87 ± 0.08 was found (p < 0.001). The Hausdorff distance decreased from 10.96 ± 11.98 mm to 8.83 ± 12.21 mm (p < 0.001) when adding PET for the lesion delineation. The best threshold value for a threshold-based delineation was found to be 14.0% of the SUVmax, with an average Dice coefficient of 0.50 ± 0.19 compared to the consensus delineation. In the validation cohort, a Dice coefficient of 0.56 ± 0.29 and a Hausdorff coefficient of 27.15 ± 21.54 mm were found for the threshold-based approach. Conclusions: SSTR-PET added to standard imaging with CT and MRI reduces the IOV in radiotherapy planning for patients with meningioma. When using a threshold-based approach for PET-based delineation of meningioma, a relatively low threshold of 14.0% of the SUVmax was found to provide the best agreement with a consensus delineation.

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2

Gkika, E., S. Tanadini-Lang, S. Kirste, P. A. Holzner, H. P. Neeff, H. C. Rischke, T. Reese, et al. "Interobserver variability in target volume delineation of hepatocellular carcinoma." Strahlentherapie und Onkologie 193, no. 10 (July 10, 2017): 823–30. http://dx.doi.org/10.1007/s00066-017-1177-y.

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3

Segedin, Barbara, and Primoz Petric. "Uncertainties in target volume delineation in radiotherapy – are they relevant and what can we do about them?" Radiology and Oncology 50, no. 3 (September 1, 2016): 254–62. http://dx.doi.org/10.1515/raon-2016-0023.

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Abstract Background Modern radiotherapy techniques enable delivery of high doses to the target volume without escalating dose to organs at risk, offering the possibility of better local control while preserving good quality of life. Uncertainties in target volume delineation have been demonstrated for most tumour sites, and various studies indicate that inconsistencies in target volume delineation may be larger than errors in all other steps of the treatment planning and delivery process. The aim of this paper is to summarize the degree of delineation uncertainties for different tumour sites reported in the literature and review the effect of strategies to minimize them. Conclusions Our review confirmed that interobserver variability in target volume contouring represents the largest uncertainty in the process for most tumour sites, potentially resulting in a systematic error in dose delivery, which could influence local control in individual patients. For most tumour sites the optimal combination of imaging modalities for target delineation still needs to be determined. Strict use of delineation guidelines and protocols is advisable both in every day clinical practice and in clinical studies to diminish interobserver variability. Continuing medical education of radiation oncologists cannot be overemphasized, intensive formal training on interpretation of sectional imaging should be included in the program for radiation oncology residents.

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4

Onal, C., O. C. Guler, Y. Dolek, and M. Cengiz. "The Role of Delineation Courses for Improving Observer Variability in Target Delineation for Gastric Cancer." International Journal of Radiation Oncology*Biology*Physics 93, no. 3 (November 2015): E170. http://dx.doi.org/10.1016/j.ijrobp.2015.07.985.

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5

Hurkmans, Coen W., Jacques H. Borger, Bradley R. Pieters, Nicola S. Russell, Edwin P. M. Jansen, and Ben J. Mijnheer. "Variability in target volume delineation on CT scans of the breast." International Journal of Radiation Oncology*Biology*Physics 50, no. 5 (August 2001): 1366–72. http://dx.doi.org/10.1016/s0360-3016(01)01635-2.

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6

Gkika, E., S. Tandini-Lang, S. Kirste, P. Holzner, H. P. Neeff, H. C. Rischke, T. Reese, et al. "EP-1253: Interobserver variability in the target delineation of hepatocellular carcinoma." Radiotherapy and Oncology 123 (May 2017): S674. http://dx.doi.org/10.1016/s0167-8140(17)31688-2.

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7

Genovesi, D., G. Ausili Cèfaro, M. Trignani, A. Vinciguerra, A. Augurio, M. Di Tommaso, F. Perrotti, et al. "Interobserver variability of clinical target volume delineation in soft-tissue sarcomas." Cancer/Radiothérapie 18, no. 2 (March 2014): 89–96. http://dx.doi.org/10.1016/j.canrad.2013.11.011.

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8

Onal, Cem, Mustafa Cengiz, Ozan C. Guler, Yemliha Dolek, and Serdar Ozkok. "The role of delineation education programs for improving interobserver variability in target volume delineation in gastric cancer." British Journal of Radiology 90, no. 1073 (May 2017): 20160826. http://dx.doi.org/10.1259/bjr.20160826.

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9

Eminowicz, Gemma, and Mary McCormack. "Variability of clinical target volume delineation for definitive radiotherapy in cervix cancer." Radiotherapy and Oncology 117, no. 3 (December 2015): 542–47. http://dx.doi.org/10.1016/j.radonc.2015.10.007.

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10

van der Veen, Julie, Akos Gulyban, and Sandra Nuyts. "Interobserver variability in delineation of target volumes in head and neck cancer." Radiotherapy and Oncology 137 (August 2019): 9–15. http://dx.doi.org/10.1016/j.radonc.2019.04.006.

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11

Genovesi, Domenico, Giampiero Ausili Cèfaro, Annamaria Vinciguerra, Antonietta Augurio, Monica Di Tommaso, Rita Marchese, Umberto Ricardi, et al. "Interobserver variability of clinical target volume delineation in supra-diaphragmatic Hodgkin’s disease." Strahlentherapie und Onkologie 187, no. 6 (May 16, 2011): 357–66. http://dx.doi.org/10.1007/s00066-011-2221-y.

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12

Sandström, Helena, Hidefumi Jokura, Caroline Chung, and Iuliana Toma-Dasu. "Multi-institutional study of the variability in target delineation for six targets commonly treated with radiosurgery." Acta Oncologica 57, no. 11 (May 22, 2018): 1515–20. http://dx.doi.org/10.1080/0284186x.2018.1473636.

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13

Chilukuri, S., S. Surana, P. P. Mohanty, and R. Kuppuswamy. "Impact of interobserver variability in delineating clinical target volumes (CTV) for head and neck intensity modulated radiation therapy (IMRT): Potential for a geographical miss." Journal of Clinical Oncology 27, no. 15_suppl (May 20, 2009): e17013-e17013. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.e17013.

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e17013 Background: Despite modern day imaging techniques and guidelines for delineation of the clinical target volume, there remains significant inter-observer variability in delineating the CTV. With the use of IMRT, the target volume receives a significant tumoricidal dose while the regions just outside the target receive unpredictable doses. In this report, the dose to the region just outside the planning target volume (PTV) (defined as volume of uncertainty [VOU]), presumed to represent the regions subject to maximum inter-observer variability, was studied. Methods: The IMRT plans of 12 patients with head and neck cancer were used to determine the dose just outside the high-risk CTV by growing volumes around CTV with 3 mm, 5 mm, and 7 mm margins. These volumes were edited at regions close to skin/air and bone. PTVs were subsequently grown using the same margins as used in the original plans. With the Boolean operations, each of these volumes was subtracted from the existing PTV to generate the volumes of uncertainty (VOU) in 3 dimensions. The dose to these VOUs was analyzed. D95, D90 and median dose which are the doses received by 95%, 90%, and 50% of the target volume respectively were studied. Results: The median prescribed dose was 68 Gy (60 Gy-72 Gy). The median percentage D95 for 3mm, 5mm and 7mm VOU was 82.5% ± 4.95, 77.25% ± 5.53, and 69% ± 6.93, respectively. The median percentage D90 for these VOU's was 87.7% ± 3.53, 83.2% ± 4.61, and 79% ± 4.5, respectively. The median dose to each of these VOU”s was 96% ± 1.6, 94.5% ± 1.95, and 92.5% ± 1.85 respectively. Conclusions: This study documents that the volumes of uncertainty surrounding the PTV, which could contain subclinical disease, in fact receive a significant amount of RT dose. Hence, despite a large amount of evidence for inter-observer variability in target delineation for head and neck cancer,the majority of locoregional recurrences are within the high dose region and not marginal failures. No significant financial relationships to disclose.

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14

Sritharan, K., H. Akhiat, D. Cahill, S. L. Choi, A. Choudhury, P. Chung, J. Diaz, et al. "PD-0571 Determining interobserver variability in prostate bed CTV target delineation using MRI." Radiotherapy and Oncology 170 (May 2022): S500—S501. http://dx.doi.org/10.1016/s0167-8140(22)02886-9.

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15

Maunu A. Pitkänen, Kaija A. Holli,. "Quality Assurance in Radiotherapy of Breast Cancer Variability in Planning Target Volume Delineation." Acta Oncologica 40, no. 1 (January 2001): 50–55. http://dx.doi.org/10.1080/028418601750071055.

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16

Piva, Cristina, Domenico Genovesi, Andrea Riccardo Filippi, Mario Balducci, Salvina Barra, Michela Buglione, Mario Busetto, et al. "Interobserver variability in clinical target volume delineation for primary mediastinal B-cell lymphoma." Practical Radiation Oncology 5, no. 6 (November 2015): 383–89. http://dx.doi.org/10.1016/j.prro.2015.04.003.

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17

Christensen, Neil I., Lisa J. Forrest, Pamela J. White, Margaret Henzler, and Michelle M. Turek. "SINGLE INSTITUTION VARIABILITY IN INTENSITY MODULATED RADIATION TARGET DELINEATION FOR CANINE NASAL NEOPLASIA." Veterinary Radiology & Ultrasound 57, no. 6 (July 28, 2016): 639–45. http://dx.doi.org/10.1111/vru.12398.

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18

Koo, Taeryool, Kwang-Ho Cheong, Kyubo Kim, Hae Jin Park, Younghee Park, Hyeon Kang Koh, Byoung Hyuck Kim, Eunji Kim, Kyung Su Kim, and Jin Hwa Choi. "Variation in clinical target volume delineation in postoperative radiotherapy for biliary tract cancer." PLOS ONE 17, no. 9 (September 1, 2022): e0273395. http://dx.doi.org/10.1371/journal.pone.0273395.

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We aimed to evaluate the inter-clinician variability in the clinical target volume (CTV) for postoperative radiotherapy (PORT) for biliary tract cancer (BTC) including extrahepatic bile duct cancer (EBDC) and gallbladder cancer (GBC). Nine experienced radiation oncologists delineated PORT CTVs for distal EBDC (pT2N1), proximal EBDC (pT2bN1) and GBC (pT2bN1) patients. The expectation maximization algorithm for Simultaneous Truth and Performance Level Estimation (STAPLE) was used to quantify expert agreements. We generated volumes with a confidence level of 80% to compare the maximum distance to each CTV in six directions. The degree of agreement was moderate; overall kappa values were 0.573 for distal EBDC, 0.513 for proximal EBDC, and 0.511 for GBC. In the distal EBDC, a larger variation was noted in the right, post, and inferior direction. In the proximal EBDC, all borders except the right and left direction showed a larger variation. In the GBC, a larger variation was found in the anterior, posterior, and inferior direction. The posterior and inferior borders were the common area having discrepancies, associated with the insufficient coverage of the paraaortic node. A consensus guideline is needed to reduce inter-clinician variability in the CTVs and adequate coverage of regional lymph node area.

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19

Klaassen, L., M. Jaarsma-Coes, B. Verbist, K. Vu, Y. Klaver, M. Rodrigues, T. Ferreira, et al. "MO-0211 Inter-observer variability in MR-based target volume delineation of uveal melanoma." Radiotherapy and Oncology 170 (May 2022): S166—S167. http://dx.doi.org/10.1016/s0167-8140(22)02313-1.

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20

Di Biase, S., F. Patani, D. Fasciolo, C. Rosa, C. Di Carlo, A. Allajbej, L. Gasparini, et al. "EP-1238 Inter-observer variability in target delineation for brain metastases in stereotactic radiotherapy." Radiotherapy and Oncology 133 (April 2019): S682. http://dx.doi.org/10.1016/s0167-8140(19)31658-5.

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21

Fyles, A. W., K. Lim, W. Small, L. Portelance, D. Gaffney, B. Erickson, J. de los Santos, S. Ishikura, C. Creutzberg, and W. Bosch. "Variability in Delineation of Clinical Target Volumes for Cervix Cancer Intensity-modulated Pelvic Radiotherapy." International Journal of Radiation Oncology*Biology*Physics 75, no. 3 (November 2009): S83—S84. http://dx.doi.org/10.1016/j.ijrobp.2009.07.208.

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22

Patel, Deep A., Stephanie T. Chang, Karyn A. Goodman, Andrew Quon, Brian Thorndyke, Sanjiv S. Gambhir, Alex McMillan, Billy W. Loo, and Albert C. Koong. "Impact of Integrated PET/CT on Variability of Target Volume Delineation in Rectal Cancer." Technology in Cancer Research & Treatment 6, no. 1 (February 2007): 31–36. http://dx.doi.org/10.1177/153303460700600105.

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23

Borghero, Y., T. Guerrero, J. Noyola-Martinez, J. Cox, C. Stevens, Z. Liao, M. Jeter, J. Chang, K. Sanders, and R. Komaki. "Interobserver Variability in Non-Small Cell Lung Cancer Target Delineation Among Thoracic Radiation Oncologists." International Journal of Radiation Oncology*Biology*Physics 63 (October 2005): S405—S406. http://dx.doi.org/10.1016/j.ijrobp.2005.07.691.

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24

Kim, Y. S., J. Joo, E. Choi, and S. LEE. "EP-1831: Inter-physician variability in delineation of clinical target volume of uterine cervical carcinoma." Radiotherapy and Oncology 119 (April 2016): S859—S860. http://dx.doi.org/10.1016/s0167-8140(16)33082-1.

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25

Lakosi, F., L. Janvary, J. Vanderick, N. Lombard, M. Meyns, L. Seidel, P. Vavassis, M. Untereiner, and P. Coucke. "Variability of Whole Breast Target Volume Delineation Between Prone and Supine Position: A Multicentric Study." International Journal of Radiation Oncology*Biology*Physics 84, no. 3 (November 2012): S252. http://dx.doi.org/10.1016/j.ijrobp.2012.07.655.

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26

Bouilhol, G., A. Arnaud, J. Lesseur, M. Ayadi, D. Sarrut, and L. Claude. "Interobserver Variability in NSCLC Target Delineation for Stereotactic Body Radiation Therapy: A Four-dimensional Analysis." International Journal of Radiation Oncology*Biology*Physics 78, no. 3 (November 2010): S790. http://dx.doi.org/10.1016/j.ijrobp.2010.07.1830.

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27

Alsherif, Wessam A., and Ranya M. Mousa. "Variability of Medial and Lateral Borders Delineation in Guidelines for Post-Mastectomy Irradiation Significantly Affects Radiation Dose Received by Left Lung and Heart." Tumori Journal 106, no. 1_suppl (April 2020): 10. http://dx.doi.org/10.1177/0300891620914130.

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Background: Delineation of Clinical Target Volume (CTV) is a basic step in 3 Dimensional Conformal (3DCRT). A notable variation however exists among different guidelines in delineation of chest wall (CW) CTV specially for the lateral margin. Some authors used wire localization for the anatomical insertion of the presumed breast It is expected that lateral margin delineation will affect the standard tangential fields and therefore the ipsilateral lung & heart (in left side) volumes irradiated to high dose. Aim of work: Evaluation of the effect of using various guidelines for chest wall CTV delineation on outcome regarding doses received by heart and left lung (in post left mastectomy irradiation) and compare these outcomes to that of wire based delineation (WBD). Methodology: Ten patients with T3/4 &/or N+ left breast cancer were planned for post mastectomy CW-3DCRT. Delineation of CW by one radiation oncologist followed 2 different guidelines namely RTOG & ESTRO in addition to a 3rd anatomical based wire delineation of chest wall underlying the presumed breast. Three CRT plans for the 3 CTVs were compared regarding coverage, homogenity & toxic dose to heart & lt. lung. Results: CTV was a highly significantly smaller when delineated using WBD vs RTOG or ESTRO guidelines. There was no statistically significant difference between the 3 delineated volumes regarding coverage & homogeneity parameters. A highly statistically significant better (lesser) V20Gy & V30Gy received by lt. lung for plans based on WBD (16.0 +/- 4.1% &12.75 +/- 2% respectively) vs those based on ESTRO (19.1 +/- 1.73 & 15.2 +/- 5.1 respectively) or RTOG guidelines (18.22 ± 1.6 & 14.52 ± 5.3 respectively), p=0.001 for V20Gy & 0.01 for V30Gy. For cardiac dose, a statistically significant lower D50% received by the heart in plans based on WBM delineation (101.6 ± 41.2 Gy) compared to plans based on ESTRO & RTOG guidelines based CTV (141 +/- 81cGy & 132 +/- 93 cGy respectively, p= 0-00001). Conclusion: WBD of post lt. mastectomy chest wall CTV delineation significantly reduced toxic dose received by heart & lt. lung. Larger trial with clinical follow up to test for being not inferior to ESMO &/or ESRTO guidelines based treatment regarding local recurrence.

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28

Altorjai, Gabriela, Irina Fotina, Carola Lütgendorf-Caucig, Markus Stock, Richard Pötter, Dietmar Georg, and Karin Dieckmann. "Cone-Beam CT-Based Delineation of Stereotactic Lung Targets: The Influence of Image Modality and Target Size on Interobserver Variability." International Journal of Radiation Oncology*Biology*Physics 82, no. 2 (February 2012): e265-e272. http://dx.doi.org/10.1016/j.ijrobp.2011.03.042.

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29

Joo, Ji Hyeon, Young Seok Kim, Byung Chul Cho, Chi Young Jeong, Won Park, Hak Jae Kim, Won Sup Yoon, et al. "Variability in target delineation of cervical carcinoma: A Korean radiation oncology group study (KROG 15-06)." PLOS ONE 12, no. 3 (March 16, 2017): e0173476. http://dx.doi.org/10.1371/journal.pone.0173476.

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30

Tiigi, K., R. Tiigi, I. Oro, M. Adamson, K. Kolk, and M. Põldveer. "EP-2356: Inter-observer variability in OAR and target volume delineation in curative prostate cancer patients." Radiotherapy and Oncology 127 (April 2018): S1232—S1233. http://dx.doi.org/10.1016/s0167-8140(18)32665-3.

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31

Peulen, Heike, José Belderbos, Matthias Guckenberger, Andrew Hope, Inga Grills, Marcel van Herk, and Jan-Jakob Sonke. "Target delineation variability and corresponding margins of peripheral early stage NSCLC treated with stereotactic body radiotherapy." Radiotherapy and Oncology 114, no. 3 (March 2015): 361–66. http://dx.doi.org/10.1016/j.radonc.2015.02.011.

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32

White, I., A. Hunt, T. Bird, S. Settatree, H. Soliman, and S. Bhide. "EP-1858 Inter-observer variability in rectal target delineation on MRI for MR image-guided radiotherapy." Radiotherapy and Oncology 133 (April 2019): S1009—S1010. http://dx.doi.org/10.1016/s0167-8140(19)32278-9.

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33

Moretones Agut, Cristina, David León, Arturo Navarro, Olalla Santacruz, Ana María Boladeras, Miquel Macià, María Cambray, Valentí Navarro, Ignasi Modolell, and Ferran Guedea. "Interobserver variability in target volume delineation in postoperative radiochemotherapy for gastric cancer. A pilot prospective study." Clinical and Translational Oncology 14, no. 2 (February 2012): 132–37. http://dx.doi.org/10.1007/s12094-012-0772-8.

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34

Dalah, Entesar, Ion Moraru, Eric Paulson, Beth Erickson, and X. Allen Li. "Variability of Target and Normal Structure Delineation Using Multimodality Imaging for Radiation Therapy of Pancreatic Cancer." International Journal of Radiation Oncology*Biology*Physics 89, no. 3 (July 2014): 633–40. http://dx.doi.org/10.1016/j.ijrobp.2014.02.035.

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35

Holliday, Emma, Clifton D. Fuller, Jayashree Kalpathy-Cramer, Daniel Gomez, Andreas Rimner, Ying Li, Suresh Senan, et al. "Quantitative assessment of target delineation variability for thymic cancers: agreement evaluation of a prospective segmentation challenge." Journal of Radiation Oncology 5, no. 1 (November 3, 2015): 55–61. http://dx.doi.org/10.1007/s13566-015-0230-7.

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36

Lim, K., A. Fyles, L. Portelance, C. Creutzberg, I. M. Jürgenliemk-Schulz, A. Viswanathan, B. Erickson, W. Bosch, I. El Naqa, and M. Varia. "Variability in Clinical Target Volume Delineation for Intensity Modulated Radiotherapy in Three Challenging Cervix Cancer Scenarios." International Journal of Radiation Oncology*Biology*Physics 78, no. 3 (November 2010): S121—S122. http://dx.doi.org/10.1016/j.ijrobp.2010.07.308.

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37

Foroudi, F., A. Haworth, A. Pangehel, J. Wong, P. Roxby, G. Duchesne, S. Williams, and KH Tai. "Inter-observer variability of clinical target volume delineation for bladder cancer using CT and cone beam CT." Journal of Medical Imaging and Radiation Oncology 53, no. 1 (February 2009): 100–106. http://dx.doi.org/10.1111/j.1754-9485.2009.02044.x.

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38

Van der Veen, J., A. Gulyban, and S. Nuyts. "PO-114 Variability in target volume delineation in Head and Neck cancer: Results of a national study." Radiotherapy and Oncology 132 (March 2019): 58–59. http://dx.doi.org/10.1016/s0167-8140(19)30280-4.

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39

Lim, Karen, Beth Erickson, Ina M. Jürgenliemk-Schulz, David Gaffney, Carien L. Creutzberg, Akila Viswanathan, Lorraine Portelance, et al. "Variability in clinical target volume delineation for intensity modulated radiation therapy in 3 challenging cervix cancer scenarios." Practical Radiation Oncology 5, no. 6 (November 2015): e557-e565. http://dx.doi.org/10.1016/j.prro.2015.06.011.

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40

Walker, J. J., M. A. Henderson, A. J. Fakiris, J. Forquer, S. Ko, P. A. S. Johnstone, and I. Das. "Intra- and Inter-Physician Variability in Target Volume Delineation for Daily CT-based Image Guided Radiation Therapy." International Journal of Radiation Oncology*Biology*Physics 72, no. 1 (September 2008): S448—S449. http://dx.doi.org/10.1016/j.ijrobp.2008.06.1831.

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41

Leunens, G., J. Menten, C. Weltens, J. Verstraete, and E. van der Schueren. "Quality assessment of medical decision making in radiation oncology: variability in target volume delineation for brain tumours." Radiotherapy and Oncology 29, no. 2 (November 1993): 169–75. http://dx.doi.org/10.1016/0167-8140(93)90243-2.

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42

Apolle, Rudi, Steffen Appold, Henk P. Bijl, Pierre Blanchard, Johan Bussink, Corinne Faivre-Finn, Jonathan Khalifa, et al. "Inter-observer variability in target delineation increases during adaptive treatment of head-and-neck and lung cancer." Acta Oncologica 58, no. 10 (July 4, 2019): 1378–85. http://dx.doi.org/10.1080/0284186x.2019.1629017.

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43

Xu, Y., S. Ma, D. Yu, J. Wang, L. Zhang, and X. Di. "FDG-PET/CT imaging for staging and definition of tumor volumes in radiation treatment planning in non-small cell lung cancer." Journal of Clinical Oncology 27, no. 15_suppl (May 20, 2009): 7574. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.7574.

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7574 Background: 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) /computed tomography (CT) has a potential improvement for staging and radiation treatment (RT) planning of various tumor sites. But from a clinical standpoint, the open questions are essentially the following: to what extent does PET/CT change the target volume? Can PET/CT reduce inter-observer variability in target volume delineation? We analyzed the use of FDG-PET/ CT images for staging and evaluated the impact of FDG- PET/CT on the radiotherapy volume delineation compared with CT in patients with non-small cell lung cancer (NSCLC) candidates for radiotherapy. Intraobserver variation in delineating tumor volumes was also observed. Methods: Twenty-three patients with stage I-III NSCLC were enrolled in this pilot study and were treated with fractionated RT based therapy with or without chemotherapy. FDG-PET/CT scans were acquired within 2 weeks prior to RT. PET and CT data sets were sent to the treatment planning system Pinnacle through compact disc. The CT and PET images were subsequently fused by means of a dedicated radiation treatment planning system. Gross Tumor Volume (GTV) was contoured by four radiation oncologists respectively on CT (CT-GTV) and PET/CT images (PET/CT-GTV). The resulting volumes were analyzed and compared. Results: For the first phase, two radiation oncologists outlined together the contours achieving a final consensus. Based on PET/CT, changes in TNM categories occurred in 8/23 cases (35%). Radiation targeting with fused FDG-PET and CT images resulted in alterations in radiation therapy planning in 12/20 patients (60%) by comparison with CT targeting. The most prominent changes in GTV have been observed in cases with atelectasis. For the second phase was four intraobserver variation in delineating tumor volumes. The mean ratio of largest to smallest CT-based GTV was 2.31 (range 1.01–5.96). The addition of the PET data reduced the mean ratio to 1.46 (range 1.12–2.27). Conclusions: PET/CT fusion images could have a potential impact on both tumor staging and treatment planning. Implementing matched PET/CT reduced observer variation in delineating tumor volumes significantly with respect to CT only. [Table: see text]

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CASTRO PENA, P., Y. M. KIROVA, F. CAMPANA, R. DENDALE, M. A. BOLLET, N. FOURNIER-BIDOZ, and A. FOURQUET. "Anatomical, clinical and radiological delineation of target volumes in breast cancer radiotherapy planning: individual variability, questions and answers." British Journal of Radiology 82, no. 979 (July 2009): 595–99. http://dx.doi.org/10.1259/bjr/96865511.

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Muracciole, X., J. Cuilliere, S. Hoffstetter, C. Alapetite, P. Quetin, M. Baron, Z. Gaci, J. Maire, S. Chapet, and C. Carrie. "Quality assurance of a French multicentric conformal radiotherapy protocol for low-stage medulloblastoma : variability in target volume delineation." International Journal of Radiation Oncology*Biology*Physics 54, no. 2 (October 2002): 148–49. http://dx.doi.org/10.1016/s0360-3016(02)03315-1.

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Harris, E. E. R. "Variability of target and normal structure delineation for breast cancer radiotherapy: an RTOG Multi-Institutional and Multiobserver Study." Breast Diseases: A Year Book Quarterly 21, no. 1 (January 2010): 67–68. http://dx.doi.org/10.1016/s1043-321x(10)79467-4.

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Li, X. Allen, An Tai, Douglas W. Arthur, Thomas A. Buchholz, Shannon Macdonald, Lawrence B. Marks, Jean M. Moran, et al. "Variability of Target and Normal Structure Delineation for Breast Cancer Radiotherapy: An RTOG Multi-Institutional and Multiobserver Study." International Journal of Radiation Oncology*Biology*Physics 73, no. 3 (March 2009): 944–51. http://dx.doi.org/10.1016/j.ijrobp.2008.10.034.

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Smet, Stéphanie, Nicole Nesvacil, Johannes Knoth, Alina Sturdza, Dina Najjari-Jamal, Filip Jelinek, Gernot Kronreif, et al. "Hybrid TRUS/CT with optical tracking for target delineation in image-guided adaptive brachytherapy for cervical cancer." Strahlentherapie und Onkologie 196, no. 11 (July 3, 2020): 983–92. http://dx.doi.org/10.1007/s00066-020-01656-2.

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Abstract Objective To prospectively compare the interobserver variability of combined transrectal ultrasound (TRUS)/computed tomography (CT)- vs. CT only- vs. magnetic resonance imaging (MRI) only-based contouring of the high-risk clinical target volume (CTVHR) in image-guided adaptive brachytherapy (IGABT) for locally advanced cervical cancer (LACC). Methods Five patients with LACC (FIGO stages IIb–IVa) treated with radiochemotherapy and IGABT were included. CT, TRUS, and T2-weighted MRI images were performed after brachytherapy applicator insertion. 3D-TRUS image acquisition was performed with a customized ultrasound stepper device and software. Automatic applicator reconstruction using optical tracking was performed in the TRUS dataset and TRUS and CT images were fused with rigid image registration with the applicator as reference structure. The CTVHR (based on the GEC-ESTRO recommendations) was contoured by five investigators on the three modalities (CTVHR_CT, CTVHR_TRUS-CT, and CTVHR_MRI). A consensus reference CTVHR_MRI (MRIref) was defined for each patient. Descriptive statistics and overlap measures were calculated using RTslicer (SlicerRT Community and Percutaneous Surgery Laboratory, Queen’s University, Canada), comparing contours of every observer with one another and with the MRIref. Results The interobserver coefficient of variation was 0.18 ± 0.05 for CT, 0.10 ± 0.04 for TRUS-CT, and 0.07 ± 0.03 for MRI. Interobserver concordance in relation to the MRIref expressed by the generalized conformity index was 0.75 ± 0.04 for MRI, 0.51 ± 0.10 for TRUS-CT, and 0.48 ± 0.06 for CT. The mean CTVHR_CT volume of all observers was 71% larger than the MRIref volume, whereas the mean CTVHR_TRUS-CT volume was 15% larger. Conclusion Hybrid TRUS-CT as an imaging modality for contouring the CTVHR in IGABT for LACC is feasible and reproducible among multiple observers. TRUS-CT substantially reduces overestimation of the CTVHR volume of CT alone while maintaining similar interobserver variability.

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Liermann, Jakob, Mustafa Syed, Edgar Ben-Josef, Kai Schubert, Ingmar Schlampp, Simon David Sprengel, Jonas Ristau, et al. "Impact of FAPI-PET/CT on Target Volume Definition in Radiation Therapy of Locally Recurrent Pancreatic Cancer." Cancers 13, no. 4 (February 14, 2021): 796. http://dx.doi.org/10.3390/cancers13040796.

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(1) Background: A new radioactive positron emission tomography (PET) tracer uses inhibitors of fibroblast activation protein (FAPI) to visualize FAP-expressing cancer associated fibroblasts. Significant FAPI-uptake has recently been demonstrated in pancreatic cancer patients. Target volume delineation for radiation therapy still relies on often less precise conventional computed tomography (CT) imaging, especially in locally recurrent pancreatic cancer patients. The need for improvement in precise tumor detection and delineation led us to innovatively use the novel FAPI-PET/CT for radiation treatment planning. (2) Methods: Gross tumor volumes (GTVs) of seven locally recurrent pancreatic cancer cases were contoured by six radiation oncologists. In addition, FAPI-PET/CT was used to automatically delineate tumors. The interobserver variability in target definition was analyzed and FAPI-based automatic GTVs were compared to the manually defined GTVs. (3) Results: Target definition differed significantly between different radiation oncologists with mean dice similarity coefficients (DSCs) between 0.55 and 0.65. There was no significant difference between the volumes of automatic FAPI-GTVs based on the threshold of 2.0 and most of the manually contoured GTVs by radiation oncologists. (4) Conclusion: Due to its high tumor to background contrast, FAPI-PET/CT seems to be a superior imaging modality compared to the current gold standard contrast-enhanced CT in pancreatic cancer. For the first time, we demonstrate how FAPI-PET/CT could facilitate target definition and increases consistency in radiation oncology in pancreatic cancer.

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Struikmans, Henk, Carla Wárlám-Rodenhuis, Tanja Stam, Gerard Stapper, Robbert J. H. A. Tersteeg, Gijsbert H. Bol, and Cornelis P. J. Raaijmakers. "Interobserver variability of clinical target volume delineation of glandular breast tissue and of boost volume in tangential breast irradiation." Radiotherapy and Oncology 76, no. 3 (September 2005): 293–99. http://dx.doi.org/10.1016/j.radonc.2005.03.029.

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