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- Nyholm, Tufve, et al.
(författare)
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A national approach for automated collection of standardized and population-based radiation therapy data in Sweden
- 2016
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Ingår i: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140 .- 1879-0887. ; 119:2, s. 344-350
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To develop an infrastructure for structured and automated collection of interoperable radiation therapy (RT) data into a national clinical quality registry. Materials and methods: The present study was initiated in 2012 with the participation of seven of the 15 hospital departments delivering RT in Sweden. A national RT nomenclature and a database for structured unified storage of RT data at each site (Medical Information Quality Archive, MIQA) have been developed. Aggregated data from the MIQA databases are sent to a national RT registry located on the same IT platform (INCA) as the national clinical cancer registries. Results: The suggested naming convention has to date been integrated into the clinical workflow at 12 of 15 sites, and MIQA is installed at six of these. Involvement of the remaining 3/15 RT departments is ongoing, and they are expected to be part of the infrastructure by 2016. RT data collection from ARIA (R), Mosaiq (R), Eclipse (TM), and Oncentra (R) is supported. Manual curation of RT-structure information is needed for approximately 10% of target volumes, but rarely for normal tissue structures, demonstrating a good compliance to the RT nomenclature. Aggregated dose/volume descriptors are calculated based on the information in MIQA and sent to INCA using a dedicated service (MIQA2INCA). Correct linkage of data for each patient to the clinical cancer registries on the INCA platform is assured by the unique Swedish personal identity number. Conclusions: An infrastructure for structured and automated prospective collection of syntactically inter operable RT data into a national clinical quality registry for RT data is under implementation. Future developments include adapting MIQA to other treatment modalities (e.g. proton therapy and brachytherapy) and finding strategies to harmonize structure delineations. How the RT registry should comply with domain-specific ontologies such as the Radiation Oncology Ontology (ROO) is under discussion.
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- Piqeur, Floor, et al.
(författare)
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Development of a consensus-based delineation guideline for locally recurrent rectal cancer
- 2022
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Ingår i: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140 .- 1879-0887. ; 177, s. 214-221
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Tidskriftsartikel (refereegranskat)abstract
- Background and purpose: Neoadjuvant chemoradiotherapy (nCRT) is used in locally recurrent rectal cancer (LRRC) to increase chances of a radical surgical resection. Delineation in LRRC is hampered by complex disease presentation and limited clinical exposure. Within the PelvEx II trial, evaluating the benefit of chemotherapy preceding nCRT for LRRC, a delineation guideline was developed by an expert LRRC team. Materials and methods: Eight radiation oncologists, from Dutch and Swedish expert centres, participated in two meetings, delineating GTV and CTV in six cases. Regions at-risk for re-recurrence or irradical resection were identified by eleven expert surgeons and one expert radiologist. Target volumes were evaluated multidisciplinary. Inter-observer variation was analysed. Results: Inter-observer variation in delineation of LRRC appeared large. Multidisciplinary evaluation per case is beneficial in determining target volumes. The following consensus regarding target volumes was reached. GTV should encompass all tumour, including extension into OAR if applicable. If the tumour is in fibrosis, GTV should encompass the entire fibrotic area. Only if tumour can clearly be distinguished from fibrosis, GTV may be reduced, as long as the entire fibrotic area is covered by the CTV. CTV is GTV with a 1 cm margin and should encompass all at-risk regions for irradical resection or re-recurrence. CTV should not be adjusted towards other organs. Multifocal recurrences should be encompassed in one CTV. Elective nodal delineation is only advised in radiotherapy-naïve patients. Conclusion: This study provides a first consensus-based delineation guideline for LRRC. Analyses of re-recurrences is needed to understand disease behaviour and to optimize delineation guidelines accordingly.
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- Egevad, L, et al.
(författare)
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Atypical stromal hyperplasia of the prostate
- 2008
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Ingår i: Scandinavian journal of urology and nephrology. - : Informa UK Limited. - 0036-5599 .- 1651-2065. ; 42:5, s. 484-487
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Tidskriftsartikel (refereegranskat)
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- Egevad, L, et al.
(författare)
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Beta-tubulin III expression in prostate cancer
- 2010
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Ingår i: Scandinavian journal of urology and nephrology. - : Informa UK Limited. - 1651-2065 .- 0036-5599. ; 44:6, s. 371-377
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Tidskriftsartikel (refereegranskat)
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- Olsson, Caroline, 1970, et al.
(författare)
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Autosegmentation based on different-sized training datasets of consistently-curated volumes and impact on rectal contours in prostate cancer radiation therapy
- 2022
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Ingår i: Physics and imaging in radiation oncology (PIRO). - : Elsevier BV. - 2405-6316. ; 22, s. 67-72
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Tidskriftsartikel (refereegranskat)abstract
- Background and purpose: Autosegmentation techniques are emerging as time-saving means for radiation therapy (RT) contouring, but the understanding of their performance on different datasets is limited. The aim of this study was to determine agreement between rectal volumes by an existing autosegmentation algorithm and manually-delineated rectal volumes in prostate cancer RT. We also investigated contour quality by differentsized training datasets and consistently-curated volumes for retrained versions of this same algorithm. Materials and methods: Single-institutional data from 624 prostate cancer patients treated to 50-70 Gy were used. Manually-delineated clinical rectal volumes (clinical) and consistently-curated volumes recontoured to one anatomical guideline (reference) were compared to autocontoured volumes by a commercial autosegmentation tool based on deep-learning (v1; n = 891, multiple-institutional data) and retrained versions using subsets of the curated volumes (v32/64/128/256; n = 32/64/128/256). Evaluations included dose-volume histogram metrics, Dice similarity coefficients, and Hausdorff distances; differences between groups were quantified using parametric or non-parametric hypothesis testing. Results: Volumes by v1-256 (76-78 cm(3)) were larger than reference (75 cm(3)) and clinical (76 cm(3)). Mean doses by v1-256 (24.2-25.2 Gy) were closer to reference (24.2 Gy) than to clinical (23.8 Gy). Maximum doses were similar for all volumes (65.7-66.0 Gy). Dice for v1-256 and reference (0.87-0.89) were higher than for v1-256 and clinical (0.86-0.87) with corresponding Hausdorff comparisons including reference smaller than comparisons including clinical (5-6 mm vs. 7-8 mm). Conclusion: Using small single-institutional RT datasets with consistently-defined rectal volumes when training autosegmentation algorithms created contours of similar quality as the same algorithm trained on large multiinstitutional datasets.
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