FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4318027095> ?p ?o ?g. }

• W4318027095 endingPage "1892" @default.
• W4318027095 startingPage "1879" @default.
• W4318027095 abstract "Normal tissue complication probability (NTCP) models are often based on doses retrieved from delineated volumes. For retrospective dose-response studies focusing on organs that have not been delineated historically, automatic segmentation might be considered. However, automatic segmentation risks generating considerable delineation errors and knowledge regarding how these errors impact the estimated organ dose is important. Furthermore, organ-at-risk (OAR) dose uncertainties cannot be eliminated and might affect the resulting NTCP model. Therefore, it is also of interest to study how OAR dose errors impact the NTCP modeling results.To investigate how random delineation errors of the proximal bronchial tree, heart, and esophagus impact the estimated OAR dose, and to investigate how random errors in the doses used for dose-response modeling affect the estimated NTCPs.We investigated the impact of random delineation errors on the estimated OAR dose using the treatment plans of 39 patients treated with conventionally fractionated radiation therapy of non-small-cell lung cancer. Study-specific reference structures were defined by manually contouring the proximal bronchial tree, heart and esophagus. For each patient and organ, 120 reshaped structures were created by introducing random shifts and margins to the entire reference structure. The mean and near-maximum dose to the reference and reshaped structures were compared. In a separate investigation, the impact of random dose errors on the NTCP model was studied performing dose-response modeling with study sets containing treatment outcomes and OAR doses with and without introduced errors. Universal patient populations with defined population risks, dose-response relationships and distributions of OAR doses were used as ground truth. From such a universal population, we randomly sampled data sets consisting of OAR dose and treatment outcome into reference populations. Study sets of different sizes were created by repeatedly introducing errors to the OAR doses of each reference population. The NTCP models generated with dose errors were compared to the reference NTCP model of the corresponding reference population.A total of 14 040 reshaped structures with random delineation errors were created. The delineation errors resulted in systematic mean dose errors of less than 1% of the prescribed dose (PD). Mean dose differences above 15% of PD and near-maximum doses differences above 25% of PD were observed for 211 and 457 reshaped structures, respectively. Introducing random errors to OAR doses used for dose-response modeling resulted in systematic underestimations of the median NTCP. For all investigated scenarios, the median differences in NTCP were within 0.1 percentage points (p.p.) when comparing different study sizes.Introducing random delineation errors to the proximal bronchial tree, heart and esophagus resulted in mean dose and near-maximum dose differences above 15% and 25% of PD, respectively. We did not observe an association between the dose level and the magnitude of the dose errors. For the scenarios investigated in this study, introducing random errors to OAR doses used for dose-response modeling resulted in systematic underestimations of the median NTCP for reference risks higher than the universal population risk. The median NTCP underestimation was similar for different study sizes, all within 0.1 p.p." @default.
• W4318027095 created "2023-01-26" @default.
• W4318027095 creator A5044272184 @default.
• W4318027095 creator A5050835736 @default.
• W4318027095 creator A5078902716 @default.
• W4318027095 date "2023-02-07" @default.
• W4318027095 modified "2023-09-26" @default.
• W4318027095 title "Impact of delineation errors on the estimated organ at risk dose and of dose errors on the normal tissue complication probability model" @default.
• W4318027095 cites W1569515227 @default.
• W4318027095 cites W1948646965 @default.
• W4318027095 cites W1978801362 @default.
• W4318027095 cites W1984483689 @default.
• W4318027095 cites W1987536026 @default.
• W4318027095 cites W2010851248 @default.
• W4318027095 cites W2037171241 @default.
• W4318027095 cites W2042397994 @default.
• W4318027095 cites W2054657819 @default.
• W4318027095 cites W2065346859 @default.
• W4318027095 cites W2073662365 @default.
• W4318027095 cites W2119913211 @default.
• W4318027095 cites W2152729363 @default.
• W4318027095 cites W2232271406 @default.
• W4318027095 cites W2531931036 @default.
• W4318027095 cites W2594608309 @default.
• W4318027095 cites W2804613808 @default.
• W4318027095 cites W2886856931 @default.
• W4318027095 cites W2916412824 @default.
• W4318027095 cites W2941434555 @default.
• W4318027095 cites W2994739006 @default.
• W4318027095 cites W3012769849 @default.
• W4318027095 cites W3089737167 @default.
• W4318027095 cites W3107628190 @default.
• W4318027095 cites W3160604201 @default.
• W4318027095 cites W3178102086 @default.
• W4318027095 cites W3198479573 @default.
• W4318027095 cites W4225264219 @default.
• W4318027095 cites W4254965803 @default.
• W4318027095 doi "https://doi.org/10.1002/mp.16235" @default.
• W4318027095 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36693127" @default.
• W4318027095 hasPublicationYear "2023" @default.
• W4318027095 type Work @default.
• W4318027095 citedByCount "0" @default.
• W4318027095 crossrefType "journal-article" @default.
• W4318027095 hasAuthorship W4318027095A5044272184 @default.
• W4318027095 hasAuthorship W4318027095A5050835736 @default.
• W4318027095 hasAuthorship W4318027095A5078902716 @default.
• W4318027095 hasBestOaLocation W43180270951 @default.
• W4318027095 hasConcept C121684516 @default.
• W4318027095 hasConcept C141071460 @default.
• W4318027095 hasConcept C2777819096 @default.
• W4318027095 hasConcept C2779104521 @default.
• W4318027095 hasConcept C2908647359 @default.
• W4318027095 hasConcept C2989005 @default.
• W4318027095 hasConcept C41008148 @default.
• W4318027095 hasConcept C71924100 @default.
• W4318027095 hasConcept C99454951 @default.
• W4318027095 hasConceptScore W4318027095C121684516 @default.
• W4318027095 hasConceptScore W4318027095C141071460 @default.
• W4318027095 hasConceptScore W4318027095C2777819096 @default.
• W4318027095 hasConceptScore W4318027095C2779104521 @default.
• W4318027095 hasConceptScore W4318027095C2908647359 @default.
• W4318027095 hasConceptScore W4318027095C2989005 @default.
• W4318027095 hasConceptScore W4318027095C41008148 @default.
• W4318027095 hasConceptScore W4318027095C71924100 @default.
• W4318027095 hasConceptScore W4318027095C99454951 @default.
• W4318027095 hasFunder F4320309603 @default.
• W4318027095 hasIssue "3" @default.
• W4318027095 hasLocation W43180270951 @default.
• W4318027095 hasLocation W43180270952 @default.
• W4318027095 hasOpenAccess W4318027095 @default.
• W4318027095 hasPrimaryLocation W43180270951 @default.
• W4318027095 hasRelatedWork W1790445412 @default.
• W4318027095 hasRelatedWork W2014435840 @default.
• W4318027095 hasRelatedWork W2086839036 @default.
• W4318027095 hasRelatedWork W2090807047 @default.
• W4318027095 hasRelatedWork W2116506495 @default.
• W4318027095 hasRelatedWork W2138340330 @default.
• W4318027095 hasRelatedWork W2157740221 @default.
• W4318027095 hasRelatedWork W2415717579 @default.
• W4318027095 hasRelatedWork W2569148402 @default.
• W4318027095 hasRelatedWork W2896967120 @default.
• W4318027095 hasVolume "50" @default.
• W4318027095 isParatext "false" @default.
• W4318027095 isRetracted "false" @default.
• W4318027095 workType "article" @default.