\u00a0<\/div>
Note:<\/u> <\/strong> \u00a0Subsequent to publishing this manuscript\u00a0it was discovered images from\u00a0<\/em> two patients included in the analysis\u00a0had errors and should not be used in future studies.\u00a0 Therefore these have not been included\u00a0in this TCIA data set, leaving 298 patients of the original 300 analyzed.<\/em><\/p>In the original study,\u00a093 of the 300 patients (31 %), the radiotherapy contours were directly drawn on the CT of the FDG-PET\/CT scan by expert radiation oncologists and thereafter used for treatment planning. For 207 of the 300 patients (69 %), the radiotherapy contours were drawn on a different CT scan dedicated to treatment planning and were propagated\/resampled to the FDG-PET\/CT scan reference frame using intensity-based free-form deformable registration with the software MIM\u00ae<\/sup>\u00a0(MIM software Inc., Cleveland, OH).
Patients with recurrent H&N cancer or with metastases at presentation, and patients receiving palliative treatment were excluded from the study. From the 300 patients, 48 received radiation alone (16 %) and 252 received chemo-radiation (84 %) with curative intent as part of treatment management. The median follow-up period of all patients was 43 months (range: 6-112). Patients that did not develop a locoregional recurrence or distant metastases during the follow-up period and that had a follow-up time smaller than 24 months were also excluded from the study. During the follow-up period, 45 patients developed a locoregional recurrence (15 %), 40 patients developed distant metastases (13 %) and 56 patients died (19 %).\u00a0\u00a0<\/p>We analyzed the FDG-PET and CT images of the 300 patients from four different cohorts for the risk assessment of locoregional recurrences (LR) and distant metastases in H&N cancer. Prediction models combining radiomic and clinical variables were constructed via random forests and imbalance-adjustment strategies using two of the four cohorts. Independent validation of the prediction and prognostic performance of the models was carried out on the other two cohorts (LR: AUC = 0.69 and CI = 0.67; DM: AUC = 0.86 and CI = 0.88). Furthermore, the results obtained via Kaplan-Meier analysis demonstrated the potential of radiomics for assessing the risk of specific tumour outcomes using multiple stratification groups.<\/p>","collection_acknowledgements":"
We would like to acknowledge the individuals and institutions that have provided data for this collection:<\/p>
- McGill University, Montreal, Canada\u00a0-\u00a0<\/strong>Special thanks to\u00a0Martin Valli\u00e8res\u00a0<\/strong>of\u00a0the Medical Physics Unit<\/li><\/ul>","collection_funding":"","hide_from_browse_table":"0","program":["Community"],"_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/collections\/42393","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/collections"}],"about":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/types\/tcia_collection"}],"version-history":[{"count":1,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/collections\/42393\/revisions"}],"predecessor-version":[{"id":47937,"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/collections\/42393\/revisions\/47937"}],"wp:attachment":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media?parent=42393"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}