دورية أكاديمية

MRI radiomics captures early treatment response in patient-derived organoid endometrial cancer mouse models

التفاصيل البيبلوغرافية
العنوان: MRI radiomics captures early treatment response in patient-derived organoid endometrial cancer mouse models
المؤلفون: Heidi Espedal, Kristine E. Fasmer, Hege F. Berg, Jenny M. Lyngstad, Tomke Schilling, Camilla Krakstad, Ingfrid S. Haldorsen
المصدر: Frontiers in Oncology, Vol 14 (2024)
بيانات النشر: Frontiers Media S.A., 2024.
سنة النشر: 2024
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: patient-derived organoids, MRI radiomics, endometrial cancer, preclinical imaging, patient-derived model, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: BackgroundRadiomics can capture microscale information in medical images beyond what is visible to the naked human eye. Using a clinically relevant mouse model for endometrial cancer, the objective of this study was to develop and validate a radiomic signature (RS) predicting response to standard chemotherapy.MethodsMice orthotopically implanted with a patient-derived grade 3 endometrioid endometrial cancer organoid model (O-PDX) were allocated to chemotherapy (combined paclitaxel/carboplatin, n=11) or saline/control (n=13). During tumor progression, the mice underwent weekly T2-weighted (T2w) magnetic resonance imaging (MRI). Segmentation of primary tumor volume (vMRI) allowed extraction of radiomic features from whole-volume tumor masks. A radiomic model for predicting treatment response was derived employing least absolute shrinkage and selection operator (LASSO) statistics at endpoint images in the orthotopic O-PDX (RS_O), and subsequently applied on the earlier study timepoints (RS_O at baseline, and week 1-3). For external validation, the radiomic model was tested in a separate T2w-MRI dataset on segmented whole-volume subcutaneous tumors (RS_S) from the same O-PDX model, imaged at three timepoints (baseline, day 3 and day 10/endpoint) after start of chemotherapy (n=8 tumors) or saline/control (n=8 tumors).ResultsThe RS_O yielded rapidly increasing area under the receiver operating characteristic (ROC) curves (AUCs) for predicting treatment response from baseline until endpoint; AUC=0.38 (baseline); 0.80 (week 1), 0.85 (week 2), 0.96 (week 3) and 1.0 (endpoint). In comparison, vMRI yielded AUCs of 0.37 (baseline); 0.69 (w1); 0.83 (week 2); 0.92 (week 3) and 0.97 (endpoint). When tested in the external validation dataset, RS_S yielded high accuracy for predicting treatment response at day10/endpoint (AUC=0.85) and tended to yield higher AUC than vMRI (AUC=0.78, p=0.18). Neither RS_S nor vMRI predicted response at day 3 in the external validation set (AUC=0.56 for both).ConclusionsWe have developed and validated a radiomic signature that was able to capture chemotherapeutic treatment response both in an O-PDX and in a subcutaneous endometrial cancer mouse model. This study supports the promising role of preclinical imaging including radiomic tumor profiling to assess early treatment response in endometrial cancer models.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2234-943X
Relation: https://www.frontiersin.org/articles/10.3389/fonc.2024.1334541/full; https://doaj.org/toc/2234-943X
DOI: 10.3389/fonc.2024.1334541
URL الوصول: https://doaj.org/article/e403cc20888a4c6e8e9d0b08de4af815
رقم الأكسشن: edsdoj.403cc20888a4c6e8e9d0b08de4af815
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2234943X
DOI:10.3389/fonc.2024.1334541