Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery
PurposeCraniopharyngiomas (CPs) are benign tumors, complete tumor resection is considered to be the optimal treatment. However, although histologically benign, the local invasiveness of CPs commonly contributes to incomplete resection and a poor prognosis. At present, some advocate less aggressive s...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-02-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2020.599888/full |
| _version_ | 1829139889133715456 |
|---|---|
| author | Guofo Ma Jie Kang Ning Qiao Bochao Zhang Xuzhu Chen Guilin Li Zhixian Gao Songbai Gui |
| author_facet | Guofo Ma Jie Kang Ning Qiao Bochao Zhang Xuzhu Chen Guilin Li Zhixian Gao Songbai Gui |
| author_sort | Guofo Ma |
| collection | DOAJ |
| description | PurposeCraniopharyngiomas (CPs) are benign tumors, complete tumor resection is considered to be the optimal treatment. However, although histologically benign, the local invasiveness of CPs commonly contributes to incomplete resection and a poor prognosis. At present, some advocate less aggressive surgery combined with radiotherapy as a more reasonable and effective means of protecting hypothalamus function and preventing recurrence in patients with tight tumor adhesion to the hypothalamus. Hence, if a method can be developed to predict the invasiveness of CP preoperatively, it will help in the development of a more personalized surgical strategy. The aim of the study was to report a radiomics-clinical nomogram for the individualized preoperative prediction of the invasiveness of adamantinomatous CP (ACPs) before surgery.MethodsIn total, 1,874 radiomics features were extracted from whole tumors on contrast-enhanced T1-weighted images. A support vector machine trained a predictive model that was validated using receiver operating characteristic (ROC) analysis on an independent test set. Moreover, a nomogram was constructed incorporating clinical characteristics and the radiomics signature for individual prediction.ResultsEleven features associated with the invasiveness of ACPs were selected by using the least absolute shrinkage and selection operator (LASSO) method. These features yielded area under the curve (AUC) values of 79.09 and 73.5% for the training and test sets, respectively. The nomogram incorporating peritumoral edema and the radiomics signature yielded good calibration in the training and test sets with the AUCs of 84.79 and 76.48%, respectively.ConclusionThe developed model yields good performance, indicating that the invasiveness of APCs can be predicted using noninvasive radiological data. This reliable, noninvasive tool can help clinical decision making and improve patient prognosis. |
| first_indexed | 2024-12-14T19:43:31Z |
| format | Article |
| id | doaj.art-81fd6e01c2894d74a4cb0b83a86ed44e |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-14T19:43:31Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-81fd6e01c2894d74a4cb0b83a86ed44e2022-12-21T22:49:38ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-02-011010.3389/fonc.2020.599888599888Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before SurgeryGuofo Ma0Jie Kang1Ning Qiao2Bochao Zhang3Xuzhu Chen4Guilin Li5Zhixian Gao6Songbai Gui7Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaNeuropathology Department, Beijing Neurosurgical Institute, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaPurposeCraniopharyngiomas (CPs) are benign tumors, complete tumor resection is considered to be the optimal treatment. However, although histologically benign, the local invasiveness of CPs commonly contributes to incomplete resection and a poor prognosis. At present, some advocate less aggressive surgery combined with radiotherapy as a more reasonable and effective means of protecting hypothalamus function and preventing recurrence in patients with tight tumor adhesion to the hypothalamus. Hence, if a method can be developed to predict the invasiveness of CP preoperatively, it will help in the development of a more personalized surgical strategy. The aim of the study was to report a radiomics-clinical nomogram for the individualized preoperative prediction of the invasiveness of adamantinomatous CP (ACPs) before surgery.MethodsIn total, 1,874 radiomics features were extracted from whole tumors on contrast-enhanced T1-weighted images. A support vector machine trained a predictive model that was validated using receiver operating characteristic (ROC) analysis on an independent test set. Moreover, a nomogram was constructed incorporating clinical characteristics and the radiomics signature for individual prediction.ResultsEleven features associated with the invasiveness of ACPs were selected by using the least absolute shrinkage and selection operator (LASSO) method. These features yielded area under the curve (AUC) values of 79.09 and 73.5% for the training and test sets, respectively. The nomogram incorporating peritumoral edema and the radiomics signature yielded good calibration in the training and test sets with the AUCs of 84.79 and 76.48%, respectively.ConclusionThe developed model yields good performance, indicating that the invasiveness of APCs can be predicted using noninvasive radiological data. This reliable, noninvasive tool can help clinical decision making and improve patient prognosis.https://www.frontiersin.org/articles/10.3389/fonc.2020.599888/fullcraniopharyngiomaadamantinomatousinvasivenessradiomicsmachine learningnomogram |
| spellingShingle | Guofo Ma Jie Kang Ning Qiao Bochao Zhang Xuzhu Chen Guilin Li Zhixian Gao Songbai Gui Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery Frontiers in Oncology craniopharyngioma adamantinomatous invasiveness radiomics machine learning nomogram |
| title | Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery |
| title_full | Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery |
| title_fullStr | Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery |
| title_full_unstemmed | Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery |
| title_short | Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery |
| title_sort | non invasive radiomics approach predict invasiveness of adamantinomatous craniopharyngioma before surgery |
| topic | craniopharyngioma adamantinomatous invasiveness radiomics machine learning nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2020.599888/full |
| work_keys_str_mv | AT guofoma noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery AT jiekang noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery AT ningqiao noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery AT bochaozhang noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery AT xuzhuchen noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery AT guilinli noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery AT zhixiangao noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery AT songbaigui noninvasiveradiomicsapproachpredictinvasivenessofadamantinomatouscraniopharyngiomabeforesurgery |