Share:
Share this content in WeChat
X
Clinical Articles
Prediction of recurrence of craniopharyngioma within 5 years after operation based on preoperative MR radiomics model
ZHAN Dongwei  KONG Xin  LUO Yuqi  ZHANG Yu  MA Jun 

Cite this article as: ZHAN D W, KONG X, LUO Y Q, et al. Prediction of recurrence of craniopharyngioma within 5 years after operation based on preoperative MR radiomics model[J]. Chin J Magn Reson Imaging, 2023, 14(7): 37-41. DOI:10.12015/issn.1674-8034.2023.07.007.


[Abstract] Objective To investigate the MR radiomics models in predicting postoperative recurrence of craniopharyngioma within 5 years.Materials and Methods One hundred and sixty four patients who underwent surgical resection of craniopharyngioma were retrospective studied (87 cases with postoperative recurrence within five years, 77 cases without recurrence). The patients were divided into exercise group and test group as the proportion of 7∶3, Clinical characteristics of the patients were collected. 3D Slicer software was used to delineate region of interest (ROI) and extract radiomics features. Single factor analysis and least absolute shrinkage and selection operator (LASSO) were used for feature selection, and support vector machine (SVM) algorithm was used to establish the radiomics model and clinical model, the area under the curve (AUC) value was calculated and receiver operating characteristic (ROC) curve was drawn to evaluate the prediction efficacy of the model.Results In the training group, the AUC of radiomics model in predicting the recurrence of craniopharyngioma within 5 years after operation was 0.767 [95% confidence interva (CI): 0649-0.816], the sensitivity was 77%, and specificity was 71%. In the test group, the AUC of radiomics model in predicting the recurrence of craniopharyngioma within 5 years after operation was 0.770 (95% CI: 0.657-0.898), the sensitivity was 71%, and specificity was 86%.Conclusions The radiomics model based on contrast-enhanced T1-weighted imaging (CE-T1WI) is effective in predicting the recurrence of craniopharyngioma.
[Keywords] craniopharyngioma;magnetic resonance imaging;radiomics;recurrence;prediction

ZHAN Dongwei1, 2   KONG Xin2   LUO Yuqi2   ZHANG Yu2   MA Jun2*  

1 Department of Radiology, Beijing Pinggu District Hospital of Traditional Chinese Medicine, Beijing 101200, China

2 Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China

Corresponding author: Ma J, E-mail: dr.junma@foxmail.com

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 61771325).
Received  2022-12-27
Accepted  2023-06-28
DOI: 10.12015/issn.1674-8034.2023.07.007
Cite this article as: ZHAN D W, KONG X, LUO Y Q, et al. Prediction of recurrence of craniopharyngioma within 5 years after operation based on preoperative MR radiomics model[J]. Chin J Magn Reson Imaging, 2023, 14(7): 37-41. DOI:10.12015/issn.1674-8034.2023.07.007.

[1]
NIELSEN E H, FELDT-RASMUSSEN U, POULSGAARD L, et al. Incidence of craniopharyngioma in Denmark (n=189) and estimated world incidence of craniopharyngioma in children and adults[J]. J Neurooncol, 2011, 104(3): 755-763. DOI: 10.1007/S11060-011-0540-6.
[2]
TAKASHI K. The 2016 WHO Classification of Tumours of the Central Nervous System: The Major Points of Revision[J]. Komori T, 2017, 57(7): 301-311. DOI: 10.2176.nmc.ra.2017-0010.
[3]
LOUIS D N, PERRY A, WESSELING P, et al. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary[J]. Neuro Oncol, 2021, 23(8): 1231-1251. DOI: 10.1093/neuonc/noab106.
[4]
KIM S K, WANG K C, SHIN S H, et al. Radical excision of pediatric craniopharyngioma: recurrence pattern and prognostic factors[J]. Childs Nerv Syst, 2001, 17(9): 531-536, 537.
[5]
QI S T, PAN J, BAO Y, et al. The characteristics and surgical treatments of various types of craniopharyngioma classified by QST[J]. Chin J Neurosurgery, 2017, 33(11): 1088-1093. DOI: 10.3760/cma.j.issn.1001-2346.2017.11.003.
[6]
LAMBIN P, RIOS-VELAZQUEZ E, LEIJENAAR R, et al. Radiomics: extracting more information from medical images using advanced feature analysis[J]. Eur J Cancer, 2012, 48(4): 441-446. DOI: 10.1016/j.ejca.2011.11.036.
[7]
KUMAR V, GU Y, BASU S, et al. Radiomics: the process and the challenges[J]. Magn Reson Imaging, 2012, 30(9): 1234-1248. DOI: 10.1016/j.mri.2012.06.010.
[8]
LAMBIN P, LEIJENAAR R T H, DEIST T M, et al. Radiomics: the bridge between medical imaging and personalized medicine[J]. Nat Rev Clin Oncol, 2017, 14(12): 749-762. DOI: 10.1038/nrclinonc.2017.141.
[9]
RIZZO S, BOTTA F, RAIMONDI S, et al. Radiomics: the facts and the challenges of image analysis[J]. Eur Radiol Exp, 2018, 2(1): 36. DOI: 10.1186/s41747-018-0068-z.
[10]
SHI X E, ZHANG Y L, ZHOU Z Q, et al. Microsurgical resection of the recurrent craniopharyngiomas[J]. Chin J Surg, 2004, 42(13): 769-772. DOI: 10.3760/j:issn:0529-5815.2004.13.001.
[11]
GAUTIER A, GODBOUT A, GROSHENY C, et al. Markers of recurrence and long-term morbidity in craniopharyngioma: a systematic analysis of 171 patients[J]. J Clin Endocrinol Metab, 2012, 97(4): 1258-1267. DOI: 10.1210/jc.2011-2817.
[12]
YASARGIL M G, CURCIC M, KIS M, et al. Total removal of craniopharyngiomas. Approaches and long-term results in 144 patients[J]. J Neurosurg, 1990, 73(1): 3-11. DOI: 10.3171/jns.1990.73.1.0003.
[13]
CHEN Z, MA Z, HE W, et al. Impact of Pituitary Stalk Preservation on Tumor Recurrence/Progression and Surgically Induced Endocrinopathy After Endoscopic Endonasal Resection of Suprasellar Craniopharyngiomas[J]. Front Neurol, 2021, 12: 753944. DOI: 10.3389/fneur.2021.753944.
[14]
XIANG X, SHI X E, LEI T, et al. Microneurosurgery treatment for 41 recurrent craniopharyngioma cases[J]. Chin J Postgrad Med, 2022, 45(10): 873-876. DOI: 10.3760/cma.j.cn115455-20220414-00301.
[15]
MINAMIDA Y, MIKAMI T, HASHI K, et al. Surgical management of the recurrence and regrowth of craniopharyngiomas[J]. J Neurosurgery, 2005, 103(2): 224-232. DOI: 10.3171/jns.2005.103.2.0224.
[16]
FAHLBUSCH R, HONEGGER J, PAULUS W, et al. Surgical treatment of craniopharyngiomas: experience with 168 patients[J]. J Neurosurgery, 1999, 90(2): 237-250. DOI: 10.3171/jns.1999.90.2.0237.
[17]
ZHOU Z Q, SHI X E, WU B, et al. Relationship between the recurrence frequency of craniopharyngioma and quality-of-life in patients after tumorectomy[J]. Chinese Journal of Minimally Invasive Neurosurgery, 2008, 13(8): 347-348.
[18]
DUFF J, MEYER F B, ILSTRUP D M, et al. Long-term outcomes for surgically resected craniopharyngiomas[J]. J Neurosurgery, 2000, 46(2): 291-302, discussion 302-305. DOI: 10.1097/00006123-200002000-00007.
[19]
LEONARDO F M, PAULA C L E, AYRTON C M, et al. MRI radiomics for the prediction of recurrence in patients with clinically non-functioning pituitary macroadenomas[J] .Comput Bio Med, 2020, 124: 103966. DOI: 10.1016/j.compbiomed.2020.103966.
[20]
SONG F, SONG X, FENG Y, et al. Radiomics feature analysis and model research for predicting histopathological subtypes of non-small cell lung cancer on CT images: A multi-dataset study[J/OL]. Med Phys, 2023 [2022-12-26]. https://pubmed.ncbi.nlm.nih.gov/36682051/. DOI: 10.1002/mp.16233.
[21]
LI X, WAN Y, LOU J, et al. Preoperative recurrence prediction in pancreatic ductal adenocarcinoma after radical resection using radiomics of diagnostic computed tomography[J]. EClinicalMedicine, 2022, 43: 101215. DOI: 10.1016/j.eclinm.2021.101215.
[22]
CHIACCHIARETTA P, MASTRODICASA D, CHIARELLI A M, et al. MRI-Based Radiomics Approach Predicts Tumor Recurrence in ER+/HER2-Early Breast Cancer Patients[J]. J Digit Imaging, 2023, 36(3): 1071-1080. DOI: 10.1007/s10278-023-00781-5.
[23]
CHEN X, TONG Y, SHI Z, et al. Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach[J]. BMC Neurol, 2019, 19(1): 6. DOI: 10.1186/s12883-018-1216-z.
[24]
MA G, KANG J, QIAO N, et al. Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery[J]. Front Oncol, 2020, 10: 599888. DOI: 10.3389/fonc.2020.599888.
[25]
DANDURAND C, SEPEHRY A A, ASADI L M, et al. Adult Craniopharyngioma: Case Series, Systematic Review, and Meta-Analysis[J]. Neurosurgery, 2018, 83(4): 631-641. DOI: 10.1093/neuros/nyx570.
[26]
SADASHIVAM S, MENON G, ABRAHAM M, et al. Adult craniopharyngioma: The role of extent of resection in tumor recurrence and long-term functional outcome[J]. Clin Neurol Neurosurg, 2020, 192: 105711. DOI: 10.1016/J.CLINEURO.2020.105711.
[27]
KAWAMATA T, KUBO O, HORI T. Histological findings at the boundary of craniopharyngiomas[J]. Brain Tumor Pathol, 2005, 22(2): 75-78. DOI: 10.1007/s10014-005-0191-4.

PREV Application value of DTI in short-term prognosis of patients with branch athero-matous disease
NEXT Differentiating pulmonary inflammatory nodules from lung cancer based on whole-focus dynamic enhanced MRI intensity histogram
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn