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DOI: 10.1055/s-0046-1818848
Multi-Institutional Machine-Learning Predictor of Gross-Total Resection in Skull-Base Chondrosarcoma
Authors
Objective: Develop and validate an anatomy-driven model that predicts gross-total resection (GTR) for skull-base chondrosarcomas (SCBs).
Methods: We analyzed 179 consecutive SBCs resected at three academic centers. Thirteen preoperative variables were abstracted: tumor location, internal carotid artery (ICA) encasement, compartmental extensions, cranial-nerve involvement, prior radiotherapy, and approach. Data were split 75/25 into training (n = 135) and validation (n = 44). Five algorithms were tuned for validation. For interpretability, multivariable logistic GLM and nomogram were refitted. Performance was summarized with AUC, accuracy, sensitivity/specificity, and Brier score.
Results: Anatomic burden varied by zone, cavernous-sinus invasion clustered in peri-lacerum (66.7%) and petroclival (57.0%); jugular-foramen extension mainly petroclival (37.2%); sinonasal/orbital spread characterized midline lesions. Approach selection mirrored: EEA predominated in midline (80%) and common in petroclival (62%), whereas lateral tumors were mostly open (84.6%). GTR was 56% (101/179) overall. In petroclival disease, corridor choice was decisive (p < 0.001): ETPA 70.3% GTR vs open 25.7% and midline EEA 36.4%.
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Operative Approach, EOR, and Residual Disease |
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Petroclival (N = 121) |
Peri-lacerum (N = 30) |
Lateral (N = 13) |
Midline (N = 15) |
p-value |
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|
EOR |
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GTR |
61 (50%) |
20 (67%) |
10 (77%) |
10 (67%) |
0.116 |
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STR |
60 (49%) |
10 (35%) |
3.0 (23%) |
5 (33%) |
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GTR% x approach |
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Open |
9/35 (26%) |
12/19 (63%) |
9/11 (82%) |
2/3 (67%) |
<0.001 |
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EE-Midline |
4/11 (36%) |
4/4 (100%) |
5/8 (63%) |
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ETPA |
45/64 (70%) |
2/4 (50%) |
0/1 (0%) |
3/4 (75%) |
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Combined/stage |
3/11 (27%) |
2/3 (67%) |
1/1 (100%) |
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|
Residual disease |
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Petrous Apex |
21 (17%) |
3 (10%) |
2 (15%) |
<0.001 |
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Meckel’s-cave |
11 (8%) |
3 (11%) |
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Cavernous-sinus |
9 (7%) |
6 (23%) |
1 (7%) |
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Cavernous-ICA |
3 (2%) |
1 (3%) |
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|
Petrous-ICA |
4 (3%) |
2 (8%) |
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Jugular-Foramen |
7 (6%) |
1 (3%) |
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Multivariable analysis showed significant lower odds of GTR with graded ICA encasement (90–180° OR=3.12; 181–270° 7.41; 271–359° 9.76; 360° 8.52), prior radiotherapy (OR=4.04), petroclival location (OR=4.72) and infratemporal extension (OR=2.75). ETPA—associated with higher odds of GTR (OR=0.22, p < 0.001)—with a favorable trend for midline-EEA (OR=0.37, p = 0.063). The GLM achieved AUC=0.756, Brier=0.19 (accuracy=0.818).




Conclusion: Anatomical determinants—particularly petroclival origin, ICA encasement, and lower-cranial-nerve corridors—are the principal barriers to complete resection in SBC. The proposed ML provides a reproducible preoperative tool that aligns corridor choice with individual anatomy, improves likelihood of GTR, and rationalizes use of adjuvant therapy.
Publication History
Article published online:
27 February 2026
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