Tag: Shape

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The meningioma surface factor: a novel approach to quantify shape irregularity on preoperative imaging and its correlation with WHO grade

J Neurosurg 136:1535–1541, 2022

Atypical and anaplastic meningiomas account for 20% of all meningiomas. An irregular tumor shape on preoperative MRI has been associated with WHO grade II–III histology. However, this subjective allocation does not allow quantification or comparison. An objective parameter of irregularity could substantially influence resection strategy toward a more aggressive approach. Therefore, the aim of this study was to objectively quantify the level of irregularity on preoperative MRI and predict histology based on WHO grade using this novel approach.

METHODS A retrospective study on meningiomas resected between January 2010 and December 2018 was conducted at two neurosurgical centers. This novel approach relies on the theory that a regularly shaped tumor has a smaller surface area than an irregularly shaped tumor with the same volume. A factor was generated using the surface area of a corresponding sphere as a reference, because for a given volume a sphere represents the shape with the smallest surface area possible. Consequently, the surface factor (SF) was calculated by dividing the surface area of a sphere with the same volume as the tumor with the surface area of the tumor. The resulting value of the SF ranges from > 0 to 1. Finally, the SF of each meningioma was then correlated with the corresponding histopathological grading.

RESULTS A total of 126 patients were included in this study; 60.3% had a WHO grade I, 34.9% a WHO grade II, and 4.8% a WHO grade III meningioma. Calculation of the SF demonstrated a significant difference in SFs between WHO grade I (SF 0.851) and WHO grade II–III meningiomas (SF 0.788) (p < 0.001). Multivariate analysis identified SF as an independent prognostic factor for WHO grade (OR 0.000009, 95% CI 0.000–0.159; p = 0.020).

CONCLUSIONS The SF is a proposed mathematical model for a quantitative and objective measurement of meningioma shape, instead of the present subjective assessment. This study revealed significant differences between the SFs of WHO grade I and WHO grade II–III meningiomas and demonstrated that SF is an independent prognostic factor for WHO grade.

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The Shape grading system: a classification for growth patterns of pituitary adenomas

Acta Neurochirurgica (2021) 163:3181–3189

Long-term tumor control of pituitary adenomas may be achieved by gross total resection (GTR). Factors, which influence the extent of resection, are invasiveness, tumor size, and possibly tumor shape. Nevertheless, the latter factor has not been assessed so far and there is no classification for the different shapes. The aim of this study was to evaluate the impact of different tumor shapes on GTR rates and outcome according to our proposed “Shape grading system.”

Methods In this retrospective single center study, the radiological outcome of nonfunctioning pituitary adenomas was assessed with respect to the following previously defined growth patterns: spherical (Shape I), oval (Shape II), dumbbell (Shape III), mushroom (Shape IV), and polylobulated (Shape V).

Results A total of 191 patients were included (Shape I, n = 28 (15%); Shape II, n = 91 (48%); Shape III, n = 37 (19%); Shape IV, n = 12 (6%); Shape V, n = 23 (12%)). GTR was achieved in 101 patients (53%) with decreasing likelihood of GTR in higher shape grades (Shape I, n = 23 (82%); Shape II, n = 67 (74%); Shape III, n = 9 (24%); Shape IV, n = 2 (17%); Shape V, n = 0 (0%)). This correlated with larger tumor remnants, a higher risk of tumor recurrence/regrowth and therefore necessity of re-surgery and/or radiotherapy/radiosurgery.

Conclusion The “Shape grading system” may be used as a predictor of the outcome in nonfunctioning pituitary adenomas. The higher the “Shape grade,” the higher the likelihood for lower GTR rates, larger tumor remnants, and need for further therapies.

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External validation of cerebral aneurysm rupture probability model with data from two patient cohorts

Acta Neurochirurgica (2018) 160:2425–2434

For a treatment decision of unruptured cerebral aneurysms, physicians and patients need to weigh the risk of treatment against the risk of hemorrhagic stroke caused by aneurysm rupture. The aim of this study was to externally evaluate a recently developed statistical aneurysm rupture probability model, which could potentially support such treatment decisions.

Methods Segmented image data and patient information obtained from two patient cohorts including 203 patients with 249 aneurysms were used for patient-specific computational fluid dynamics simulations and subsequent evaluation of the statistical model in terms of accuracy, discrimination, and goodness of fit. The model’s performance was further compared to a similaritybased approach for rupture assessment by identifying aneurysms in the training cohort that were similar in terms of hemodynamics and shape compared to a given aneurysm from the external cohorts.

Results When applied to the external data, the model achieved a good discrimination and goodness of fit (area under the receiver operating characteristic curve AUC = 0.82), which was only slightly reduced compared to the optimism-corrected AUC in the training population (AUC = 0.84). The accuracy metrics indicated a small decrease in accuracy compared to the training data (misclassification error of 0.24 vs. 0.21). The model’s prediction accuracy was improved when combined with the similarity approach (misclassification error of 0.14).

Conclusions The model’s performance measures indicated a good generalizability for data acquired at different clinical institutions. Combining the model-based and similarity-based approach could further improve the assessment and interpretation of new cases, demonstrating its potential use for clinical risk assessment.

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