PhD Scientific Days 2024

Surgical Medicine

Histopathological prediction of pediatric posterior fossa tumors based on geometry analysis

Előadó neve

Dr. Mezei, Tamás, PhD

Előadó munkahelye

Clinic of Neurosurgery and Neurointervention

Előadó telefonszáma

+36303603124

Előadó e-mail címe

tamas.mezei13@gmail.com

Az előadás címe

Histopathological prediction of pediatric posterior fossa tumors based on geometry analysis

Szerző(k) neve és munkahelye

Tamás Mezei^1,2, János Báskay^3,4, Balázs Markia¹, Péter Várallyay¹, Péter Banczerowski^1,2, Péter Pollner^3,4

1: Clinic of Neurosurgery and Neurointervention
2: Department of Neurosurgery, Semmelweis University
3: Health Services Management Training Center, Semmelweis University
4: Department of Biological Physics, Eötvös Loránd University

Bemutatás módja

Szóbeli

Szekció

Surgical Medicine

Language of the presentation

English

Preferred session

Surgical Medicine

Összefoglaló szövege

Introduction
The most common types of pediatric posterior fossa tumors are pilocytic astrocytomas, embryonal tumors and ependymomas. Preoperative knowledge of the pathological diagnosis may facilitate optimal surgical management. The complex geometry of tumors can be characterized by using different metrics like fractal geometry parameters which plays an important role in the description of irregular, rough shapes.
Aims
Our aim was to perform the fractal analysis of pediatric posterior fossa tumors and thus identify new radiological biomarker(s).
Methods
We performed a retrospective clinical study, in which we processed the data and preoperative images of pediatric patients who underwent surgery for posterior fossa tumor. For all patients, the T1, ceT1, T2, FLAIR sequences of the MRI scans were required. Tumors were segmented by ITK-SNAP software (version 3.8.0), then fractal analysis (sliding-window method to determine the fractal dimension of tumors, lacunarity index), t-tests, Fischer exact tests, logistic regression and ROC analysis were performed.
Results
The selection criteria were fulfilled by 48 patients (34 female and 14 male). T-tests for tumor volume, fractal dimension (FD), FLAIR lacunarity index (LI) and Fischer test for characterization of the cystic component revealed significant differences between the 3 main tumor types. Prediction formula was constructed by weighting the chosen factors by logistic regression. With ROC analysis, we measured a mean 0.716 AUC (80%CI=0.623-0.809) value for just the fractal properties. Additional clinical parameters could improve the AUC to 0.793 (80%CI=0.700-0.896).
Conclusions
Our study suggests that fractal metrics are useful tools for preoperative estimation of histological diagnosis.
Funding
Supported by the ÚNKP-23-4-II New National Excellence Program of the Ministry for Culture and Innovation from the National Research, Development and Innovation Fund.
The study was partially funded by the National Research, Development and Innovation Office of Hungary grant (RRF-2.3.1-21-2022-00006, Data-Driven Health Division of National Laboratory for Health Security) and grant K128780.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

University

Semmelweis University

Supervisor

Péter Banczerowski

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

6182

Start

15:30

End

15:40