Analiza ikstalnej i międzystatkowej scyntygrafii mózgu przy użyciu zaawansowanej obróbki komputerowej i wieloparametrowe przewidywanie wyników chirurgii epilepsji
Ictal-interictal SPECT analysis using SPM and multimodal prediction of epilepsy surgery outcome
W skrócie
Badacze sprawdzili, jak zaawansowana analiza komputerowa obrazów mózgu (scyntygrafia) pomaga w planowaniu operacji u pacjentów z opornościową epilepsją. Wykazali, że ta metoda jest najlepszym narzędziem do znalezienia źródła padaczki i przewidzenia, czy operacja będzie udana - aż 72 procent pacjentów miało dobre wyniki. Połączenie wyników tej analizy z innymi badaniami mózgu dało lekarzom narzędzie do dokładnego przewidywania powodzenia zabiegu chirurgicznego dla każdego pacjenta.
Oryginalny abstract (angielski)
BACKGROUND: Presurgical evaluation of drug-resistant focal epilepsy relies on multiple noninvasive tests, but their relative contributions to epileptogenic zone (EZ) localization and surgical prognosis remain uncertain, particularly in MRI-negative or otherwise challenging cases. Ictal-interictal SPECT analysis using SPM (ISAS) may improve localization, yet its role within a structured multimodal framework is not well defined. METHODS: We conducted a single-center retrospective cohort study of 25 patients with drug-resistant focal epilepsy who underwent comprehensive presurgical evaluation and ablation surgery with 2-year follow-up. All patients had seizure semiology, MRI, interictal and ictal scalp EEG, 99mTc-ECD interictal and ictal SPECT, and ISAS. Concordance was assessed against the predicted EZ (multimodal ± invasive EEG), while sensitivity, specificity, PPV, and NPV were calculated against the outcome-defined EZ (Engel I-II at 2 years). A logistic regression model combined MRI, interictal EEG, ictal EEG, and ISAS concordance into a weighted multimodal score predicting surgical success. RESULTS: Eighteen of 25 patients (72%) achieved Engel I-II outcomes. Sensitivity/specificity were 33%/57% for semiology, 16%/85% for MRI, 61%/71% for interictal EEG, 72%/57% for ictal EEG, 12%/100% for interictal SPECT, 55%/100% for ictal SPECT, and 81%/100% for ISAS, which also showed the highest NPV (70%). In the favorable-outcome group, ISAShad the highest EZ concordance, while all surgical failures had multifocal or nonlocalizable ISASpatterns. Using a multivariate logistic regression model, the derived prognostic scores demonstrated the highest predictive weight (regression coefficient) for ISAS concordance, intermediate weights for MRI and ictal EEG, and a minor weight for interictal EEG, yielding individualized probabilities of Engel I-II outcome. CONCLUSIONS: Quantitatively processed SPECT, interpreted with a structured algorithm, provided the strongest diagnostic and prognostic information among noninvasive modalities. The epilepsy surgery outcome model offers a transparent, reproducible tool for data-driven presurgical decision-making. Importantly, because SPECT is typically reserved for complex cases, this cohort is not representative of presurgical epilepsy cohorts in general.