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Neurooncol Adv
Neurooncol Adv
noa
Neuro-Oncology Advances
2632-2498
Oxford University Press US

10.1093/noajnl/vdae090.063
vdae090.063
Final Category: Neuroimaging/Radiologic Advances
AcademicSubjects/MED00300
AcademicSubjects/MED00310
NIRL-01 DEEP LEARNING-BASED VOLUMETRIC SEGMENTATION ENABLES RESPONSE ASSESSMENT AFTER LASER INTERSTITIAL THERMAL THERAPY
Haskell-Mendoza Aden Duke University School of Medicine, Durham, NC, USA

Reason Ellery Duke University School of Medicine, Durham, NC, United States Minor Outlying Islands

Gonzalez Ariel Duke University School of Medicine, Durham, NC, USA

Jackson Joshua Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA

Sankey Eric Piedmont Athens Regional Medical Center, Athens, GA, USA

Srinivasan Ethan Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, MD, USA

II James Herndon Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA

Fecci Peter Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA

Calabrese Evan Department of Radiology, Duke University Medical Center, Durham, NC, USA

8 2024
02 8 2024
02 8 2024
6 Suppl 1 2024 SNO/ASCO CNS Metastases Conference i20i20
© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

Abstract

BACKGROUND

Laser interstitial thermal therapy (LITT) allows for definitive tissue diagnosis, surgical cytoreduction, and faster post-operative return to systemic therapies for patients with brain tumors or radiation necrosis. Ablated tissue remains in situ following LITT, resulting in characteristic post-LITT lesion expansion. Post-LITT edema may be associated with transient clinical worsening and complicates subsequent response assessment.

METHODS

All patients receiving LITT at a single center for tumors or radiation necrosis from 2015 – 2023 with ≥ 9 months of MRI follow-up were retrospectively reviewed. A 3D U-net segmentation model implemented in nnU-Net was developed for automated segmentation of Contrast-enhancing Lesion Volume (CeLV) of LITT-treated lesions on T1-weighted post-contrast MR images. CeLVs were analyzed to establish volumetric post-LITT response assessments.

RESULTS

Sixty-one LITT-treated lesions and 6 control cases of medically-managed radiation necrosis were analyzed across 384 unique MRI exams. Automated segmentation was qualitatively accurate in 367/384 (95.6%) images. CeLV increased to a median of 68.3% (IQR 35.1 – 109.2%) from baseline at 1 – 3 months from LITT (P = 0.0012) and subsequently returned to baseline. Median overall survival (mOS) for LITT-treated patients was 39.1 (9.2 – 93.4) months. Using previously established volumetric thresholds, volumetric disease progression was defined as lesion expansion ≥ 40% from volumetric nadir or baseline. Twenty-one of 56 (37.5%) patients experienced volumetric progression with a progression-free survival of 21.4 (6.0 – 93.4) months. Patients with volumetric progression had lower mOS (17.3 vs 62.1 months, P = 0.0015).

CONCLUSION

We observed a nearly 70% increase in CeLV at 1 – 3 months post-LITT, which characteristically resolved within 6 months of the procedure. Development of response assessment criteria that account for transient post-LITT lesion expansion is feasible and should be considered for clinical trials. Automated lesion segmentation may facilitate adoption of volumetric response assessment into clinical practice.
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