Nakyoung Kim

Seoul, Republic of Korea

Last Updated: 09/26/2026

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Found 17 publications

Pathology-validated structural and physiologic habitat imaging for differentiating radiation necrosis from tumor recurrence in brain metastases.

Pathology-validated structural and physiologic habitat imaging for differentiating radiation necrosis from tumor recurrence in brain metastases.

Journal: Journal of neuro-oncology

Published: June 17, 2026

A deep learning-based model for postoperative resection assessment in glioblastoma: A comparative study.

A deep learning-based model for postoperative resection assessment in glioblastoma: A comparative study.

Journal: Neurosurgical review

Published: September 29, 2025

Prospective longitudinal analysis of physiologic MRI-based tumor habitat predicts short-term patient outcomes in IDH-wildtype glioblastoma.

Prospective longitudinal analysis of physiologic MRI-based tumor habitat predicts short-term patient outcomes in IDH-wildtype glioblastoma.

Journal: Neuro-oncology

Published: October 25, 2024

Mapping tumor habitats in isocitrate dehydrogenase -wild type glioblastoma: Integrating MRI, pathologic, and RNA data from the Ivy Glioblastoma Atlas Project.

Mapping tumor habitats in isocitrate dehydrogenase -wild type glioblastoma: Integrating MRI, pathologic, and RNA data from the Ivy Glioblastoma Atlas Project.

Journal: Neuro-oncology

Published: August 23, 2024

Correction: Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

Correction: Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society

Published: March 22, 2024

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society

Published: October 25, 2023

Prospective longitudinal analysis of imaging-based spatiotemporal tumor habitats in glioblastoma, IDH-wild type: implication in patient outcome using multiparametric physiologic MRI.

Prospective longitudinal analysis of imaging-based spatiotemporal tumor habitats in glioblastoma, IDH-wild type: implication in patient outcome using multiparametric physiologic MRI.

Journal: BMC cancer

Published: August 27, 2023

Reducing false positives in deep learning-based brain metastasis detection by using both gradient-echo and spin-echo contrast-enhanced MRI: validation in a multi-center diagnostic cohort.

Reducing false positives in deep learning-based brain metastasis detection by using both gradient-echo and spin-echo contrast-enhanced MRI: validation in a multi-center diagnostic cohort.

Journal: European radiology

Published: April 24, 2023

Deep learning-based detection and quantification of brain metastases on black-blood imaging can provide treatment suggestions: a clinical cohort study.

Deep learning-based detection and quantification of brain metastases on black-blood imaging can provide treatment suggestions: a clinical cohort study.

Journal: European radiology

Published: January 17, 2023

Prediction of pseudoprogression in post-treatment glioblastoma using dynamic susceptibility contrast-derived oxygenation and microvascular transit time heterogeneity measures.

Prediction of pseudoprogression in post-treatment glioblastoma using dynamic susceptibility contrast-derived oxygenation and microvascular transit time heterogeneity measures.

Journal: European radiology

Published: September 01, 2022

Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis.

Tumor Habitat Analysis Using Longitudinal Physiological MRI to Predict Tumor Recurrence After Stereotactic Radiosurgery for Brain Metastasis.

Journal: Korean journal of radiology

Published: July 21, 2022

Vessel size and perfusion-derived vascular habitat refines prediction of treatment failure to bevacizumab in recurrent glioblastomas: validation in a prospective cohort.

Vessel size and perfusion-derived vascular habitat refines prediction of treatment failure to bevacizumab in recurrent glioblastomas: validation in a prospective cohort.

Journal: European radiology

Published: April 18, 2022

Showing 1-12 of 17

Last Updated: 09/26/2026