paper-with-me

Papers

Quantitative characterization of the imaging limits of diffuse low-grade oligodendrogliomas

2018-03-23

Background : Supratentorial diffuse low-grade gliomas in adults extend beyond maximal visible MRI-defined abnormalities, and a gap exists between the imaging signal changes and the actual tumor margins. Direct quantitative comparisons between imaging and histological analyses are lacking to date. However, they are of the utmost importance if one wishes to develop realistic models for diffuse glioma growth. Methods : In this study, we quantitatively compare the cell concentration and the edema fraction from human histological biopsy samples (BSs) performed inside and outside imaging abnormalities during serial imaging-based stereotactic biopsy of diffuse low-grade gliomas. Results : The cell concentration was significantly higher in BSs located inside (1189 $\pm$ 378 cell/mm$^2$) than outside (740 $\pm$ 124 cell/mm$^2$) MRI-defined abnormalities (p=0.0003). The edema fraction was significantly higher in BSs located inside (mean, 45 $\pm$ 23%) than outside (mean, 5 $\pm$ 9%) MRI-defined abnormalities (p<0.0001). At borders of the MRI-defined abnormalities, 20% of the tissue surface area was occupied by edema, and only 3% by tumor cells. The cycling cell concentration was significantly higher in BSs located inside (10 $\pm$ 12 cell/mm$^2$) compared to outside (0.5 $\pm$ 0.9 cell/mm$^2$) MRI-defined abnormalities (p=0.0001). Conclusions : We show that the margins of T2-weighted signal changes are mainly correlated with the edema fraction. In 62.5% of patients, the cycling tumor cell fraction (defined as the ratio of the cycling tumor cell concentration to the total number of tumor cells) was higher at the limits of the MRI-defined abnormalities than closer to the center of the tumor. In the remaining patients, the cycling tumor cell fraction increased towards the center of the tumor.

📄 PDF Abstract BibTeX arXiv:1803.09005

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

The University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) Dataset

2021-08-30 · Evan Calabrese, Javier E. Villanueva-Meyer, Jeffrey D. Rudie, Andreas M. Rauschecker 외

Here we present the University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) dataset. The UCSF-PDGM dataset includes 500 subjects with histopathologically-proven diffuse gliomas who were imaged …

MicroDiffuse3D: A Foundation Model for 3D Microscopy Imaging Restoration

2026-05-08 · Yongkang Li, Brian Wong, King Wai Chiu, Hanwen Xu 외 arxiv

Chemical imaging enables label-free visualization of cells, tissues and living systems while providing direct biochemical information that is difficult to obtain with conventional fluorescence microscopy. Despite its pro…

Image Restoration

High Resolution, Deep Imaging Using Confocal Time-of-flight Diffuse Optical Tomography

2021-01-27 · Yongyi Zhao, Ankit Raghuram, Hyun K. Kim, Andreas H. Hielscher 외

Light scattering by tissue severely limits how deep beneath the surface one can image, and the spatial resolution one can obtain from these images. Diffuse optical tomography (DOT) is one of the most powerful techniques …

Vocal Bursts Intensity Prediction

Sharp images from diffuse beams: factorisation of the discrete delta function

2019-11-21

Discrete delta functions define the limits of attainable spatial resolution for all imaging systems. Here we construct broad, multi-dimensional discrete functions that replicate closely the action of a Dirac delta functi…

Analysis of Diffractive Neural Networks for Seeing Through Random Diffusers

2022-05-01 · Yuhang Li, Yi Luo, Bijie Bai, Aydogan Ozcan

Imaging through diffusive media is a challenging problem, where the existing solutions heavily rely on digital computers to reconstruct distorted images. We provide a detailed analysis of a computer-free, all-optical ima…

Autonomous DrivingImage Reconstruction