Advances in Diffusion and Perfusion MRI for Quantitative Cancer Imaging.

Curr Pathobiol Rep

Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA.

Published: December 2019

AI Article Synopsis

  • The article reviews recent advancements in cancer imaging that enhance the quantitative measurement of tumors' cellular and vascular characteristics.
  • Fast Magnetic Resonance Imaging (MRI) technologies have enabled new methods to simultaneously assess these properties, especially through techniques like diffusion MRI (dMRI) and dynamic contrast-enhanced MRI (DCE-MRI).
  • The review highlights that while these imaging techniques are valuable, their full potential in measuring tumor characteristics such as perfusion and membrane permeability has yet to be realized, prompting discussions on concepts and future developments.

Article Abstract

Purpose Of Review: This article is to review recent technical developments and their clinical applications in cancer imaging quantitative measurement of cellular and vascular properties of the tumors.

Recent Findings: Rapid development of fast Magnetic Resonance Imaging (MRI) technologies over last decade brought new opportunities in quantitative MRI methods to measure both cellular and vascular properties of tumors simultaneously.

Summary: Diffusion MRI (dMRI) and dynamic contrast enhanced (DCE)-MRI have become widely used to assess the tissue structural and vascular properties, respectively. However, the ultimate potential of these advanced imaging modalities has not been fully exploited. The dependency of dMRI on the diffusion weighting gradient strength and diffusion time can be utilized to measure tumor perfusion, cellular structure, and cellular membrane permeability. Similarly, DCE-MRI can be used to measure vascular and cellular membrane permeability along with cellular compartment volume fractions. To facilitate the understanding of these potentially important methods for quantitative cancer imaging, we discuss the basic concepts and recent developments, as well as future directions for further development.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747414PMC
http://dx.doi.org/10.1007/s40139-019-00204-7DOI Listing

Publication Analysis

Top Keywords

cancer imaging
12
vascular properties
12
quantitative cancer
8
cellular vascular
8
cellular membrane
8
membrane permeability
8
cellular
6
imaging
5
advances diffusion
4
diffusion perfusion
4

Similar Publications

Background: To develop and validate a clinical-radiomics model for preoperative prediction of lymphovascular invasion (LVI) in rectal cancer.

Methods: This retrospective study included data from 239 patients with pathologically confirmed rectal adenocarcinoma from two centers, all of whom underwent MRI examinations. Cases from the first center (n = 189) were randomly divided into a training set and an internal validation set at a 7:3 ratio, while cases from the second center (n = 50) constituted the external validation set.

View Article and Find Full Text PDF

[A Review of progresses in research on delayed resistance to EGFR-TKI by Traditional Chinese medicine via inhibiting cancer stem cells properties].

Xi Bao Yu Fen Zi Mian Yi Xue Za Zhi

January 2025

Department of Integrated Traditional Chinese and Western Medicine, Shandong First Medical University Affiliated Cancer Hospital, Jinan 250117, China. *Corresponding author, E-mail:

It has been popular and challenging to undertake researches on the delay of acquired resistance of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI). As key cells for tumor initiation, cancer stem cells (CSC) play an important role in the process of resistance to EGFR-TKI. Although preliminary studies found that traditional Chinese medicine (TCM) could inhibit CSC properties and delay EGFR-TKI resistance, the specific molecular mechanism remains unclear.

View Article and Find Full Text PDF
Article Synopsis
  • Deep learning methods show strong potential for predicting lung cancer risk from CT scans, but there's a need for more comprehensive comparisons and validations of these models in real-world settings.
  • The study reviews 21 state-of-the-art deep learning models, analyzing their performance using CT scans from a subset of the National Lung Screening Trial, with a focus on malignant versus benign classification.
  • Results reveal that 3D deep learning models generally outperformed 2D models, with the best 3D model achieving an AUROC of 0.86 compared to 0.79 for the best 2D model, emphasizing the need to choose appropriate pretrained datasets and model types for effective lung cancer risk prediction.
View Article and Find Full Text PDF

Can parenchymal volume analysis replace nuclear renal scans for split renal function before and after partial nephrectomy with warm ischemia?

Urol Oncol

January 2025

Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China; State Key Laboratory of Oncology in Southern China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, China; State Key Laboratory of Oncology in Southern China, Guangzhou, P. R. China. Electronic address:

Article Synopsis
  • The study evaluates parenchymal volume analysis (PVA) as a potential alternative to nuclear renal scan (NRS) for assessing split renal function (SRF) before and after partial nephrectomy (PN) with warm ischemia.
  • Preoperatively, PVA showed a strong correlation with NRS findings, indicating its reliability for SRF assessment (49.4% vs. 50.0%, P = .501).
  • Results suggest that while PVA is consistent with NRS preoperatively, the efficacy of PVA remains uncertain for post-operative SRF evaluation after PN, indicating a need for further investigation.
View Article and Find Full Text PDF

A Radiomic-Clinical Model of Contrast-Enhanced Mammography for Breast Cancer Biopsy Outcome Prediction.

Acad Radiol

January 2025

Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 (C.L., S.W.); Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 (D.A., M.Z., J.S., S.W.); Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15213 (S.W.); Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA 15213 (S.W.). Electronic address:

Rationale And Objectives: In the USA over 1 million breast biopsies are performed annually. Approximately 9.6% diagnostic exams were given Breast Imaging Reporting and Data System (BI-RADS) ≥4A, most of which are 4A/4B.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!