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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Related Experiment Video

Updated: Jun 20, 2026

Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling

Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling

Published on: May 31, 2024

Reference-based maximum upslope: a CBF quantification method without using arterial input function in dynamic

Tokunori Kimura¹, Hiroshi Kusahara

¹MRI Systems Development Department, MRI Systems Division, Toshiba Medical Systems Corporation, Systems Group, Otawara, Tochigi, Japan. kimura@mr.nasu.toshiba.co.jp

Magnetic Resonance in Medical Sciences : MRMS : an Official Journal of Japan Society of Magnetic Resonance in Medicine

|September 29, 2009

Summary

A new reference-based method for cerebral blood flow (CBF) assessment in dynamic susceptibility contrast MRI significantly reduces errors without needing an arterial input function. This technique is robust and practical for acute stroke patients.

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Last Updated: Jun 20, 2026

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Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

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Published on: January 7, 2021

Area of Science:

Neuroimaging
Medical Physics
Radiology

Background:

Dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) is crucial for assessing cerebral blood flow (CBF).
Traditional DSC-MRI methods often rely on arterial input function (AIF) measurements, which can be challenging and introduce errors.
Accurate CBF quantification is vital for diagnosing and managing neurological conditions, particularly acute stroke.

Purpose of the Study:

To evaluate the accuracy of a novel reference-based method for calculating CBF in DSC-MRI.
To assess the errors associated with this method when the arterial input function (AIF) is not used.
To compare the performance of the reference-based method against traditional deconvolution and non-deconvolution techniques.

Main Methods:

Cerebral blood flow (CBF) and cerebral blood flow ratio (CBFratio) were calculated using numerical simulations.
Methods included three non-deconvolution techniques (e.g., maximum upslope) and a deconvolution method (block-circulant singular value decomposition - cSVD).
Error analysis was performed with and without simulated noise, considering parameters like mean transit time (MTT), AIF delay, and temporal resolution, using clinical DSC-MRI data.

Main Results:

The reference-based maximum upslope (Ref-US) method demonstrated the smallest errors in CBFratio, outperforming even the cSVD method.
Ref-US showed greater robustness against AIF noise and coarse temporal resolution compared to cSVD, with comparable robustness against transit delay.
Pixel-by-pixel correlations between Ref-US and cSVD-CBF maps were high (r > 0.9), indicating good visual agreement.

Conclusions:

The reference-based upslope (Ref-US) technique offers a practical alternative for DSC-MRI perfusion assessment without AIF measurement.
This method balances robustness against systematic and random errors, making it suitable for patients with acute stroke.
The simplicity of the Ref-US technique facilitates its implementation in clinical settings.