Evidence map›Paper›PMID 42682154›Full record

ArticleJournal of applied clinical medical physics2026

Empirical noise mapping guides optimal region-of-interest selection for accurate noise estimation in prostate DWI.

Milica Medved, Aritrick Chatterjee, Ambereen Yousuf, Batuhan Gundogdu, Aytekin Oto, Gregory S Karczmar

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Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Milica MedvedDepartment of Radiology, The University of Chicago, Chicago, Illinois, USA.ORCID https://orcid.org/0000-0003-2945-5511
Aritrick ChatterjeeDepartment of Radiology, The University of Chicago, Chicago, Illinois, USA.
Ambereen YousufDepartment of Radiology, The University of Chicago, Chicago, Illinois, USA.
Batuhan GundogduData Science Institute, The University of Chicago, Chicago, Illinois, USA.
Aytekin OtoDepartment of Radiology, The University of Chicago, Chicago, Illinois, USA.
Gregory S KarczmarDepartment of Radiology, The University of Chicago, Chicago, Illinois, USA.

Funding

Detection of prostate Cancer Specific Signals with Hybrid Multi-Dimensional MRIR01CA228036 · NCI · UNIVERSITY OF CHICAGO · PI KARCZMAR, GREGORY S., OTO, AYTEKIN · 2019 to 2023
$2.7M
Quantitative DCEMRI of Prostate Cancer Correlation with Gold StandardsR01CA172801 · NCI · UNIVERSITY OF CHICAGO · PI KARCZMAR, GREGORY S., OTO, AYTEKIN · 2013 to 2017
$2.3M
3T MRI Scanner for multidisciplinary imaging and image-guided therapyS10OD018448 · OD · UNIVERSITY OF CHICAGO · PI KARCZMAR, GREGORY S. · 2014 to 2014
$2.0M
NCI NIH HHS R01 CA172801NCI NIH HHS R01CA172801NCI NIH HHS R01 CA228036NCI NIH HHS R01CA228036NIH HHS S10 OD018448NIH HHS S10OD018448University of Chicago Comprehensive Cancer Center
6 · The paper itself

Abstract

backgroundSignal-to-noise ratio (SNR) measurements are important for quality assurance, especially when quantitative MRI markers or new hardware are being developed or evaluated. Regions of low signal or assumed uniform signal are used for SNR estimation in a variety of MR image types, but this is unreliable due to spatial heterogeneity of noise arising from the organization of multiple-detector arrays and sensitivity encoding (SENSE) reconstruction. PURPOSE: We present a universally applicable method for empirical noise mapping by propagating simulated noise through the image-generating reconstruction pipeline, to identify optimal regions of interest (ROIs) for determining noise levels in prostate diffusion-weighted imaging (DWI).

methodsThirty-six men were imaged at 3T with DWI. K-space data were propagated through an off-line reconstruction pipeline including sensitivity encoding (SENSE), to generate DW images. Simulated complex Gaussian noise generated from prescan per-channel measurements was similarly processed to produce pure noise maps. Per-voxel standard deviations (SD) of spatial distributions of noise, averaged over prostate, internal obturator muscle (IOM), low signal (anterior and posterior), rectum, and bladder ROIs were calculated and compared to evaluate suitability for SNR estimation in prostate DWI.

resultsIOM ROI noise levels, averaged bilaterally, were not significantly different from those in the prostate. Bladder ROI noise levels were comparable. Noise levels measured in low signal areas were highly dependent on SENSE algorithm regularization strength. DISCUSSION: The proposed method can be used-on any scanner-to accurately calculate noise levels in MR images, without repeated acquisition or interference from SENSE use.

conclusionBladder and averaged IOM ROIs are appropriate for estimating DWI noise levels in the prostate. Low signal ROIs should not be used, due to the strong dependence on the SENSE regularization strength, and by extension, on the SENSE reconstruction algorithm. The presented method can be used instead to obtain accurate spatial maps of noise levels.

Indexed as

AlgorithmsDiffusion Magnetic Resonance ImagingImage Processing, Computer-AssistedProstateProstatic NeoplasmsSignal-To-Noise RatioHumansMaleMiddle Ageddiffusion‐weighted imaging (DWI)electronic noiseimage reconstructionmagnetic resonance imaging (MRI)prostate cancer

Identifiers

PMID42682154
PMCPMC13535670

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.