Evidence map›Paper›PMID 39181479›Full record

ArticleMagnetic resonance imaging2024

Longitudinal registration of T

Michelle W Tong, Hon J Yu, Maren M Sjaastad Andreassen, Stephane Loubrie, Ana E Rodríguez-Soto, Tyler M Seibert, Rebecca Rakow-Penner, Anders M Dale

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Magnetic resonance imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. GuidedMorph: Two-Stage Deformable Registration for Breast MRI.IEEE journal of biomedical and health informatics · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Michelle W TongDepartment of Bioengineering, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA. Electronic address: mwtong@ucsd.edu.
Hon J YuDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Maren M Sjaastad AndreassenSection of Oncology, Drammen Hospital, Vestre Viken Hospital Trust, Drammen, Norway.
Stephane LoubrieDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Ana E Rodríguez-SotoDepartment of Bioengineering, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA.
Tyler M SeibertDepartment of Bioengineering, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Radiation Medicine, University of California San Diego, La Jolla, CA, USA.
Rebecca Rakow-PennerDepartment of Bioengineering, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA.
Anders M DaleDepartment of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.

Funding

Advanced diffusion MRI for evaluating early response to radiation treatment in cervical cancerR37CA249659 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Rebecca Ann Rakow-Penner · 2021 to 2026
$3.8M
NCI NIH HHS R37 CA249659
6 · The paper itself

Abstract

purposeMRI is commonly used to aid breast cancer diagnosis and treatment evaluation. For patients with breast cancer, neoadjuvant chemotherapy aims to reduce the tumor size and extent of surgery necessary. The current clinical standard to measure breast tumor response on MRI uses the longest tumor diameter. Radiologists also account for other tissue properties including tumor contrast or pharmacokinetics in their assessment. Accurate longitudinal image registration of breast tissue is critical to properly compare response to treatment at different timepoints.

methodsIn this study, a deformable Fast Longitudinal Image Registration (FLIRE) algorithm was optimized for breast tissue. FLIRE was then compared to the publicly available software packages with high accuracy (DRAMMS) and fast runtime (Elastix). Patients included in the study received longitudinal T

resultsAlignment and runtime performance were compared using two-way repeated measure ANOVAs (P < 0.05). Across all patients, Pearson's correlation coefficient across the entire image volume was slightly higher with statistical significance and had less variance for FLIRE (0.98 ± 0.01 stdev) compared to DRAMMS (0.97 ± 0.03 stdev) and Elastix (0.95 ± 0.03 stdev). Additionally, FLIRE runtime (10.0 mins) was 9.0 times faster than DRAMMS (89.6 mins) and 1.5 times faster than Elastix (14.5 mins) on a Linux workstation.

conclusionFLIRE demonstrates promise for time-sensitive clinical applications due to its accuracy, robustness across patients and timepoints, and speed.

Indexed as

AlgorithmsBreastBreast NeoplasmsMagnetic Resonance ImagingAdultAgedFemaleHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedLongitudinal StudiesMiddle AgedNeoadjuvant TherapyReproducibility of ResultsSoftwareBreastLongitudinalNeoadjuvant chemotherapyNon-linearRegistrationT(1)

Identifiers

PMID39181479
PMCPMC11921785

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.