Evidence map›Paper›PMID 38316622›Full record

ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2024

Comprehensive evaluation of magnetic resonance imaging sequences for signal intensity based assessment of anterior cruciate ligament healing following surgical treatment.

Shankar G Kaushal, Jin-Young Kim, Mallika Singh, Mo Han, Sean W Flannery, Dominique A Barnes, Kirsten Ecklund, Martha M Murray, Gary J Badger, Braden C Fleming and 1 more

Abstract read
In one paragraph

Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Pediatric ACL Injuries: A Current Concepts Review.Journal of clinical medicine · 2026
    Review
  3. Article
  4. 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

11 authors.

Shankar G KaushalDepartment of Orthopaedic Surgery and Sports Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-2727-7125
Jin-Young KimDepartment of Orthopaedic Surgery and Sports Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Mallika SinghDepartment of Orthopaedic Surgery and Sports Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-2640-7592
Mo HanDepartment of Orthopaedic Surgery and Sports Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Sean W FlanneryDepartment of Orthopedics, Rhode Island Hospital, Brown University, Providence, Rhode Island, USA.ORCID 0000-0003-0495-2626
Dominique A BarnesDepartment of Orthopedics, Rhode Island Hospital, Brown University, Providence, Rhode Island, USA.ORCID 0000-0003-4917-7854
Kirsten EcklundDepartment of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Martha M MurrayDepartment of Orthopaedic Surgery and Sports Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-5086-9511
Gary J BadgerDepartment of Medical Biostatistics, Larner College of Medicine, University of Vermont, Burlington, Vermont, USA.
Braden C FlemingDepartment of Orthopedics, Rhode Island Hospital, Brown University, Providence, Rhode Island, USA.ORCID 0000-0002-7841-425X
Ata M KiapourDepartment of Orthopaedic Surgery and Sports Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-7742-5769

Funding

Biologically Enhanced Healing of Autograft ACL Reconstruction.R01AR056834 · NIAMS · RHODE ISLAND HOSPITAL · PI FLEMING, BRADEN C, MURRAY, MARTHA M · 2009 to 2017
$5.8M
Non-invasive Assessment of Ligament Healing, in VivoR01AR065462 · NIAMS · RHODE ISLAND HOSPITAL · PI FLEMING, BRADEN C, MURRAY, MARTHA M · 2014 to 2016
$2.1M
NIAMS NIH HHS R01 AR056834NIAMS NIH HHS R01-AR056834NIAMS NIH HHS R01 AR065462NIAMS NIH HHS R01-AR065462
6 · The paper itself

Abstract

Normalized signal intensity (SI) obtained from magnetic resonance imaging (MRI) has been used to track anterior cruciate ligament (ACL) postoperative remodeling. We aimed to assess the effect of MRI sequence (PD: proton density-weighted; T2: T2-weighted; CISS: constructive interference in steady state) on postoperative changes in healing ACLs/grafts. We hypothesized that CISS is better at detecting longitudinal SI and texture changes of the healing ACL/graft compared to the common clinical sequences (PD and T2). MR images of patients who underwent ACL surgery were evaluated and separated into groups based on surgical procedure (Bridge-Enhanced ACL Repair (BEAR; n = 50) versus ACL reconstruction (ACLR; n = 24)). CISS images showed decreasing SI across all timepoints in both the BEAR and ACLR groups (p < 0.01), PD and T2 images showed decreasing SI in the 6-to-12- and 12-to-24-month postoperative timeframes in the BEAR group (p < 0.02), and PD images additionally showed decreasing SI between 6- and 24-months postoperation in the ACLR group (p = 0.02). CISS images showed texture changes in both the BEAR and ACLR groups, showing increases in energy and decreases in entropy in the 6-to-12- and 6-to-24-month postoperative timeframes in the BEAR group (p

Indexed as

Anterior Cruciate LigamentAnterior Cruciate Ligament ReconstructionMagnetic Resonance ImagingAdolescentAdultAnterior Cruciate Ligament InjuriesFemaleHumansMaleRetrospective StudiesWound HealingYoung Adultanterior cruciate ligamentconstructive interference in steady statemagnetic resonance imagingsignal intensitytexture analysis

Identifiers

PMID38316622
PMCPMC12121851

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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.