Evidence map›Paper›PMID 36719291›Full record

ArticleRadiology2023

Ablative Margins of Colorectal Liver Metastases Using Deformable CT Image Registration and Autosegmentation.

Yuan-Mao Lin, Iwan Paolucci, Caleb S O'Connor, Brian M Anderson, Bastien Rigaud, Bryan M Fellman, Kyle A Jones, Kristy K Brock, Bruno C Odisio

Open access · greenAbstract read
In one paragraph

Article in Radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 1 pooled it
14.1field-weighted citation impact, top 1% of its field
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

49 citing papers in PubMed, 1 synthesis or guideline pooled it, 70 citations in OpenAlex.

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  4. Estimation of tumor coverage after RF ablation of hepatocellular carcinoma using single 2D image slices.International journal of computer assisted radiology and surgery · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Yuan-Mao LinFrom the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.ORCID 0000-0002-0275-9593
Iwan PaolucciFrom the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.ORCID 0000-0002-9393-3015
Caleb S O'ConnorFrom the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.
Brian M AndersonFrom the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.ORCID 0000-0002-2748-1444
Bastien RigaudFrom the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.ORCID 0000-0002-0038-429X
Bryan M FellmanFrom the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.
Kyle A JonesFrom the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.ORCID 0000-0001-8245-8573
Kristy K Brock *From the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.ORCID 0000-0001-9364-5040
Bruno C Odisio *From the Departments of Interventional Radiology (Y.M.L., I.P., B.C.O.), Imaging Physics (C.S.O., B.M.A., B.R., K.A.J., K.K.B.), and Biostatistics (B.M.F.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.ORCID 0000-0002-1771-8233
The University of Texas MD Anderson Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
Optimization and Evaluation of Anatomical Models of Liver Radiation ResponseR01CA221971 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BROCK, KRISTY · 2018 to 2022
$1.8M
Anatomical Modeling to Improve the Precision of Image Guided Liver AblationR01CA235564 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BROCK, KRISTY, ODISIO, BRUNO C · 2019 to 2023
$1.7M
NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA221971NCI NIH HHS R01 CA235564
6 · The paper itself

Abstract

Background Confirming ablation completeness with sufficient ablative margin is critical for local tumor control following colorectal liver metastasis (CLM) ablation. An image-based confirmation method considering patient- and ablation-related biomechanical deformation is an unmet need. Purpose To evaluate a biomechanical deformable image registration (DIR) method for three-dimensional (3D) minimal ablative margin (MAM) quantification and the association with local disease progression following CT-guided CLM ablation. Materials and Methods This single-institution retrospective study included patients with CLM treated with CT-guided microwave or radiofrequency ablation from October 2015 to March 2020. A biomechanical DIR method with AI-based autosegmentation of liver, tumors, and ablation zones on CT images was applied for MAM quantification retrospectively. The per-tumor incidence of local disease progression was defined as residual tumor or local tumor progression. Factors associated with local disease progression were evaluated using the multivariable Fine-Gray subdistribution hazard model. Local disease progression sites were spatially localized with the tissue at risk for tumor progression (<5 mm) using a 3D ray-tracing method. Results Overall, 213 ablated CLMs (mean diameter, 1.4 cm) in 124 consecutive patients (mean age, 57 years ± 12 [SD]; 69 women) were evaluated, with a median follow-up interval of 25.8 months. In ablated CLMs, an MAM of 0 mm was depicted in 14.6% (31 of 213), from greater than 0 to less than 5 mm in 40.4% (86 of 213), and greater than or equal to 5 mm in 45.1% (96 of 213). The 2-year cumulative incidence of local disease progression was 72% for 0 mm and 12% for greater than 0 to less than 5 mm. No local disease progression was observed for an MAM greater than or equal to 5 mm. Among 117 tumors with an MAM less than 5 mm, 36 had local disease progression and 30 were spatially localized within the tissue at risk for tumor progression. On multivariable analysis, an MAM of 0 mm (subdistribution hazard ratio, 23.3; 95% CI: 10.8, 50.5;

Indexed as

Catheter AblationColorectal NeoplasmsLiver NeoplasmsDisease ProgressionFemaleHumansMiddle AgedRetrospective StudiesTomography, X-Ray ComputedTreatment Outcome

Identifiers

PMID36719291
PMCPMC10102669
OpenAlexW4318671232

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.