Evidence map›Paper›PMID 26396634›Full record

ArticleNuclear medicine and molecular imaging2014

Tumor SUVmax Normalized to Liver Uptake on (18)F-FDG PET/CT Predicts the Pathologic Complete Response After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

Jihyun Park, Kyoung Jin Chang, Young Seok Seo, Byung Hyun Byun, Joon Ho Choi, Hansol Moon, Ilhan Lim, Byung Il Kim, Chang Woon Choi, Sang Moo Lim

Open access · bronzeAbstract read
In one paragraph

Article in Nuclear medicine and molecular imaging, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 29% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Meta-analysis of [European radiology · 2025
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  3. Development and validation of anAnnals of nuclear medicine · 2025
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  13. Improving the Prognostic Performance of SUVJournal of clinical medicine · 2020
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  18. Observational
  19. Elevated tumor-to-liver uptake ratio (TLR) fromEuropean journal of nuclear medicine and molecular imaging · 2017
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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

10 authors at 1 institution in 1 country.

Jihyun ParkDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Kyoung Jin ChangDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Young Seok SeoDepartment of Radiation Oncology, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Byung Hyun ByunDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Joon Ho ChoiDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Hansol MoonDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Ilhan LimDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Byung Il KimDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Chang Woon ChoiDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Sang Moo LimDepartment of Nuclear Medicine, Korea Cancer Center Hospital, 75, Nowon-ro, Nowon-gu, Seoul, 139-706 Republic of Korea.
Korea Institute of Radiological and Medical Sciences · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study investigates the feasibility of using (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) to predict the pCR (pathologic complete response) rate after neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced rectal cancer.

methodsA total of 88 patients with locally advanced rectal cancer were retrospectively analyzed. All patients were treated with NCRT, followed by radical surgery, and (18)F-FDG PET/CT was performed before and after NCRT. For a semiquantitative assessment, a volume of interest was drawn, including the whole tumor region, and the maximum SUV (SUVmax), SUVmax normalized to liver uptake (SLR), SUVmax normalized to blood pool uptake (SBR), the metabolic tumor volume at SUV 2.0 (MTV[2.0]), SUV 2.5 (MTV[2.5]), and SUV 3.0 (MTV[3.0]) were measured. In addition, their percentage changes after NCRT were assessed. The pCR was verified through a histologic examination of postsurgical specimens. A receiver operating characteristic curve analysis was conducted to predict the pCR by using these PET parameters.

resultsThe pCR was predicted in 17 patients (19 %). The values of the area under the curve (AUC) for predicting the pCR were 0.774 for SUVmax after NCRT, 0.826 for SLR after NCRT, 0.815 for SBR after NCRT, 0.724 for MTV(2.5) after NCRT, 0.729 for the percentage change in SUVmax, 0.700 for the percentage change in SLR, and 0.749 for the percentage change in MTV (2.5). Among these PET parameters, SLR after NCRT showed the highest AUC value. The optimal criterion, sensitivity, specificity, and accuracy of SLR after NCRT for predicting the pCR were ≤1.41, 88 %, 65 %, and 68 %, respectively.

conclusionsF-FDG PET was found to be useful for predicting the pCR after NCRT in patients with locally advanced rectal cancer. Among various PET parameters, SUVmax normalized to liver uptake after NCRT was the best predictor of the pCR.

Indexed as

18F-FDGChemoradiotherapyPositron emission tomographyRectal CancerResponse

Identifiers

PMID26396634
PMCPMC4571668
OpenAlexW1987649732

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.