Evidence map›Paper›PMID 34281566›Full record

ArticleRadiation oncology (London, England)2021

Diffusion-weighted MRI and

Xin Xu, Zhi-Yong Sun, Hua-Wei Wu, Chen-Peng Zhang, Bin Hu, Ling Rong, Hai-Yan Chen, Hua-Ying Xie, Yu-Ming Wang, Hai-Ping Lin and 3 more

Abstract read
In one paragraph

Article in Radiation oncology (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. IncreasedSkeletal radiology · 2023
    Article
  9. Article
  10. Review
  11. 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

13 authors.

Xin Xu *Department of Radiation Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Zhi-Yong Sun *Department of Thoracic Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Hua-Wei WuDepartment of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Chen-Peng ZhangDepartment of Nuclear Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Bin HuDepartment of Radiation Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Ling RongDepartment of Radiation Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Hai-Yan ChenDepartment of Radiation Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Hua-Ying XieDepartment of Radiation Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Yu-Ming WangDepartment of Thoracic Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Hai-Ping LinDepartment of Thoracic Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Yong-Rui BaiDepartment of Radiation Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
Qing YeDepartment of Thoracic Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China. renjiyeqing@163.com.
Xiu-Mei MaDepartment of Radiation Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China. sallyma@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeoadjuvant chemoradiotherapy (nCRT) followed by surgery is a currently widely used strategy for locally advanced esophageal cancer (EC). However, the conventional imaging methods have certain deficiencies in the evaluation and prediction of the efficacy of nCRT. This study aimed to explore the value of functional imaging in predicting the response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced esophageal squamous cell carcinoma (ESCC).

methodsFifty-four patients diagnosed with locally advanced ESCC from August 2017 to September 2019 and treated with nCRT were retrospectively analyzed. DW-MRI scanning was performed before nCRT, at 10-15 fractions of radiotherapy, and 4-6 weeks after the completion of nCRT.

resultsA total of 8 of 54 patients (14.8%) were evaluated as disease progression in the preoperative assessment. The remaining forty-six patients underwent operations, and the pathological assessments of the surgical resection specimens demonstrated pathological complete response (pCR) in 10 patients (21.7%) and complete response of primary tumor (pCR-T) in 16 patients (34.8%). The change of metabolic tumor volume (∆MTV) and change of total lesion glycolysis (∆TLG) were significantly different between patients with pCR and non-pCR. The SUVmax-T

conclusion

Indexed as

ChemoradiotherapyDiffusion Magnetic Resonance ImagingEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaFemaleFluorodeoxyglucose F18HumansMaleMiddle AgedNeoadjuvant TherapyPositron Emission Tomography Computed TomographyPrognosisRadiopharmaceuticalsRetrospective StudiesROC CurveTumor BurdenFluorodeoxyglucose F18Radiopharmaceuticals18F-FDG PET/CTDW-MRIEsophageal squamous cell cancerNeoadjuvant chemoradiotherapyPathological complete response

Identifiers

PMID34281566
PMCPMC8287821

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.