Evidence map›Paper›PMID 39211555›Full record

ArticleFrontiers in oncology2024

Assessment of pathological grade and variants of bladder cancer with a continuous-time random-walk diffusion model.

Wei Wang, Jingyun Wu, Qi Shen, Wei Li, Ke Xue, Yuxin Yang, Jianxing Qiu

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

  1. The Stalk Sign in Bladder Cancer: CEUS Versus MRI.Diagnostics (Basel, Switzerland) · 2026
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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

7 authors.

Wei WangDepartment of Radiology, Peking University First Hospital, Beijing, China.
Jingyun WuDepartment of Radiology, Peking University First Hospital, Beijing, China.
Qi ShenDepartment of Urology, Peking University First Hospital, Institute of Urology, National Research Center for Genitourinary Oncology, Peking University, Beijing, China.
Wei LiDepartment of Radiology, Peking University First Hospital, Beijing, China.
Ke XueMR Collaboration, United Imaging Research Institute of Intelligent Imaging, Beijing, China.
Yuxin YangMR Collaboration, United Imaging Research Institute of Intelligent Imaging, Beijing, China.
Jianxing QiuDepartment of Radiology, Peking University First Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To evaluate the efficacy of high b-value diffusion-weighted imaging (DWI) with a continuous-time random-walk (CTRW) diffusion model in determining the pathological grade and variant histology (VH) of bladder cancer (BCa). Methods: A total of 81 patients (median age, 70 years; range, 35-92 years; 18 females; 66 high grades; 30 with VH) with pathologically confirmed bladder urothelial carcinoma were retrospectively enrolled and underwent bladder MRI on a 3.0T MRI scanner. Multi-b-value DWI was performed using 11 b-values. Three CTRW model parameters were obtained: an anomalous diffusion coefficient (D) and two parameters reflecting temporal (α) and spatial (β) diffusion heterogeneity. The apparent diffusion coefficient (ADC) was calculated using b0 and b800. D, α, β, and ADC were statistically compared between high- and low-grade BCa, and between pure urothelial cancer (pUC) and VH. Comparisons were made using the Mann-Whitney U test between different pathological states. Receiver operating characteristic curve analysis was used to assess performance in differentiating the pathological states of BCa. Results: ADC, D, and α were significantly lower in high-grade BCa compared to low-grade, and in VH compared to pUC (p < 0.001), while β showed no significant differences (p > 0.05). The combination of D and α yielded the best performance for determining BCa grade and VH (area under the curves = 0.913, 0.811), significantly outperforming ADC (area under the curves = 0.823, 0.761). Conclusion: The CTRW model effectively discriminated pathological grades and variants in BCa, highlighting its potential as a noninvasive diagnostic tool.

Indexed as

diffusion magnetic resonance imagingneoplasm gradingpathologytumor microenvironmenturinary bladder neoplasms

Identifiers

PMID39211555
PMCPMC11357921

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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.