Evidence map›Paper›PMID 38688633›Full record

ArticleIn vivo (Athens, Greece)

Identification and Quantification of Radiotherapy-related Protein Expression in Cancer Tissues Using the Qupath Software and Prediction of Treatment Response.

Tomokazu Hasegawa, Masanori Someya, Takaaki Tsuchiya, Mio Kitagawa, Yuki Fukushima, Toshio Gocho, Shoh Mafune, Ryuu Okuda, Juno Kaguchi, Atsuya Ohguro and 6 more

Abstract read
In one paragraph

Article in In vivo (Athens, Greece). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Digital pathology in tau research: A comparison of QuPath and HALO.Journal of neuropathology and experimental neurology · 2025
    Article
  2. Article
  3. 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

16 authors.

Tomokazu HasegawaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan; hasse@sapmed.ac.jp.
Masanori SomeyaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Takaaki TsuchiyaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Mio KitagawaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Yuki FukushimaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Toshio GochoDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Shoh MafuneDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Ryuu OkudaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Juno KaguchiDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Atsuya OhguroDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Ryo KamiyamaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Ayato AshinaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Yuka ToshimaDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Yoshihiko HirohashiDepartment of Pathology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Toshihiko TorigoeDepartment of Pathology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Koh-Ichi SakataDepartment of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimAutomated measurement of immunostained samples can enable more convenient and objective prediction of treatment outcome from radiotherapy. We aimed to validate the performance of the QuPath image analysis software in immune cell markers detection by comparing QuPath cell counting results with those of physician manual cell counting. PATIENTS AND

methodsCD8- and FoxP3-stained cervical, CD8-stained oropharyngeal, and Ku70-stained prostate cancer tumor sections were analyzed in 104 cervical, 92 oropharyngeal, and 58 prostate cancer patients undergoing radiotherapy at our Institution.

resultsQuPath and manual counts were highly correlated. When divided into two groups using ROC curves, the agreement between QuPath and manual counts was 89.4% for CD8 and 88.5% for FoxP3 in cervical cancer, 87.0% for CD8 in oropharyngeal cancer and 80.7% for Ku70 in prostate cancer. In cervical cancer, the high CD8 group based on QuPath counts had a better prognosis and the low CD8 group had a significantly worse prognosis [p=0.0003; 5-year overall survival (OS), 65.9% vs. 34.7%]. QuPath counts were more predictive than manual counts. Similar results were observed for FoxP3 in cervical cancer (p=0.002; 5-year OS, 62.1% vs. 33.6%) and CD8 in oropharyngeal cancer (p=0.013; 5-year OS, 80.2% vs. 47.2%). In prostate cancer, high Ku70 group had worse and low group significantly better outcome [p=0.007; 10-year progression-free survival (PFS), 56.0% vs. 93.8%].

conclusionQuPath showed a strong correlation with manual counting, confirming its utility and accuracy and potential applicability in clinical practice.

Indexed as

SoftwareAdultAgedBiomarkers, TumorCD8 AntigensFemaleForkhead Transcription FactorsHumansImage Processing, Computer-AssistedImmunohistochemistryKu AutoantigenMaleMiddle AgedNeoplasmsPrognosisProstatic NeoplasmsBiomarkers, TumorCD8 AntigensForkhead Transcription FactorsFOXP3 protein, humanKu AutoantigenCD8cervical cancerFoxP3Ku70oropharyngeal cancerprostate cancerQuPath

Identifiers

PMID38688633
PMCPMC11059912

What OpenQuestion holds

Textmetadata
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Registered trials

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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.