ArticleCancer medicine2025
Preoperative Diagnostic Value of Spectral CT for Predicting Perineural Invasion in Esophageal Cancer.
Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Preoperative Diagnostic Value of Spectral CT for Predicting Perineural Invasion in Esophageal Cancer.Cancer medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
purposeTo assess the diagnostic value of preoperative spectral CT quantitative parameters in predicting perineural invasion (PNI) in esophageal squamous cell carcinoma (ESCC), which is a critical prognostic factor associated with increased recurrence and poor survival. Preoperative identification of PNI can guide individualized treatment strategies.
methodsA retrospective analysis was conducted on 78 patients with EC who underwent preoperative spectral CT. Patients were classified into PNI-positive and -negative groups on the basis of histopathological findings. Spectral CT parameters, including conventional single-energy CT value (Sect), virtual monochromatic images, effective atomic number (Zeff), and iodine concentration (IC), were compared between groups. Statistical analyses were performed through t, rank sum, and chi-squared tests. A diagnostic nomogram was constructed by employing independent predictors and validated via receiver operating characteristic curve analysis with DeLong's test for the pairwise comparison of the area under the curve (AUC), ensuring the robust evaluation of discriminative performance.
resultsSignificant differences in spectral CT parameters were observed between the PNI-positive and PNI-negative groups. Specifically, the PNI-positive group exhibited higher values of 40-70 keV, Zeff, and IC (all p < 0.05) than the PNI-negative group. Among parameters, 40 keV demonstrated the highest predictive accuracy for PNI, with an AUC of 0.943. Binary logistic regression identified CYF, Sect, and 40 keV as independent predictors of PNI status. A nomogram incorporating these variables achieved the optimal diagnostic performance with an AUC of 0.971.
conclusionPreoperative spectral CT quantitative parameters, particularly 40 keV, Zeff, and IC, provide valuable insights for assessing PNI in ESCC. The integration of spectral CT parameters with clinical features can significantly improve the accuracy of PNI diagnosis.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.