Application value of magnetic resonance spectroscopy imaging in the diagnosis of prostate cancer

Magnetic resonance spectroscopy (MRSI) can distinguish between benign and malignant prostate diseases. This study investigated the potential of MRSI for diagnosing prostate cancer and guiding prostate biopsy. We retrospectively reviewed 234 patients with suspected prostate cancer who underwent MRSI with targeted prostate biopsy. Patients were divided into two groups according to their puncture pathology: prostate cancer (n = 103, 44.02%) and benign prostatic disease (n = 131, 55.98%). The t-test, Mann-Whitney U test, or chi-square test was used to compare the groups. The diagnostic abilities of MRSI, prostate-specific antigen level, digital rectal examination, and magnetic resonance imaging without contrast for prostate cancer were compared using the area under the receiver operating characteristic curve (AUC-ROC); the ARC-ROC values were 0.831, 0.768, 0.692, and 0.656, respectively. The AUC-ROC value for diagnosing prostate cancer using the CC/c ratio was 0.853. CC/c ratio > 0.97 was identified as the optimal threshold for diagnosing prostate cancer (sensitivity, 86.5%; specificity, 78.6%; Youden index, 0.651). Spearman correlation analysis revealed a correlation between the CC/c ratio and Gleason score (r = 0.737, p < 0.001). Using the CC/c ratio of MRSI as an adjunct to targeted prostate biopsy can improve the detection rate of positive biopsies and evaluate prostate cancer invasiveness.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-09-27
DOI
https://doi.org/10.1038/s41598-024-73605-3
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application value of magnetic resonance spectroscopy imaging in the diagnosis of prostate cancer

Haiyang Wei, Zhiheng Huang, Wuxue Li, Tianhe Zhang et al.
Scientific Reports
Prostate Cancer Diagnosis and Treatment
article

Application value of magnetic resonance spectroscopy imaging in the diagnosis of prostate cancer

Haiyang Wei, Zhiheng Huang, Wuxue Li, Tianhe Zhang, Xinghua Zhao, Zhiyong Zhou, Changbao Xu, Shuailin Zhao
article en

Abstract

Magnetic resonance spectroscopy (MRSI) can distinguish between benign and malignant prostate diseases. This study investigated the potential of MRSI for diagnosing prostate cancer and guiding prostate biopsy. We retrospectively reviewed 234 patients with suspected prostate cancer who underwent MRSI with targeted prostate biopsy. Patients were divided into two groups according to their puncture pathology: prostate cancer (n = 103, 44.02%) and benign prostatic disease (n = 131, 55.98%). The t-test, Mann-Whitney U test, or chi-square test was used to compare the groups. The diagnostic abilities of MRSI, prostate-specific antigen level, digital rectal examination, and magnetic resonance imaging without contrast for prostate cancer were compared using the area under the receiver operating characteristic curve (AUC-ROC); the ARC-ROC values were 0.831, 0.768, 0.692, and 0.656, respectively. The AUC-ROC value for diagnosing prostate cancer using the CC/c ratio was 0.853. CC/c ratio > 0.97 was identified as the optimal threshold for diagnosing prostate cancer (sensitivity, 86.5%; specificity, 78.6%; Youden index, 0.651). Spearman correlation analysis revealed a correlation between the CC/c ratio and Gleason score (r = 0.737, p < 0.001). Using the CC/c ratio of MRSI as an adjunct to targeted prostate biopsy can improve the detection rate of positive biopsies and evaluate prostate cancer invasiveness.

Scientific ReportsVol. 14(1)
Second Affiliated Hospital of Zhengzhou University (CN)
Good health and well-being
Openalex Percentile: Top 69%
Prostate Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.