Objectives: To report our early experience with manually controlled targeted biopsy with real-time multiparametric magnetic resonance imaging and transrectal ultrasound fusion images for the diagnosis of prostate cancer.
Methods: A total of 20 consecutive patients suspicious of prostate cancer at the multiparametric magnetic resonance imaging scan were recruited prospectively. Targeted biopsies were carried out for each cancer-suspicious lesion, and 12 systematic biopsies using the BioJet system. Pathological findings of targeted and systematic biopsies were analyzed.
Results: The median age of the patients was 70 years (range 52-83 years). The median preoperative prostate-specific antigen value was 7.4 ng/mL (range 3.54-19.9 ng/mL). Median preoperative prostate volume was 38 mL (range 24-68 mL). The number of cancer-detected cases was 14 (70%). The median Gleason score was 6.5 (range 6-8). Cancer-detected rates of the systematic and targeted biopsy cores were 6.7 and 31.8%, respectively (P < 0.0001). In six patients who underwent radical prostatectomy, the geographic locations and pathological grades of clinically significant cancers and index lesions corresponded to the pathological results of the targeted biopsies.
Conclusion: Prostate cancers detected by targeted biopsies with manually controlled targeted biopsy using real-time multiparametric magnetic resonance imaging and transrectal ultrasound fusion imaging have significantly higher grades and longer length compared with those detected by systematic biopsies. Further studies and comparison with the pathological findings of whole-gland specimens have the potential to determine the role of this biopsy methodology in patients selected for focal therapy and those under active surveillance.
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http://dx.doi.org/10.1111/iju.12643 | DOI Listing |
World J Gastrointest Oncol
January 2025
Department of Hepatobiliary and Pancreaticosplenic Surgery, Jingzhou Hospital Affiliated to Yangtze University, Jingzhou 434100, Hubei Province, China.
Background: The liver, as the main target organ for hematogenous metastasis of colorectal cancer, early and accurate prediction of liver metastasis is crucial for the diagnosis and treatment of patients. Herein, this study aims to investigate the application value of a combined machine learning (ML) based model based on the multiparameter magnetic resonance imaging for prediction of rectal metachronous liver metastasis (MLM).
Aim: To investigate the efficacy of radiomics based on multiparametric magnetic resonance imaging images of preoperative first diagnosed rectal cancer in predicting MLM from rectal cancer.
World J Gastrointest Oncol
January 2025
Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China.
Background: Microvascular invasion (MVI) is a significant risk factor for recurrence and metastasis following hepatocellular carcinoma (HCC) surgery. Currently, there is a paucity of preoperative evaluation approaches for MVI.
Aim: To investigate the predictive value of texture features and radiological signs based on multiparametric magnetic resonance imaging in the non-invasive preoperative prediction of MVI in HCC.
Prostate Int
September 2024
Gazi University School of Medicine, Urology Department, Ankara, Turkey.
Aim: To investigate the predictive value of lesion length in multiparametric prostate magnetic resonance imaging with respect to prostate volume for clinically significant prostate cancer diagnosis in targeted biopsies.
Materials And Methods: The data of biopsy-naïve patients in the Turkish Urooncology Association Prostate Cancer Database who underwent targeted prostate biopsies were included in this study. Lesion density is calculated as the ratio of lesion length (mm) in MR to prostate volume (cc).
Prostate Int
September 2024
Erciyes University, Department of Urology, Devision of UroOncology, Kayseri, Turkey.
Background: It has been more than a decade since fusion prostate biopsy (FPB) has been used in the diagnosis of prostate cancer (PCa). Therefore, patients with a previous history of negative FPB and ongoing suspicion of PCa are beginning to emerge. This study investigated whether the first biopsy type (standard or fusion) should be effective in deciding on a second biopsy.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Radiology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China.
Objective: To evaluate the feasibility of utilizing artificial intelligence (AI)-predicted biparametric MRI (bpMRI) image features for predicting the aggressiveness of prostate cancer (PCa).
Materials And Methods: A total of 878 PCa patients from 4 hospitals were retrospectively collected, all of whom had pathological results after radical prostatectomy (RP). A pre-trained AI algorithm was used to select suspected PCa lesions and extract lesion features for model development.
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