ArticleEBioMedicine2016
Prospective Pilot Trial to Evaluate a High Resolution Diffusion-Weighted MRI in Prostate Cancer Patients.
Article in EBioMedicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising.Magma (New York, N.Y.) · 2024Article
- High-resolution Diffusion-weighted Imaging to Detect Changes in Tumor Size and ADC, and Predict Adverse Biopsy Histology during Prostate Cancer Active Surveillance.Cancer research communications · 2024Article
- MRI findings guiding selection of active surveillance for prostate cancer: a review of emerging evidence.Translational andrology and urology · 2018Review
- Article
- Multiparametric MRI in the Detection of Clinically Significant Prostate Cancer.Korean journal of radiologyReview
Corrections and comments
- Commented on by
Authors and funding
8 authors.
Funding
Abstract
objectivesHigh-resolution prostate imaging may allow for detection of subtle changes in tumor size, decrease the reliance on biopsies, and help define tumor boundaries during ablation. This pilot clinical trial evaluates a novel high-resolution prostate MRI for detection of small, biopsy-proven prostate tumors.
methodsOur team developed a software that can be loaded on any modern MRI to generate high resolution diffusion-weighted imaging sequences (HR-DWI), which were compared to standard diffusion-weighted imaging sequence (S-DWI) in a prospective pilot trial in active surveillance patients. HR-DWI captures the entire volume of the prostate rather than sections, reducing streaking artifacts and geometric distortions. Multiple shots, rather than single shots, are used to differentiate signal and noise, enhancing resolution. All images were read by two radiologists. The primary outcome was the percent of biopsy-proven zones seen in 17 patients. The trial was powered to detect discordant proportions of 0.04 and 0.40 at one-sided alpha=0.05.
resultsThe resolution was defined using standard phantoms. HR-DWI produced a 5-fold improvement in spatial resolution when compared to S-DWI. Multiparametric (MP)-MRI incorporating S-DWI was useful for predicting biopsy results (AUC 0.72, Fisher's exact p<0.001); however, using HR-DWI allowed MP-MRI to be more highly predictive of biopsy results (AUC 0.88, Fisher's exact p<0.001). AUC for MP-MRI incorporating HR-DWI was significantly larger than MP-MRI incorporating S-DWI (p=0.002). MP-MRI with HR-DWI had a sensitivity of 95.7% and identified tumor in 22 of 23 zones proven to have cancer on biopsy. In contrast, MP-MRI with S-DWI had a sensitivity of 60.9% and only identified 14 of 23 biopsy-positive zones (p=0.004).
conclusionWe developed a novel DWI and evaluated its improved resolution in a clinical setting. This technology has many potential applications and should be evaluated in future clinical trials as a patient management tool.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.