Evidence map›Paper›PMID 25374914›Full record

ArticleAmerican journal of clinical and experimental urology2014

A system for evaluating magnetic resonance imaging of prostate cancer using patient-specific 3D printed molds.

Alan Priester, Shyam Natarajan, Jesse D Le, James Garritano, Bryan Radosavcev, Warren Grundfest, Daniel Ja Margolis, Leonard S Marks, Jiaoti Huang

Abstract read
In one paragraph

Article in American journal of clinical and experimental urology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. How else can we approach prostate cancer biomarker discovery?Expert review of molecular diagnostics · 2020
    Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. 3D printing in urology: Is it really promising?Turkish journal of urology · 2018
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

9 authors.

Alan PriesterDepartment of Bioengineering, University of California Los Angeles CA, USA.
Shyam NatarajanDepartment of Urology, David Geffen School of Medicine Los Angeles, USA.
Jesse D LeDepartment of Urology, David Geffen School of Medicine Los Angeles, USA.
James GarritanoDepartment of Bioengineering, University of California Los Angeles CA, USA.
Bryan RadosavcevDepartment of Pathology, David Geffen School of Medicine Los Angeles, USA.
Warren GrundfestDepartment of Bioengineering, University of California Los Angeles CA, USA.
Daniel Ja MargolisDepartment of Radiology, David Geffen School of Medicine Los Angeles, USA.
Leonard S MarksDepartment of Urology, David Geffen School of Medicine Los Angeles, USA.
Jiaoti HuangDepartment of Pathology, David Geffen School of Medicine Los Angeles, USA.

Funding

UCLA SPORE IN PROSTATE CANCERP50CA092131 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI FREEMAN, MICHAEL R · 2002 to 2023
$42.6M
Biopsy Tracking and MRI Fusion to Enhance Imaging of Cancer Within the ProstateR01CA158627 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MARKS, LEONARD STEPHEN · 2011 to 2013
$1.4M
NCI NIH HHS P50 CA092131NCI NIH HHS R01 CA158627
6 · The paper itself

Abstract

We have developed a system for evaluating magnetic resonance imaging of prostate cancer, using patient-specific 3D printed molds to facilitate MR-histology correlation. Prior to radical prostatectomy a patient receives a multiparametric MRI, which an expert genitourinary radiologist uses to identify and contour regions suspicious for disease. The same MR series is used to generate a prostate contour, which is the basis for design of a patient-specific mold. The 3D printed mold contains a series of evenly spaced parallel slits, each of which corresponds to a known MRI slice. After surgery, the patient's specimen is enclosed within the mold, and all whole-mount levels are obtained simultaneously through use of a multi-bladed slicing device. The levels are then formalin fixed, processed, and delivered to an expert pathologist, who identifies and grades all lesions within the slides. Finally, the lesion contours are loaded into custom software, which elastically warps them to fit the MR prostate contour. The suspicious regions on MR can then be directly compared to lesions on histology. Furthermore, the false-negative and false-positive regions on MR can be retrospectively examined, with the ultimate goal of developing methods for improving the predictive accuracy of MRI. This work presents the details of our analysis method, following a patient from diagnosis through the MR-histology correlation process. For this patient MRI successfully predicted the presence of cancer, but true lesion volume and extent were underestimated. Most cancer-positive regions missed on MR were observed to have patterns of low T2 signal, suggesting that there is potential to improve sensitivity.

Indexed as

3D printingMRIpathologyprostate cancerregistrationwhole mount

Identifiers

PMID25374914
PMCPMC4219304

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.