| Title |
Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study
|
|---|---|
| Published in |
European Radiology, April 2018
|
| DOI | 10.1007/s00330-018-5374-6 |
| Pubmed ID | |
| Authors |
Matthew D. Greer, Nathan Lay, Joanna H. Shih, Tristan Barrett, Leonardo Kayat Bittencourt, Samuel Borofsky, Ismail Kabakus, Yan Mee Law, Jamie Marko, Haytham Shebel, Francesca V. Mertan, Maria J. Merino, Bradford J. Wood, Peter A. Pinto, Ronald M. Summers, Peter L. Choyke, Baris Turkbey |
| Abstract |
To evaluate if computer-aided diagnosis (CAD) prior to prostate multi-parametric MRI (mpMRI) can improve sensitivity and agreement between radiologists. Nine radiologists (three each high, intermediate, low experience) from eight institutions participated. A total of 163 patients with 3-T mpMRI from 4/2012 to 6/2015 were included: 110 cancer patients with prostatectomy after mpMRI, 53 patients with no lesions on mpMRI and negative TRUS-guided biopsy. Readers were blinded to all outcomes and detected lesions per PI-RADSv2 on mpMRI. After 5 weeks, readers re-evaluated patients using CAD to detect lesions. Prostatectomy specimens registered to MRI were ground truth with index lesions defined on pathology. Sensitivity, specificity and agreement were calculated per patient, lesion level and zone-peripheral (PZ) and transition (TZ). Index lesion sensitivity was 78.2% for mpMRI alone and 86.3% for CAD-assisted mpMRI (p = 0.013). Sensitivity was comparable for TZ lesions (78.7% vs 78.1%; p = 0.929); CAD improved PZ lesion sensitivity (84% vs 94%; p = 0.003). Improved sensitivity came from lesions scored PI-RADS < 3 as index lesion sensitivity was comparable at PI-RADS ≥ 3 (77.6% vs 78.1%; p = 0.859). Per patient specificity was 57.1% for CAD and 70.4% for mpMRI (p = 0.003). CAD improved agreement between all readers (56.9% vs 71.8%; p < 0.001). CAD-assisted mpMRI improved sensitivity and agreement, but decreased specificity, between radiologists of varying experience. • Computer-aided diagnosis (CAD) assists clinicians in detecting prostate cancer on MRI. • CAD assistance improves agreement between radiologists in detecting prostate cancer lesions. • However, this CAD system induces more false positives, particularly for less-experienced clinicians and in the transition zone. • CAD assists radiologists in detecting cancer missed on MRI, suggesting a path for improved diagnostic confidence. |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 50% |
| Italy | 1 | 10% |
| Spain | 1 | 10% |
| Saudi Arabia | 1 | 10% |
| Unknown | 2 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 50% |
| Scientists | 3 | 30% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
| Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 18% |
| Researcher | 10 | 13% |
| Student > Doctoral Student | 9 | 11% |
| Student > Bachelor | 6 | 8% |
| Other | 5 | 6% |
| Other | 8 | 10% |
| Unknown | 27 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 27 | 34% |
| Computer Science | 8 | 10% |
| Engineering | 4 | 5% |
| Agricultural and Biological Sciences | 2 | 3% |
| Arts and Humanities | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 34 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 March 2022.
All research outputs
#2,759,517
of 25,649,244 outputs
Outputs from European Radiology
#263
of 5,048 outputs
Outputs of similar age
#55,804
of 344,137 outputs
Outputs of similar age from European Radiology
#5
of 73 outputs
Altmetric has tracked 25,649,244 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,048 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 94% of its peers.
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We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.