Evidence map›Paper›PMID 37009941›Full record

ArticleEuropean journal of hybrid imaging2023

Quantitative assessment of PSMA PET response to therapy in castration-sensitive prostate cancer using an automated imaging platform for disease identification and measurement.

Sai Duriseti, Gholam Berenji, Sonny Tsai, Matthew Rettig, Nicholas G Nickols

Abstract read
In one paragraph

Article in European journal of hybrid imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Sai DurisetiVA Greater Los Angeles, Radiation Oncology Service, 11301 Wilshire Blvd, Building 500, Suite 0426, Los Angeles, CA, 90073, USA. sduriseti@mednet.ucla.edu.ORCID http://orcid.org/0000-0002-8073-5132
Gholam BerenjiVA Greater Los Angeles, Nuclear Medicine Service, 11301 Wilshire Blvd, Building 500, Suite 0090, Los Angeles, CA, 90073, USA.
Sonny TsaiGreater Los Angeles VA, Hematology and Oncology Section, 11301 Wilshire Blvd. Building 304, Suite E2-218, Los Angeles, CA, 90073, USA.
Matthew RettigGreater Los Angeles VA, Hematology and Oncology Section, 11301 Wilshire Blvd. Building 304, Suite E2-218, Los Angeles, CA, 90073, USA.
Nicholas G NickolsVA Greater Los Angeles, Radiation Oncology Service, 11301 Wilshire Blvd, Building 500, Suite 0426, Los Angeles, CA, 90073, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

rationaleProstate cancer treatment response may be automatically quantified using a molecular imaging analysis platform targeting prostate-specific membrane antigen (PSMA).

methodsA retrospective analysis of patients with castration-sensitive prostate cancer who underwent PSMA-targeted molecular imaging prior to and 3 months or more after treatment was conducted. Disease burden was analyzed with aPROMISE, an artificial intelligence imaging platform that automatically quantifies PSMA-positive lesions. The calculated PSMA scores for prostate/bed, nodal, and osseous disease sites were compared with prostate-specific antigen (PSA) values.

resultsOf 30 eligible patients, the median decline in prostate/bed, nodal, and osseous disease PSMA scores were 100% (range 52-100%), 100% (range - 87-100%), and 100% (range - 21-100%), respectively. PSMA score decline was significantly associated with PSA decline.

conclusionChanges in aPROMISE PSMA scores are associated with changes in PSA and may quantify treatment response.

Indexed as

Artificial intelligenceAutomatedPSMA

Identifiers

PMID37009941
PMCPMC10068685

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.