ArticleJournal of imaging informatics in medicine2026
Technical Developments in Radiology: Enhancing Research Workflows with PACScrawler.
Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Efficiently identifying and retrieving imaging studies to create research cohorts is often hindered by the segregated storage of medical imaging data and radiological reports. To address this, we developed PACScrawler, an open-source tool designed to streamline cohort assembly by enabling efficient search and access to imaging studies across Picture Archiving and Communication Systems (PACS) and Radiology Information Systems (RIS). The system features a backend crawler module that regularly collects DICOM and RIS metadata and radiology reports from newly acquired studies and stores them in a local Apache Solr/Lucene index. A web-based interface enables multi-parameter search across the indexed database, and a retrieval module downloads the corresponding imaging data on demand. Between 2012 and 2024, PACScrawler indexed 2,327,317 examinations from 316,310 patients at our institution. In our local setup, routine indexing of 1079 examinations on a representative day required 26.5 min, corresponding to a median of 1.4 s per study. In a batch retrieval benchmark, ten head MRI examinations comprising 325 series were retrieved in 16 min 08 s using PACScrawler compared with 31 min 45 s by manual sequential PACS export. For LLM-assisted query construction, 17 of 20 generated Solr queries were usable with no or limited manual adjustment. As an illustrative use case, the index enabled longitudinal monitoring of local imaging volumes and examination complexity. PACScrawler lowers the technical barrier for clinical imaging research by providing an open-source, regularly updated local search index for selected PACS/RIS metadata and radiology reports. It supports retrospective cohort identification, on-demand retrieval of imaging data, and longitudinal monitoring of institutional imaging trends while routine indexing is limited to metadata and report text. As a DICOM-based tool, PACScrawler may be adapted to other clinical environments after local PACS/RIS integration and validation; source code is available at https://github.com/pacs-ris-crawler/pacs-ris-crawler .
Indexed as
Identifiers
42481901What 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.