title: Utilisation of a thoracic oncology database to capture radiological and pathological images for evaluation of response to chemotherapy in patients with malignant pleural mesothelioma.
abstract: OBJECTIVE
  An area of need in cancer informatics is the ability to store images in a comprehensive database as part of translational cancer research. To meet this need, we have implemented a novel tandem database infrastructure that facilitates image storage and utilisation.
  
  
  BACKGROUND
  We had previously implemented the Thoracic Oncology Program Database Project (TOPDP) database for our translational cancer research needs. While useful for many research endeavours, it is unable to store images, hence our need to implement an imaging database which could communicate easily with the TOPDP database.
  
  
  METHODS
  The Thoracic Oncology Research Program (TORP) imaging database was designed using the Research Electronic Data Capture (REDCap) platform, which was developed by Vanderbilt University. To demonstrate proof of principle and evaluate utility, we performed a retrospective investigation into tumour response for malignant pleural mesothelioma (MPM) patients treated at the University of Chicago Medical Center with either of two analogous chemotherapy regimens and consented to at least one of two UCMC IRB protocols, 9571 and 13473A.
  
  
  RESULTS
  A cohort of 22 MPM patients was identified using clinical data in the TOPDP database. After measurements were acquired, two representative CT images and 0-35 histological images per patient were successfully stored in the TORP database, along with clinical and demographic data.
  
  
  CONCLUSIONS
  We implemented the TORP imaging database to be used in conjunction with our comprehensive TOPDP database. While it requires an additional effort to use two databases, our database infrastructure facilitates more comprehensive translational research.
  
  
  CONCLUSIONS
  The investigation described herein demonstrates the successful implementation of this novel tandem imaging database infrastructure, as well as the potential utility of investigations enabled by it. The data model presented here can be utilised as the basis for further development of other larger, more streamlined databases in the future.
authors.affiliation: Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
authors.forename: George B
authors.initials: GB
authors.lastname: Carey
authors.forename: Stephanie
authors.initials: S
authors.lastname: Kazantsev
authors.forename: Mosmi
authors.initials: M
authors.lastname: Surati
authors.forename: Cleo E
authors.initials: CE
authors.lastname: Rolle
authors.forename: Archana
authors.initials: A
authors.lastname: Kanteti
authors.forename: Ahad
authors.initials: A
authors.lastname: Sadiq
authors.forename: Neil
authors.initials: N
authors.lastname: Bahroos
authors.forename: Brigitte
authors.initials: B
authors.lastname: Raumann
authors.forename: Ravi
authors.initials: R
authors.lastname: Madduri
authors.forename: Paul
authors.initials: P
authors.lastname: Dave
authors.forename: Adam
authors.initials: A
authors.lastname: Starkey
authors.forename: Thomas
authors.initials: T
authors.lastname: Hensing
authors.forename: Aliya N
authors.initials: AN
authors.lastname: Husain
authors.forename: Everett E
authors.initials: EE
authors.lastname: Vokes
authors.forename: Wickii
authors.initials: W
authors.lastname: Vigneswaran
authors.forename: Samuel G
authors.initials: SG
authors.lastname: Armato
authors.forename: Hedy L
authors.initials: HL
authors.lastname: Kindler
authors.forename: Ravi
authors.initials: R
authors.lastname: Salgia