Journal of Digital Imaging

, Volume 24, Issue 1, pp 107–113 | Cite as

Data Management Solution for Large-Volume Computed Tomography in an Existing Picture Archiving and Communication System (PACS)

  • Takashi Yoshinobu
  • Katsumi Abe
  • Yasuo Sasaki
  • Makiko Tabei
  • Seiji Tanaka
  • Motoichiro Takahashi
  • Satoru Furuhashi
  • Ikue Tanaka
  • Takashi Shizukuishi
  • Takuya Aizawa
  • Toshiya Maebayashi
  • Masakuni Sakaguchi
  • Yoshitaka Okuhata
  • Junko Kikuta
  • Naoya Ishibashi
Article

Abstract

Multidetector row computed tomography (MDCT) creates massive amounts of data, which can overload a picture archiving and communication system (PACS). To solve this problem, we designed a new data storage and image interpretation system in an existing PACS. Two MDCT image datasets, a thick- and a thin-section dataset, and a single-detector CT thick-section dataset were reconstructed. The thin-section dataset was archived in existing PACS disk space reserved for temporary storage, and the system overwrote the source data to preserve available disk space. The thick-section datasets were archived permanently. Multiplanar reformation (MPR) images were reconstructed from the stored thin-section datasets on the PACS workstation. In regular interpretations by eight radiologists during the same week, the volume of images and the times taken for interpretation of thick-section images with (246 CT examinations) or without (170 CT examinations) thin-section images were recorded, and the diagnostic usefulness of the thin-section images was evaluated. Thin-section datasets and MPR images were used in 79% and 18% of cases, respectively. The radiologists’ assessments of this system were useful, though the volume of images and times taken to archive, retrieve, and interpret thick-section images together with thin-section images were significantly greater than the times taken without thin-section images. The limitations were compensated for by the usefulness of thin-section images. This data storage and image interpretation system improves the storage and availability of the thin-section datasets of MDCT and can prevent overloading problems in an existing PACS for the moment.

Key words

CT MDCT PACS computer applications 

References

  1. 1.
    Chang S, Lim JH, Choi D, Kim SK, Lee WJ: Differentiation of ampullary tumor from benign papillary stricture by thin-section multidetector CT. Abdom Imaging 33:457–462, 2008CrossRefPubMedGoogle Scholar
  2. 2.
    Das M, Mühlenbruch G, Katoh M, Bakai A, Salganicoff M, Stanzel S, Mahnken AH, Günther RW, Wildberger JE: Automated volumetry of solid pulmonary nodules in a phantom: accuracy across different CT scanner technologies. Invest Radiol 42:297–302, 2007CrossRefPubMedGoogle Scholar
  3. 3.
    Perrella A, Borsatti MA, Tortamano IP, Rocha RG, Cavalcanti MG: Validation of computed tomography protocols for simulated mandibular lesions: a comparison study. Braz Oral Res 21:165–169, 2007CrossRefPubMedGoogle Scholar
  4. 4.
    Mühlenbruch G, Klotz E, Wildberger JE, Koos R, Das M, Niethammer M, Hohl C, Honnef D, Thomas C, Günther RW, Mahnken AH: The accuracy of 1- and 3-mm slices in coronary calcium scoring using multi-slice CT in vitro and in vivo. Eur Radiol 17:321–329, 2007CrossRefPubMedGoogle Scholar
  5. 5.
    Prevrhal S, Fox JC, Shepherd JA, Genant HK: Accuracy of CT-based thickness measurement of thin structures: modeling of limited spatial resolution in all three dimensions. Med Phys 30:1–8, 2003CrossRefPubMedGoogle Scholar
  6. 6.
    Catalano C, Laghi A, Fraioli F, Pediconi F, Napoli A, Danti M, Reitano I, Passariello R: Pancreatic carcinoma: the role of high-resolution multislice spiral CT in the diagnosis and assessment of resectability. Eur Radiol 13:149–156, 2003CrossRefPubMedGoogle Scholar
  7. 7.
    Hunsaker A, Ingenito E, Topal U, Pugatch R, Reilly J: Preoperative screening for lung volume reduction surgery: usefulness of combining thin-section CT with physiologic assessment. Am J Roentgenol 170:309–314, 1998Google Scholar
  8. 8.
    Zeman RK, Berman PM, Silverman PM, Davros WJ, Cooper C, Kladakis AO, Gomes MN: Diagnosis of aortic dissection: value of helical CT with multiplanar reformation and three-dimensional rendering. Am J Roentgenol 164:1375–1380, 1995Google Scholar
  9. 9.
    Kohs GJ, Legunn J: CT in your clinical practice. Am J Roentgenol 183:1–12, 2004Google Scholar
  10. 10.
    Rubin GD: Data explosion: the challenge of multidetector-row CT. Eur J Radiol 36:74–80, 2000CrossRefPubMedGoogle Scholar
  11. 11.
    Rivers H, Poston B: Medical archiving: solutions for medical image management. Radiol Manage 28:38–44, 2006PubMedGoogle Scholar
  12. 12.
    Meenan C, Daly B, Toland C, Nagy P: Use of a thin-section archive and enterprise 3D software for long-term storage of thin-slice CT data sets. J Digit Imaging 19:84–88, 2006CrossRefPubMedGoogle Scholar
  13. 13.
    Lee KH, Lee HJ, Kim JH, Kang HS, Lee KW, Hong H, Chin HJ, Ha KS: Managing the CT data explosion: initial experiences of archiving volumetric datasets in a mini-PACS. J Digit Imaging 18:188–195, 2005CrossRefPubMedGoogle Scholar

Copyright information

© Society for Imaging Informatics in Medicine 2009

Authors and Affiliations

  • Takashi Yoshinobu
    • 1
  • Katsumi Abe
    • 1
  • Yasuo Sasaki
    • 2
  • Makiko Tabei
    • 3
  • Seiji Tanaka
    • 3
  • Motoichiro Takahashi
    • 1
  • Satoru Furuhashi
    • 1
  • Ikue Tanaka
    • 1
  • Takashi Shizukuishi
    • 1
  • Takuya Aizawa
    • 1
  • Toshiya Maebayashi
    • 1
  • Masakuni Sakaguchi
    • 1
  • Yoshitaka Okuhata
    • 1
  • Junko Kikuta
    • 1
  • Naoya Ishibashi
    • 1
  1. 1.Department of RadiologyNihon University School of MedicineItabashi-kuJapan
  2. 2.Department of RadiologyIwate Prefectural Central HospitalMoriokaJapan
  3. 3.Fujifilm MedicalMinato-kuJapan

Personalised recommendations