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Pulmonary nodule detection on MDCT images: evaluation of diagnostic performance using thin axial images, maximum intensity projections, and computer-assisted detection

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Abstract

This study aimed at evaluating the diagnostic benefits of maximum intensity projections (MIP) and a commercially available computed-assisted detection system (CAD) for the detection of pulmonary nodules on MDCT as compared with standard 1-mm images on lung cancer screening material. Thirty subjects were randomly selected from our database. Three radiologists independently reviewed three types of images: axial 1-mm images, axial MIP slabs, and CAD system detections. Two independent experienced chest radiologists decided which were true-positive nodules. Two hundred eighty-five nodules ≥1 mm were identified as true-positive by consensus of two independent chest radiologists. The detection rates of the three independent observers with 1-mm axial images were 22 ± 4.8%, 30 ± 5.3%, and 47 ± 2.8%; with MIP: 33 ± 5.4%, 39 ± 5.7%, and 45 ± 5.8%; and with CAD: 35 ± 5.6%, 36 ± 5.6%, and 36 ± 5.6%. There was a reading technique effect on the observers’ sensitivity for nodule detection: sensitivities with MIP were higher than with 1-mm images or CAD for all nodules (F-values = 0.046). For nodules ≥3 mm, readers’ sensitivities were higher with 1-mm images or MIP than with CAD (p < 0.0001). CAD was the most and MIP the less time-consuming technique (p < 0.0001). MIP and CAD reduced the number of overlooked small nodules. As MIP is more sensitive and less time consuming than the CAD we used, we recommend viewing MIP and 1-mm images for the detection of pulmonary nodules.

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Authors and Affiliations

  1. Service Central de Radiologie et d’Imagerie Médicale, CHU Grenoble, BP 217, 38043, Grenoble Cedex 09, France

    A. Jankowski, T. Martinelli, F. Thony, M. Coulomb & G. Ferretti

  2. Réanimation médicale et soins intensifs d’urgence, CHU Grenoble BP 217, 38043, Grenoble Cedex 09, France

    J. F. Timsit

  3. INSERM U 823, Institut Albert Bonnot, Rond-point de la Chantourne, 38706, La Tronche Cedex, France

    J. F. Timsit, C. Brambilla & G. Ferretti

  4. Pneumologie, Département de Médecine aigue spécialisée, CHU Grenoble BP 217, 38043, Grenoble Cedex 09, France

    C. Brambilla

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  1. A. Jankowski
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Correspondence to A. Jankowski.

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Jankowski, A., Martinelli, T., Timsit, J.F. et al. Pulmonary nodule detection on MDCT images: evaluation of diagnostic performance using thin axial images, maximum intensity projections, and computer-assisted detection. Eur Radiol 17, 3148–3156 (2007). https://doi.org/10.1007/s00330-007-0727-6

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