Abstract

Background: Structured reporting (SR) in radiology has been recognized recently by major scientific societies. This study aims to build structured computed tomography (CT) and magnetic resonance (MR)-based reports in pancreatic adenocarcinoma during the staging phase in order to improve communication between the radiologist and members of multidisciplinary teams. Materials and Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the CT-SR and MRI-SR, assessing a level of agreement for all report sections. Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. Results: The final CT-SR version was built by including n = 16 items in the “Patient Clinical Data” section, n = 11 items in the “Clinical Evaluation” section, n = 7 items in the “Imaging Protocol” section, and n = 18 items in the “Report” section. Overall, 52 items were included in the final version of the CT-SR. The final MRI-SR version was built by including n = 16 items in the “Patient Clinical Data” section, n = 11 items in the “Clinical Evaluation” section, n = 8 items in the “Imaging Protocol” section, and n = 14 items in the “Report” section. Overall, 49 items were included in the final version of the MRI-SR. In the first round for CT-SR, all sections received more than a good rating. The overall mean score of the experts was 4.85. The Cα correlation coefficient was 0.85. In the second round, the overall mean score of the experts was 4.87, and the Cα correlation coefficient was 0.94. In the first round, for MRI-SR, all sections received more than a good rating. The overall mean score of the experts was 4.73. The Cα correlation coefficient was 0.82. In the second round, the overall mean score of the experts was 4.91, and the Cα correlation coefficient was 0.93. Conclusions: The CT-SR and MRI-SR are based on a multi-round consensus-building Delphi exercise derived from the multidisciplinary agreement of expert radiologists in order to obtain more appropriate communication tools for referring physicians.

Highlights

  • Pancreatic cancer accounts for almost as many deaths (466,000) as cases (496,000) because of its poor prognosis and is the seventh leading cause of cancer death in both sexes

  • 49 items were included in the final version of the magnetic resonance imaging (MRI)-Structured reporting (SR)

  • The overall mean score of the experts was 4.91, the Cα correlation coefficient was 0.93, and the sum of scores for the magnetic resonance (MR) structured report was 1108 (93.35 ± 3.28). For both the computed tomography (CT) and MR pancreas structured report, between the first and second round, a major agreement was reached among the 20 panelists highlighted by the increase of Cα correlation coefficient, overall mean score, and sum of scores

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Summary

Introduction

Pancreatic cancer accounts for almost as many deaths (466,000) as cases (496,000) because of its poor prognosis and is the seventh leading cause of cancer death in both sexes. Rates are from 4-fold to 5-fold higher in higher Human Development Index (HDI) countries, with the highest incidence rates in Europe, Northern America, and Australia/New Zealand [1]. Both incidence and mortality rates either have been stable or have slightly increased in many countries, likely reflecting the increasing prevalence of obesity, diabetes, and alcohol consumption, improvements in diagnostic and cancer registration practices may be in play in some countries [1,2,3,4]. The multidisciplinary team should make the choice concerning the resectability of pancreatic cancer following the acquisition of a complete staging [10,11]. MRI is a useful diagnostic tool in oncologic patients since this offers morphological data by T2-weighted (W) and T1-W sequences, and functional data by diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE)-MRI, as well as new tools such as blood oxygenation-level dependent (BOLD) sequences [14,15]

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