Deep-inspiration breath-hold PET/CT: clinical findings with a new technique for detection and characterization of thoracic lesions. Academic Article uri icon

Overview

abstract

  • UNLABELLED: Respiratory motion during PET/CT acquisition can cause misregistration and inaccuracies in calculation of standardized uptake values (SUVs). Our aim was to compare the detection and characterization of thoracic lesions on PET/CT with and without a deep-inspiration protocol. METHODS: We studied 15 patients with suspected pulmonary lesions who underwent clinical PET/CT, followed by deep-inspiration breath-hold (BH) PET/CT. In BH CT, the whole chest of the patient was scanned in 15 s at the end of deep inspiration. For BH PET, patients were asked to hold their breath 9 times for 20-s intervals. One radiologist reviewed images, aiming to detect and characterize pulmonary, nodal, and skeletal abnormalities. Clinical CT and BH CT were compared for number, size, and location of lesions. Lesion SUVs were compared between clinical PET and BH PET. Images were also visually assessed for accuracy of fusion and registration. RESULTS: All patients had lesions on clinical CT and BH CT. Pulmonary BH CT detected more lesions than clinical CT in 13 of 15 patients (86.7%). The total number of lung lesions detected increased from 53 with clinical CT to 82 with BH CT (P<0.001). Eleven patients showed a total of 31 lesions with abnormal (18)F-FDG uptake. BH PET/CT had the advantage of reducing misregistration and permitted a better localization of sites with (18)F-FDG uptake. A higher SUV was noted in 22 of 31 lesions on BH PET compared with clinical PET, with an average increase in SUV of 14%. CONCLUSION: BH PET/CT enabled an increased detection and better characterization of thoracic lesions compared with a standard PET/CT protocol, in addition to more precise localization and quantification of the findings. The technique is easy to implement in clinical practice and requires only a minor increase in the examination time.

publication date

  • May 1, 2007

Research

keywords

  • Artifacts
  • Image Enhancement
  • Image Interpretation, Computer-Assisted
  • Positron-Emission Tomography
  • Respiratory Mechanics
  • Thoracic Neoplasms
  • Tomography, X-Ray Computed

Identity

Scopus Document Identifier

  • 34250667163

Digital Object Identifier (DOI)

  • 10.2967/jnumed.106.038034

PubMed ID

  • 17475958

Additional Document Info

volume

  • 48

issue

  • 5