Using quantitative breath sound measurements to predict lung function following resection

<p>Abstract</p> <p>Background</p> <p>Predicting postoperative lung function is important for estimating the risk of complications and long-term disability after pulmonary resection. We investigated the capability of vibration response imaging (VRI) as an alternative to lung scintigraphy for prediction of postoperative lung function in patients with intrathoracic malignancies.</p> <p>Methods</p> <p>Eighty-five patients with intrathoracic malignancies, considered candidates for lung resection, were prospectively studied. The projected postoperative (ppo) lung function was calculated using: perfusion scintigraphy, ventilation scintigraphy, and VRI. Two sets of assessments made: one for lobectomy and one for pneumonectomy. Clinical concordance was defined as both methods agreeing that either a patient was or was not a surgical candidate based on a ppoFEV₁% and ppoDLCO% > 40%.</p> <p>Results</p> <p>Limits of agreement between scintigraphy and VRI for ppo following lobectomy were -16.47% to 15.08% (mean difference = -0.70%;95%CI = -2.51% to 1.12%) and for pneumonectomy were -23.79% to 19.04% (mean difference = -2.38%;95%CI = -4.69% to -0.07%). Clinical concordance between VRI and scintigraphy was 73% for pneumonectomy and 98% for lobectomy. For patients who had surgery and postoperative lung function testing (<it>n </it>= 31), ppoFEV₁% using scintigraphic methods correlated with measured postoperative values better than projections using VRI, (adjusted R²= 0.32 scintigraphy; 0.20 VRI), however the difference between methods failed to reach statistical significance. Limits of agreement between measured FEV₁% postoperatively and ppoFEV₁% based on perfusion scintigraphy were -16.86% to 23.73% (mean difference = 3.44%;95%CI = -0.29% to 7.16%); based on VRI were -19.56% to 28.99% (mean difference = 4.72%;95%CI = 0.27% to 9.17%).</p> <p>Conclusions</p> <p>Further investigation of VRI as an alternative to lung scintigraphy for prediction of postoperative lung function is warranted.</p

Adaptive Statistical Iterative Reconstruction (ASIR): Re-defining CT dose reduction strategies

Advances in Technology Poster: P104KEY LEARNING OBJECTIVES: (1) Brief description of ASIR (Adaptive Statistical Iterative Reconstruction) physics. (2) Compare diagnostic quality of CT scan images performed without and with ASIR. (3) Demonstrate various clinical applications of ASIR. DESCRIPTION: Diagnostic x-rays account for the largest artificial source of exposure to ionizing radiation and CT represents the greater proportion. Traditionally, reducing CT dose result in an increase in image noise and a compromise on image quality. ASIR, on the other hand utilizes complex algebraic calculations to lower image noise and CT dose without loss of anatomical detail. ASIR has been shown to reduce CT doses by up to 50%. A study conducted in our institution comparing the Dose Length Products (DLPs) of CT pulmonary angiogram scans performed in the same patients without and with ASIR showed statistically significant reduction in dose of up to 42% without compromising diagnostic accuracy (445.87 vs 257.59). This educational poster provides a brief description of how ASIR works. It also shows the diagnostic quality of images obtained with ASIR by comparing similar images of the same patients without ASIR. Thirdly, the various ways in which ASIR can be utilized will be discussed. CONCLUSION: ASIR effectively lowers CT doses without compromising diagnostic quality. Radiologists need to be conversant with recent developments in CT dose lowering strategies such as ASIR and various ways in which it can be utilized clinically