Gianluca Pontone MD, Presenter: Speakers Bureau, General Electric Company Consultant, General Electric Company Research Consultant, HeartFlow, Inc Speakers Bureau, HeartFlow, Inc Speakers Bureau, Medtronic, Inc Speakers Bureau, Bayer AG

Erika Bertella, Abstract Co-Author: Nothing to Disclose

Andrea Baggiano, Abstract Co-Author: Nothing to Disclose

Saima Mushtaq, Abstract Co-Author: Nothing to Disclose

Maria Petulla, Abstract Co-Author: Nothing to Disclose

Monica Loguercio, Abstract Co-Author: Nothing to Disclose

Chiara Segurini, Abstract Co-Author: Nothing to Disclose

Edoardo Conte, Abstract Co-Author: Nothing to Disclose

Virginia Beltrama, Abstract Co-Author: Nothing to Disclose

Daniele Andreini MD, Abstract Co-Author: Consultant, General Electric Company

To evaluate the impact of a new reconstruction algorithm, a novel intra-cycle motion correction algorithm to reduce motion artifacts, on image quality, overall evaluability and diagnostic accuracy in not-evaluable patients for artifacts evaluated by Computed tomography coronary angiography (CTCA) in comparison with standard reconstruction algorithm.

From a cohort of 900 patients referred to our hospital to perform CTCA for suspected CAD, 160 (18%) patients (mean age 65.3±11.7 yo, 101 male) with at least one coronary segment with diameter>2 mm classified as not evaluable for motion artifacts were enrolled and evaluated on dedicated post-processing workstation (AW version 4.5, GE Healthcare) using standard reconstruction algorithm (Group 1) and intra-cycle motion correction algorithm (Group 2). The Likert image quality, defined as 1 (not-evaluable) to 4 (no artifacts, unrestricted evaluation), and overall evaluability were estimated and compared among groups. Finally, a sub-group of 45 patients was referred to invasive coronary angiography as reference and sensitivity (Se), specificity (Sp), negative predictive value (NPV), positive predictive value (PPV) and accuracy (Ac) of CTCA were evaluated, censoring as positive the not-evaluable segments, and compared among groups .

Group 2 showed a higher Likert score (3.1±0.9 vs. 2.5±1.1, p<0.001) and overall evaluability (94% vs. 79%, p<0.001) in comparison with Group 1. In a segment based-model and in a vessel-based model, Sp, PPV and Ac were higher in Group 2 vs Group 1 (87% vs 73%, 50% vs 34%, 85% vs 73%, p<0.001 and 62% vs 28%, 66% vs 51% and 75% vs 57%, p<0.001, respectively). The Group 2 showed a higher accuracy vs group 1 in a patient based model (93% vs 75%, p<0.05). Finally, 96 out of 160 patients enrolled became fully evaluable after intra-cycle motion correction algorithm reducing the prevalence of not-evaluable patients form 18% up to 7% of overall population studied by CTCA.

In the routine clinical practice the intra-cycle motion correction algorithm is able to improve the image quality, the overall evaluability and the diagnostic accuracy of CTCA.

The intra-cycle motion correction algorithm is able to improve the image quality of CTCA.

Pontone, G, Bertella, E, Baggiano, A, Mushtaq, S, Petulla, M, Loguercio, M, Segurini, C, Conte, E, Beltrama, V, Andreini, D, Impact of Intra-cycle Motion Correction Algorithm on Overall Evaluability and Accuracy in 160 Not-evaluable Consecutive Patients Studied by Computed Tomography Coronary Angiography for Suspected CAD.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14010555.html