Automated calculation of the distal contractile integral in esophageal pressure topography with a region-growing algorithm


Address for Correspondence
Zhiyue Lin, Northwestern University, Feinberg School of Medicine, Department of Medicine, 676 St Clair St, Suite 1400, Chicago, IL 60611-2951, USA.
Tel: +1 312 926 5496; fax: +1 312 695 3999;


Background  The distal contractile integral (DCI) is an index of contractile vigor in high-resolution esophageal pressure topography (EPT) calculated as the product of amplitude, duration, and span of the distal esophageal contraction. The aim of this study was to develop an automated algorithm calculating DCI.

Methods  The DCI was calculated conventionally using ManoView™ (Given Imaging, Los Angeles, CA, USA) software in EPT studies from 72 controls and 20 patients and compared to the calculation using a MATLAB™ (Version 7.9.0, R2009b; The MathWorks Inc., Natick, MA, USA) ‘region-growing’ algorithm. This algorithm first established the spatial limits of the distal contraction (the proximal pressure trough to either the distal pressure trough or to the superior margin of the lower esophageal sphincter at rest). Pixel-by-pixel horizontal line segments were then analyzed within this span starting at the pressure maximum and extending outward from that point. The limits of ‘region-growing’ were defined either by the spatial DCI limits or by encountering a pressure <20 mmHg. The DCI was then calculated as the total units of mmHg s cm greater than 20 mmHg within this domain.

Key Results  Excellent correlation existed between the two methods (r = 0.98, < 0.001). The DCI values obtained with the conventional calculation were slightly but significantly greater than with the region-growing algorithm. Differences were attributed to the inclusion of vascular pressures in the conventional calculation or to differences in localization of the distal limit of the DCI.

Conclusions & Inferences  The proposed region-growing algorithm provides an automated method to calculate DCI that limits inclusion of vascular pressure artifacts and minimizes the need for user input in data analysis.