Abstract
 Top of page
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgments
 Author contributions
 Conflict of Interests
 References
Background The distal contractile integral (DCI) is an index of contractile vigor in highresolution 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) ‘regiongrowing’ 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). Pixelbypixel horizontal line segments were then analyzed within this span starting at the pressure maximum and extending outward from that point. The limits of ‘regiongrowing’ 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, P < 0.001). The DCI values obtained with the conventional calculation were slightly but significantly greater than with the regiongrowing 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 regiongrowing 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.
Introduction
 Top of page
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgments
 Author contributions
 Conflict of Interests
 References
In high resolution esophageal pressure topography (EPT) the vigor of the distal esophageal contraction is characterized by its amplitude, duration, and vertical length.^{1–3} The resulting metric is termed distal contractile integral (DCI) and calculated as the product of the mean amplitude of the contraction (excluding the 20 mmHg footprint) times its duration times its length between the proximal (P) pressure trough and either the distal (D) pressure trough or the proximal margin of the lower esophageal sphincter (LES). The DCI is expressed in units of mmHg s cm. In the Chicago Classification for esophageal motility disorders in EPT hypertensive peristalsis is defined as a mean DCI >5000 mmHg s cm in the context of normal contractile latency.^{2} An extreme phenotype of hypercontractility is defined by the presence of at least one test swallow resulting in a contraction with a DCI >8000 mmHg s cm.^{4} Consequently, the DCI is a fundamental parameter to identify hypertensive motility disorders in EPT.
The current method to calculate DCI consists of manually delineating a spacetime box encompassing the distal esophageal contraction, calculating the average intraluminal pressure within that box and multiplying that value (less 20 mmHg) by the duration and the length of the box.^{2} Even if the calculation is automated with the software provided by the manufacturer this method requires user input to delineate the spacetime box of interest. It may also lead to the inclusion of extraneous pressure signals within that box in the computation such as repetitive vascular artifacts that are separated from the major contractile complex.
Regiongrowing is an algorithmic method for image segmentation. This signal processing technique automatically extracts features from an image which are then further used for a variety of classification tasks.^{5} Basically, a point of interest is identified on the image based on a characteristic such as density, and adjacent areas are then systematically interrogated to see if they also possess that characteristic. Regiongrowing has fairly wide applications in medical image analysis such as quantifying the size or volume of mass lesions in ultrasound or CT imaging.^{6,7} The application of regiongrowing to calculate DCI may provide an entirely automated method minimizing the need for user input and automatically excluding many pressure artifacts. The aim of this study was to develop and test an automatic regiongrowing algorithm for calculating DCI in clinical EPT studies.
Results
 Top of page
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgments
 Author contributions
 Conflict of Interests
 References
Table 1 summarizes the DCI data calculated using ManoView™ software and regiongrowing algorithm for 72 controls. The values given by ManoView™ were significantly greater than those given by the regiongrowing algorithm (P < 0.01 for mean DCI and for the greatest DCI). The mean differences between the 2 methods of calculation were 136 (±232) and 174 (±242) mmHg s cm for the mean and the greatest DCI respectively. The linear correlation was very strong between the two methods (r = 0.98, P < 0.001 for mean DCI and r = 0.98, P < 0.001 for greatest DCI, Fig. 2).
Table 1. Mean and greatest DCI values calculated using ManoView™ software and regiongrowing algorithm developed in MATLAB™ for 72 normal subjects  Percentiles  Mean ± SD  Range 

5th  25th  50th  75th  95th 


Mean DCI (mmHg s cm) 
Regiongrowing algorithm  381  1074  1455  2034  4391  1690 ± 1092  324–5407 
ManoView™  512  1064  1600  2215  4649  1840 ± 1190  343–6479 
Greatest DCI (mmHg s cm) 
Regiongrowing algorithm  806  1322  1815  2411  5605  2175 ± 1337  518–6850 
ManoView™  791  1446  2073  2613  5835  2350 ± 1430  604–7732 
In the 20 patients selected because their EPT study contained a test swallow with DCI (calculated with ManoView™ software) between 4000 and 10 000 mmHg s cm, the values given with ManoView™ were also greater (Table 2, P < 0.01). The mean difference between the two methods was 323 (±317) mmHg s cm. Fig. 3 illustrates the very strong linear correlation between the 2 methods of calculation for these patients (r = 0.97, P < 0.001).
Table 2. Greatest DCI values calculated using ManoView™ software and regiongrowing algorithm developed in MATLAB™ for 20 selected patients with a swallow of marginally abnormal DCI  Percentiles  Mean ± SD  Range 

5th  25th  50th  75th  95th 


Greatest DCI (mmHg s cm) 
Regiongrowing algorithm  4328  5233  5668  7461  8869  6242 ± 1526  4141–8895 
ManoView™  4485  5254  6090  7513  9828  6564 ± 1677  4400–9990 
The regiongrowing algorithm provided a lesser DCI value than the ManoView™ calculation in 59 control subjects (82%) and 18 patients (90%). Inclusion of pressures attributable to vascular pulsations in ManoView™ software calculation might explain some of this difference. The examples illustrated in Fig. 4 demonstrate how the regiongrowing algorithm had the effect of excluding some vascular artifact from the calculation. Another source of discrepancy between methods was attributable to the location of distal limit for DCI calculation. This is illustrated in Fig. 5 for two of the patients studied. From the maximal spatial pressure variation plots in panels B and E, it is evident that no pressure minima existed between the distal esophageal segment and the EGJ. In these cases, the proximal margin of the EGJ after the termination of peristalsis was utilized as the userdefined distal limit of DCI calculation.
Discussion
 Top of page
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgments
 Author contributions
 Conflict of Interests
 References
We developed and tested an automated regiongrowing algorithm for calculating DCI in clinical EPT studies. The DCI calculations in 72 normal subjects and 20 patients with a swallow characterized by a marginally abnormal DCI (between 4000 and 10 000 mmHg s cm) demonstrated that the proposed automatic regiongrowing algorithm gave DCI values very similar to, although slightly less than using ManoView™ software. The magnitude of the differences was small and unlikely to be clinically relevant. Hence, the regiongrowing algorithm described offers the advantages of minimizing the required user input for calculating DCI and of excluding vascular artifact from the calculation.
The method of DCI calculation presented in this study is rapid and automated, an adaptation of conventional regiongrowing methodology to the task of EPT interpretation. Conventional regiongrowing methods use pixels as the basic elements of regions.^{5,6} The algorithm proposed here uses horizontal line segments as the basic element of a region owing to the nature of how data are acquired in an HRM study. An added benefit of using line segments centered on the maximal pressure value in the distal segment is that it makes the calculation process faster.^{7} Key to the reproducibility of the DCI calculation is identifying the spatial limits to be included in the calculation. As the DCI calculation excludes pressure below 20 mmHg, a fixed pressure threshold of 20 mmHg can be used as a uniform criterion for delineating the margins of line segments. Similarly, the proximal limit is readily identifiable as either the pressure minima, often referred to as the transition zone,^{9} or the point at which the pressure diminishes to 20 mmHg. The greatest potential for variability is in localization of the distal limit for the DCI calculation. In instance in which there is a pressure minimum between the distal contraction (the combination of S2 and S3 as defined by Clouse ^{10}), and the LES, this is straightforward. However, in instances such as illustrated in Fig. 5 no such minima exist and the userdefined proximal margin of the LES (or EGJ) is alternatively used. Still, this is a point also used in delineating the proximal margin for the calculation of the Integrated Relaxation Pressure (IRP) so it does not add to the steps required of the user in the interpretation process.
Another advantage of the regiongrowing algorithm is the exclusion of pressure artifacts that occur either before or after the distal contraction. This could be of importance in instances of swallows with borderline abnormal DCI. Pressure artifacts encountered in EPT data are essentially usually attributable to cardiovascular pulsation from structures neighboring of the esophagus, especially in supine position.^{11} These pressure signals will be included in the DCI calculation with ManoView™ software as presented in Fig. 4. Although some advanced signal processing techniques, such as empirical mode decomposition,^{12} wavelet decomposition^{13} and adaptive and median filtering,^{14} have been shown to improve the quality of esophageal manometric data, an active interaction between the user processing the data and the computer program is required. The proposed regiongrowing algorithm does not require any prior information about the EPT data, and does not require any intervention by the person processing the data and can be implemented for online processing. Note, however, that although vascular signals separated from the main contractile complex by a pressure trough of <20 mmHg will automatically be excluded by the regiongrowing algorithm those that are superimposed on it will necessarily be included. Similarly, although intrabolus pressure compartmentalized between the main contractile complex and the EGJ will be automatically excluded when <20 mmHg, this will be included in the calculation when >20 mmHg, a condition that implies abnormal EGJ relaxation.
Finally normative data for DCI have been established using the calculation method included in the ManoView™ software calculation owing to the calculation methodology employed. Our results suggest a statistically significant difference between the values obtained with the two methods of calculation in control subjects. In theory the thresholds should be redefined for the diagnosis of hypertensive peristalsis or hypercontractility in EPT using this new method of DCI calculation. However the differences are relatively small and probably not clinically relevant.
In conclusion, the proposed automated regiongrowing algorithm calculates DCI on EPT plots with minimal user input beyond what is already required to identify the timing of the test swallow and the localization of the sphincteric zones. The ability of the automated regiongrowing algorithm performed well compared to DCI calculation by an expert user utilizing ManoView™ software. As such, the algorithm described provides another building block for the automated analysis of EPT studies.