Novel description on esophageal timed barium swallow: a correlation between advanced parametrization and esophageal X-ray images

Abstract

Aim: The TBS-derived image processing method, based on the observer's diagnosis, has been developed in the current investigation. Image parametrization is proposed for both novel description and convergent shreds of evidence.

Background: Condensed X-ray images of the esophageal timed barium swallow (TBS) provide substantial implications for elucidating the pathophysiological dimensions of esophageal motility disorders.

Methods: Through the simultaneous study on TBS and high-resolution manometry (HRM) findings, we performed a retrospective cohort study on 252 patients from March 2018 to October 2019. Interventions, irrelevant information, and insufficient patient data were excluded. Only subjects with adequate data and acceptable test accuracy were considered for participation. We reviewed 117 Dicom (digital imaging and communications in medicine) X-ray images from patients with confirmed diagnoses of achalasia type II, esophagogastric junction outflow obstruction (EGJOO), or non-achalasia.

Results: The results suggested a cut-off level of 47% in DDi (dilated diameter index) as a sign of the dilated body. In achalasia type II patients (n=66 images), the mean DDi was 55.6%. Our method presented a sensitivity of 95% and a specificity of 93% compared to images of the non-achalasia findings. The mean DDi in EGJOO patients was 50.4%, according to the 27 images. Moreover, results from EGJOO patients provided a sensitivity of 85% and specificity of 87%.

Conclusion: TBS is an efficacious method and a prominent component in the process of achalasia diagnosis. Standard parametrization might develop radiological exports proposed by DDi. Our method could assist in obtaining a non-invasive medical diagnosis and help advance diagnostic reports to identify achalasia subtypes somewhat earlier. To the best of our knowledge, this interface is an innovative parametrization for TBS image review.

Keywords: Achalasia; Esophageal barium time swallow; High-resolution esophageal manometry; Image processing.

Figure 1

Flowchart of the computer coding procedure. Step 1: There are two possible types of input images into our ComC, jpg and dicom, and both are acceptable. In this step, the X-ray image is imported manually by the operator. Step 2: Next is the questionnaire stage, in which the view of the image and the related data are selected based on information from the BSS procedure. The operator answers only the questions to input image info in ComC. These include image from the BSS procedure. The operator answers only the questions to input image info in ComC. These include image view and barium type as well. Step 3: This step is crucial; the operator crops the Image in which is defined as the region of interest (ROI). While esophagus shapes differ among patients, the diaphragm and aortic knob are prior signs of lower and upper thoracic segmentation, respectively. Moreover, spinal cord numbering from the diaphragm is used in determining the accuracy of ROI findings (Figure 2)

Figure    2

Image cropped to find ROI. Step 4: For image restoration and reconstruction, the linear gaussian noise has been added and the wiener filter applied. These functions aided the image enhancement and denoising process (22). Using a grayscale index, thresholding was applied to extract the border of the esophagus from its background. ComC uses the mean of the grayscale index from the cropped ROI in the first iteration for autonomous border extraction. In the second iteration, if the border is unclear or not confirmed, manual thresholding was done until the esophagus border was extracted (Figure 3 a and b). The digital spectrum of the grayscale index (known as binary image) is noted between 0 to 1 at scale of 10^-4 or 0 to 255, representing black to white, respectively. Step 5: the image was qualified based on operator confirmation. The operator checks the quality of the detected border and may confirm it at this stage (Figure 3c). Step 6: Using our novel algorithm, autonomous measurement through the esophageal border was done. A computer-aided coding began to process the measurement of the diameter and positive/negative behavior of the cropped ROI. Parametrization was done utilizing the threshold step and esophagus border extraction. The final results from this step are presented in Figure 4

Figure 3

a) Unqualified thresholding on the cropped ROI. b) Qualified thresholding on the cropped ROI. c) Pre-analysis on qualified ROI

Figure 4.

Final outcome from ComC; node highlight and critical border detection. Step 7: Considering outcomes from ComC, node highlighting have been abbreviated on Table 2. for an image review. Moreover, Dilated Diameter index (DDi), Positive Peristalsis Behavior (PPB) and Negative Peristalsis Behavior (NPB) are translated formulation for image achievements (Table 3)

Figure 5

PPB and NPB findings. The green “+” are PPB at the esophageal border, and the black “+” are NPB. The blue filled circles are middle points at each node pair (esophageal diameter centers). A) Normal analyzed image. B) X3 zoom export of Image A

Figure 6

DDi results from confirmed achalasia type II patients, TBS images (n=66). MINDDi=35.6%, MAXDDi=76.6% (standard deviation) STDDDi= 6%.

Figure 7

Extracted DDi from confirmed EGJOO patients, TBS images (n=21). MINDDi=29.32%, MAXDDi=63%, STDDDi= 8.9%

Figure 8

DDi results from confirmed non-achalasia patients. MINDDi=24.1%, MAXDDi=58.2%, STDDDi=7.74%.

Figure 9

Extracted PPB from confirmed EGJOO patients. (MINPPB=68.6%, MAXPPB=100% and STDPPB=9.4%).