Study of Individual Characteristic Abdominal Wall Thickness Based on Magnetic Anchored Surgical Instruments.
- Author:
Ding-Hui DONG
;
Wen-Yan LIU
;
Hai-Bo FENG
;
Yi-Li FU
;
Shi HUANG
;
Jun-Xi XIANG
;
Yi LYU
1
Author Information
- Publication Type:Journal Article
- MeSH: Abdominal Wall; anatomy & histology; Adult; Aged; Body Mass Index; Female; Humans; Male; Middle Aged; Minimally Invasive Surgical Procedures; Surgical Instruments; Tomography, X-Ray Computed
- From: Chinese Medical Journal 2015;128(15):2040-2044
- CountryChina
- Language:English
-
Abstract:
BACKGROUNDMagnetic anchored surgical instruments (MASI), relying on magnetic force, can break through the limitations of the single port approach in dexterity. Individual characteristic abdominal wall thickness (ICAWT) deeply influences magnetic force that determines the safety of MASI. The purpose of this study was to research the abdominal wall characteristics in MASI applied environment to find ICAWT, and then construct an artful method to predict ICAWT, resulting in better safety and feasibility for MASI.
METHODSFor MASI, ICAWT is referred to the thickness of thickest point in the applied environment. We determined ICAWT through finding the thickest point in computed tomography scans. We also investigated the traits of abdominal wall thickness to discover the factor that can be used to predict ICAWT.
RESULTSAbdominal wall at C point in the middle third lumbar vertebra plane (L3) is the thickest during chosen points. Fat layer thickness plays a more important role in abdominal wall thickness than muscle layer thickness. "BMI-ICAWT" curve was obtained based on abdominal wall thickness of C point in L3 plane, and the expression was as follow: f(x) = P1 × x 2 + P2 × x + P3, where P1 = 0.03916 (0.01776, 0.06056), P2 = 1.098 (0.03197, 2.164), P3 = -18.52 (-31.64, -5.412), R-square: 0.99.
CONCLUSIONSAbdominal wall thickness of C point at L3 could be regarded as ICAWT. BMI could be a reliable predictor of ICAWT. In the light of "BMI-ICAWT" curve, we may conveniently predict ICAWT by BMI, resulting a better safety and feasibility for MASI.