• Users Online: 21
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 5  |  Issue : 4  |  Page : 177-180

A novel approach to estimate age and sex from mri measurement of liver dimensions in an Indian (Bengali) Population – A pilot study


1 Calcutta National Medical College, Kolkata, West Bengal, India
2 Department of Forensic and State Medicine, Calcutta National Medical College, Kolkata, West Bengal, India

Date of Submission02-Sep-2019
Date of Decision17-Sep-2019
Date of Acceptance25-Oct-2019
Date of Web Publication11-Dec-2019

Correspondence Address:
Saikat Das
Calcutta National Medical College, Kolkata, West Bengal
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jfsm.jfsm_45_19

Rights and Permissions
  Abstract 


Radiological methods have been used to assess the ossification stages of bones to estimate age and sex, but studies using the growth stages of organs such as the liver for identification purposes have not yet been performed. Liver weight increases with age, reaching a maximum between 41 and 50 years in men and between 51 and 60 years in women. Thereafter, above the age of 50 years, the liver weight decreases again, and the differences in liver weight between men and women are lost. For this reason, we have conducted this study in a population aged between 10 and 40 years. In this study, we attempted to find correlations between liver dimensions (from magnetic resonance imaging [MRI] images) and age and sex in an eastern Indian (Bengali) population. MRI images showing the liver were acquired from people aged between 10 and 40 years visiting the MRI Centre of Calcutta National Medical College. Liver MRI was acquired from 104 people. Chi-square tests showed a significant correlation between age and the mid hepatic point anteroposterior (MHP AP) dimension. However, there was no such significant correlation between age and maximum craniocaudal (Max CC) dimension or between age and maximum transverse dimension. The following discriminant function equation was derived (Df) = 0.04 MHP AP + 0.006 Max CC + 0.031 Max transverse −11.873 (Constant). Using this formula, 60.6% of the original grouped cases from the Eastern Indian Bengali population would be correctly classified. From the forensic point of view, the dimensions of the liver may be of the value of corroborating age and sex in doubtful cases in living individuals, aged between 10 and 40 years.

Keywords: Age, estimation, forensic, liver, magnetic resonance imaging, sex


How to cite this article:
Das S, Ghosh R, Chowdhuri S. A novel approach to estimate age and sex from mri measurement of liver dimensions in an Indian (Bengali) Population – A pilot study. J Forensic Sci Med 2019;5:177-80

How to cite this URL:
Das S, Ghosh R, Chowdhuri S. A novel approach to estimate age and sex from mri measurement of liver dimensions in an Indian (Bengali) Population – A pilot study. J Forensic Sci Med [serial online] 2019 [cited 2020 Nov 24];5:177-80. Available from: https://www.jfsmonline.com/text.asp?2019/5/4/177/272723




  Introduction Top


Identification is one of the most important aspects of medicolegal identification.[1] The estimation of age and sex plays an important role for establishing identity.[2] In recent years, forensic science has demonstrated using radiological methods for age estimation and sex determination in living individuals.[3] Radiological methods have been mostly used to assess the ossification stages of bones, and studies using the growth stages of organs like the liver for identification purposes have not yet been performed.

In general, the liver is considered to be larger in males than in females,[4] with liver weight increasing with age, reaching a maximum between 41 and 50 years in men and 51 and 60 years in women;[4] thereafter, liver weight decreases. As this loss in liver weight starts earlier in men than women, the difference in liver weight between men and women is lost above the age of 50 years. For this reason, we used a population aged between 10 and 40 years.

In this study, we attempted to find relationships between liver dimensions measured on magnetic resonance imaging (MRI) and age and sex in an eastern Indian population using linear regression and discriminant analysis, respectively.


  Methodology Top


Study subjects

This study was conducted on people visiting the MRI Centre of Calcutta National Medical College (CNMC). Ethical clearance was obtained from the Ethics Committee of CNMC, and informed consent was obtained from the study individuals; the individuals did not receive any ionizing radiation from the procedures performed for this study. The study group consisted of 104 people (29 males and 75 females) aged between 10 and 40 years. None of the livers studied showed any pathological condition, and distorted MRI images were excluded from the analysis. Individuals with alcohol drinking habits were excluded.

Magnetic resonance imaging analysis

All MRI images were transferred to a commercially available workstation where they were studied using RadiAnt DICOM Viewer software, and the measurements were noted under the supervision of the center's radiologist.

The following liver measurements were noted from the abdominal MRI:

  1. Mid hepatic point anteroposterior (MHP AP)
  2. Maximum CC to liver tip (Max CC)
  3. Maximum transverse dimension of the liver.


The plane of the horizontal component of the main portal vein was identified and used as a reference point for the measurements. The MHP was defined as the point halfway between the mid vertebra and right lateral margin of the liver at the level of the main portal vein on a transverse section [Figure 1]. The MHP AP measurement was taken from the anterior to the posterior margin of the liver at the level of the mid-hepatic point [Figure 2]. The Max CC dimension was defined as the greatest obtainable craniocaudal (CC) dimension of the liver from the hepatic dome to the liver tip on coronal or sagittal reconstructed images [Figure 3]. The maximum transverse dimension was the maximum measurement from the right to left margins of the liver at the level of the portal vein [Figure 3].
Figure 1: Magnetic resonance imaging of liver showing mid hepatic point dimension

Click here to view
Figure 2: Magnetic resonance imaging of liver showing maximum craniocaudal dimension

Click here to view
Figure 3: Magnetic resonance imaging of liver showing mid hepatic point anteroposterior (line 1) and maximum transverse dimension (line 2)

Click here to view


Statistical analysis

Data analysis was performed using Statistical Package for Social Sciences software (IBM SPSS Statistics for Windows, Version 25.0. IBM Corp., Armonk, NY). Chi-square tests, linear regression, and discriminant function (Df) analysis were used in the study. P < 0.05 was considered statistically significant. Results are expressed in the form of tables, and similarities with other studies are discussed.


  Results Top


A total of 104 individuals were included in the analysis, with 29 being males and 75 females. The minimum age was 11 years, and the maximum age was 40 years.

The P value for the Chi-square test for the relationship between the MHP AP liver dimension and age was 0.041, indicating statistical significance [Table 1].
Table 1: Chi-square tests (age and mid hepatic point anteroposterior relationship)

Click here to view


[Table 2] shows comparisons of mean MHP AP measurements between different 5-year age groups. The mean MHP AP increased with increasing age group (except between 31 and 35 years), suggesting the usefulness of MRI-based MHP AP liver measurements for age determination.
Table 2: Comparison of mean mid hepatic point anteroposterior with age group

Click here to view


In comparison, the P values for the relationships between age and Mac CC and Max transverse measurements were 0.311 and 0.437, respectively, indicating no significant relationship.

The regression models evaluating age as a linear function of the measurements [Figure 4] yielded the following regression equations:{Figure 4}

Males: age = 3.978+ (0.171 × MHP AP) − (0.005 × MaxCC) + (0.004 × MaxTransverse)

Females: age = 2.546+ (0.105 × MHP AP) + (0.085 × MaxCC) − (0.005 × MaxTransverse)

The functions MaxCC/MHP AP, MaxTransverse/MHP AP, MaxCC/MaxTransverse, MaxCC × MHP AP/MaxTransverse, MHP AP × MaxTransverse/MaxCC, MaxCC × MaxTransverse/MHP AP showed no significant associations with age.

Df analysis was performed to identify the variables best discriminating between males and females resulted in the following equation:

Df equation obtained [Table 3] is,
Table 3: Canonical discriminant function coefficients

Click here to view


Df = 0.04 MHP AP + 0.006 Max CC + 0.031 Max Transverse – 11.873 (Constant)

The cutoff value = (0.612 − 0.237)/2 = 0.1875. Above the value of 0.1875, cases were predicted to be male, while below this value, they were predicted to be female [Table 4]. Wilk's lambda for the model was 0.871 signifying moderate power to discriminate between the two sexes [Table 5].
Table 4: Functions at group centroids to calculate cutoff point

Click here to view
Table 5: Wilks' Lambda

Click here to view


Overall, 60.6% of the sample was classified into the correct group by the model, as shown in [Table 6]. Cross-validated results showed 59.6% of the cases to be correctly classified by this model. The formula obtained from the discriminant equation was validated. Univariate Df [Table 7] was used to estimate the relative contribution of each variable to discrimination of sex.
Table 6: Classification results

Click here to view
Table 7: Univariate discriminant function analysis

Click here to view



  Discussion Top


A previous study[5] validated the single hepatic measurements of MHP CC, Max CC, and MHP AP and their products as good indicators of hepatic size and a reliable method for comparing liver size on serial studies. Other indicators may also be used for radiographic measurements.

Our study was distinctive in that we used an organ for identification purposes. The results showed a significant relationship between age and the MHP AP liver dimension. The Df model also was shown to be useful for differentiating male and female individuals. We have used a method involving the identification of the ossification of bones on radiographs and here used a similar method involving liver images, which may be useful in cases of skeletal deformities or mutilation where the liver is still intact and can be examined. However, it should be kept in mind that a limitation of the liver measurement method is that it cannot be performed on dead bodies as the organ shrinks during decomposition. Otherwise, this method should be useful for confirming the age of people where there are doubts overage, and could also be useful in certain medicolegal cases. For example, under the POCSO Act 2012, the Indian government protects children below 18 years from sexual offenses.[6],[7] Every year in India, there is illegal immigration from neighboring countries, and many residents do not have registered birth certificates. For these reasons, our finding may be useful for confirming age.

The growth rates of the body vary between different ethnic groups; therefore, the results of this study, which was conducted on the Bengali population, cannot be generalized to other populations. Our study was the first of its kind to use radiographic measurements of organs to determine age and discriminate sex, and for this reason, we recommend conducting similar such studies on other populations to build a database in order for this method to be used for routine purposes, keeping in mind the expense of the procedure.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Krogman WM, Iscan YM. The Human Skeleton in Forensic Medicine. 2nd ed. Springfield, Illinois, USA: Charles C. Thomas Pub., Ltd.; 1986.  Back to cited text no. 1
    
2.
Rastogi P, Kanchan T, Menezes RG, Yoganarasimha K. Middle finger length a predictor of stature in the Indian population. Med Sci Law 2009;49:123-6.  Back to cited text no. 2
    
3.
Garamendi PM, Landa MI, Botella MC, Alemán I. Forensic age estimation on digital X-ray images: Medial epiphyses of the clavicle and first rib ossification in relation to chronological age. J Forensic Sci 2011;56 Suppl 1:S3-12.  Back to cited text no. 3
    
4.
Choukèr A, Martignoni A, Dugas M, Eisenmenger W, Schauer R, Kaufmann I, et al. Estimation of liver size for liver transplantation: The impact of age and gender. Liver Transpl 2004;10:678-85.  Back to cited text no. 4
    
5.
Sachit KV, McClure K, Parker L, Mitchell DG, Verma M, Bergin, D. Simple Linear Measurements of the Normal Liver: Interobserver Agreement and Correlation with Hepatic Volume on MRI; 2010. Department of Radiology Faculty Papers. Paper, No. 8.  Back to cited text no. 5
    
6.
Chowdhuri S, Mukhopadhayay P. A study of the socio-demographic profile of the persons accused under POCSO act 2012. Int J Health Res Med Leg Pract 2016;2:50-5.  Back to cited text no. 6
    
7.
Seth R, Srivastava RN. Child sexual abuse: Management and prevention, and protection of children from sexual offences (POCSO) act. Indian Pediatr 2017;54:949-53.  Back to cited text no. 7
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Methodology
Results
Discussion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed2335    
    Printed87    
    Emailed0    
    PDF Downloaded168    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]