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 Table of Contents  
Year : 2018  |  Volume : 13  |  Issue : 4  |  Page : 252-254

Fingerprint abnormalities in systemic sclerosis: Results of a single center pilot study

Department of Clinical Immunology and Rheumatology, Nizam's Institute of Medical Sciences, Hyderabad, Telangana, India

Date of Web Publication18-Nov-2018

Correspondence Address:
Dr. Kodishala Chanakya
206, Manohar Bhavan Apartments, Dwarakapuri Colony, Panjagutta, Hyderabad - 500 082, Telangana
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/injr.injr_10_18

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Background: Fingertip abnormalities in the form of digital ulcers and gangrene is well known in systemic sclerosis (SSc), but little has been described about the frequency and systemic associations of finger print (FP) abnormalities in these patients. Our objective was to study the FP abnormalities in SSc patients and find possible association with digital vasculopathy.
Methods: Patients with SSc and SSc overlap with other connective tissue diseases were screened for FP abnormalities using a Standardization Testing and Quality Certification Directorate-certified biometric FP scanner. FP quality assessment was done by recording the National Institute of Standards and Technology FP Image Quality (NFIQ) scores. NFIQ's 5 levels of quality are intended to be predictive of fingerprint matching. NFIQ = 1 indicates high quality and NFIQ = 5 indicates poor quality FPs. Social difficulties due to fingerprint abnormalities were noted. Ten healthy controls were included for comparison.
Results: Of 37 patients, 29 with SSc and 8 with overlap syndromes, 15 (40.5%) had FP abnormalities in the form of nonrecognition of at least one finger with a median of 2 fingers (range 1–6). The mean NFIQ score of these patients was 4.5 (poor) while mean NFIQ scores in SSc was 3.8. All FPs of 10 controls were recognized, and the mean NFIQ score was 2.2 indicating a better FPs quality. There was no association of FP abnormalities with digital vasculopathy.
Conclusions: In this pilot study, we found that fingerprint abnormalities occur frequently in SSc patients. Documentation of this abnormality should allow the use of other biometric tools for personal identification.

Keywords: Fingerprint loss, scleroderma, systemic sclerosis

How to cite this article:
Chanakya K, Rajasekhar L. Fingerprint abnormalities in systemic sclerosis: Results of a single center pilot study. Indian J Rheumatol 2018;13:252-4

How to cite this URL:
Chanakya K, Rajasekhar L. Fingerprint abnormalities in systemic sclerosis: Results of a single center pilot study. Indian J Rheumatol [serial online] 2018 [cited 2021 Jul 29];13:252-4. Available from:

  Introduction Top

Scleroderma is a clinically heterogeneous disorder characterized by the loss of cutaneous elasticity and accompanying tightness followed by thickening and hardening of the skin (sclerosis). Given that the most obvious signs of systemic sclerosis (SSc) are its cutaneous manifestations and that they occur in most patients, the skin is clearly important in the initial diagnosis of SSc and its subsequent classification into clinical subsets. Skin involvement is crucial in the disease process, and skin thickening provides a surrogate measure of disease severity and has prognostic value. In patients with SSc, an abnormal accumulation of extracellular matrix constituents is the most prominent pathological manifestation of the disease in skin.

Among the multitude of skin manifestations of SSc, fingertip abnormalities are commonly encountered. These include digital pits and ulcerations, digital tapering, Raynaud's phenomenon (RP), digital ischemia, and gangrene. It is noted in clinical practice that these fingertip abnormalities lead to changes in the epidermal ridges of the fingertips causing distortion of the fingerprints. Among the numerous troublesome manifestations of the disease with skin contributing to a considerable part, fingerprint abnormalities are infrequently reported by the patients and seldom observed by clinicians. They are usually reported when the patient cannot get recognized on the basis of fingerprint identification at certain places needing this mode of recognition. It may also come to notice when the past fingerprints do not match to the same patient's current fingerprints.

There are various other primary dermatological conditions which involve destruction of fingerprints.[1] Apart from these, a rare familial dominantly inherited condition adermatoglyphia has absent finger prints (FPs). It is also termed as “the immigration delay disease.”[2]

Although fingertip problems are pathognomonic of SSc, little is known about the frequency, systemic associations of FP abnormalities, and social impact in literature. The current study was taken up to study FP abnormalities in SSc patients and look for association with digital vasculopathy.

  Methods Top

This was a prospective observational study over a period of December 2016 to January 2017 at our institutional which is a tertiary care center. Patients with SSc fulfilling the ACR/EULAR 2013 classification criteria [3] and those with SSc overlap with other connective tissue diseases were eligible for inclusion. We excluded those with active digital ulcers and gangrene as their fingertips cannot be placed on the scanner with adequate pressure to obtain the FPs. Demographic parameters and other clinical features of the disease were noted. Digital vasculopathy was defined as RP complicated by digital ulcer, critical digital ischemia or gangrene, or requiring digital sympathectomy.[4] The social difficulties due to fingerprint abnormalities were also noted.

Eligible patients were screened for FP abnormalities using a Standardization Testing and Quality Certification Directorate-certified biometric FP scanner. FP quality was assessed by the National Institute of Standards and Technology FP image quality (NFIQ) scores.[5] NFIQ's 5 levels of quality are predictive of fingerprint matching. NFIQ = 1 indicates high quality samples and NFIQ = 5 indicates poor quality samples. The NFIQ algorithm is based on an artificial neural network that tries to predict the quality class from 11 features of the image. These features include the numbers of minutiae and image blocks with quality index exceeding several thresholds. The neural network has been trained with a large number of fingerprint images and the corresponding comparison statistics was obtained with different fingerprint verification software. Ten healthy age- and gender-matched controls with no RP were included for comparison.

Ethical approval

The protocol and documents related to this study were reviewed and formally approved by the Institutional Ethics Committee.

  Results Top

Over 1-month period, 41 consecutive patients with SSc and SSc overlap syndrome were screened for FP abnormalities; 4 were excluded because they had active digital ulcers as fingers could not be placed on the scanner [Figure 1]. Of the 37 patients, 29 had SSc (diffuse cutaneous SSc [n = 20] and limited cutaneous SSc [n = 9]), while 8 had overlap syndromes. On history, 17 of the 37 patients reported some difficulty in the past with biometric recognition of their FPs at various places such as registration for government identity cards (Aadhar card) (n = 11), obtaining groceries at ration stores as they have to give FPs (n = 4), and obtaining mobile phone SIM card (n = 2).
Figure 1: Patient disposition in the study

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Three patients in the study had pre-existing deformities of fingers and those finger prints were not captured and considered as unrecognized. Two of these had one deformed finger each, while one patient had three deformed fingers. The other baseline characteristics are given in [Table 1].
Table 1: The baseline clinical characteristics of the patients with systemic sclerosis

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Finger print findings

On screening with biometric scanner, 15 of 37 (40.5%) patients had FP abnormalities. The median number of nonrecognized fingers per person was 2 (range 1–6 fingers). In the control group, all FPs were recognized (100 fingers).

The number of fingers recognized by the biometric scanner in patients was 326 versus 100 fingers in the controls. Therefore, the number of fingers unrecognized among cases was significantly higher than controls, 44 versus 0, P < 0.0001.

The mean NFIQ score of these 15 patients who had FP abnormalities by the biometric scanner was 4.5 (poor) while the mean NFIQ scores in the SSc patients alone (excluding overlap syndrome) was 3.8. Among the 10 controls, all FPs were recognized, and the mean NFIQ score was 2.2 indicating a better FPs quality.

Sixteen of 37 patients had history of digital vasculopathy in the form of digital pits, digital ischemia, or ulcers. Of these 16 patients, 8 had FP recognition difficulty while among the 21 patients with no digital vasculopathy, 7 had FP recognition abnormality [Table 2]. Hence, no association was found between presence of digital vasculopathy and the presence of FP abnormalities (Fisher's exact test, P = 0.3). Similarly, the frequency of pulmonary arterial hypertension, interstitial lung disease, RP, and dysphagia was equal in the groups with and without FP recognition abnormality [Table 2].
Table 2: The frequency of clinical organ involvement in those with and without fingerprint abnormalities

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  Discussion Top

With the advancing technology, modernization, and urbanization, personal identification has become an important aspect of life, be it while using a smartphone with a fingerprint sensor, computer with fingerprint identification or signing in at work place or accessing bank security locks and finally identity cards. In this pilot study, about 40% patients had difficulty with FP recognition and had a poor FP quality and thus becoming social problem for them, especially when needed to use FPs for identification. This leads to loss of government-provided benefits. We however found no relationship between digital vasculopathy and presence of FP abnormalities. The possible explanation could be due to the mechanism by which a biometric scanner captures the FPs which is quite unique. As the finger is pressed onto the glass surface of the scanner, a row of light-emitting diodes emits bright light on it. The reflected light bounces back from the finger to an image sensor, and it identifies a pattern based on the ridges and valleys on the fingers and codes them by a fixed algorithm. The FP is then matched to a previously stored image based on the pattern of ridges and valleys. When the scanner is unable to identify a definite pattern in the finger due to various reasons such as distorted ridges and valleys, break in the continuity of skin, or too much or too less skin secretions, the scanner fails to form a definite pattern and image and hence cannot recognize the FPs. Since digital vasculopathy starts by affecting distal most pulp space, FP captured from more proximal pulp space may not correlate with digital vasculopathy. Popa et al. in 2010 reported a study on structural and biological changes of FP in 25 SSc patients at baseline and followed them for 6 months.[6] They found that in all SSc patients, fingerprints' pore density was lower, papillary combs were more flattened, and papillary grooves narrower than in controls. Epithelial cell DNA levels were significantly higher, but their decrease over time was faster in SSc FP versus controls FP. Morphological constituents of FP significantly deteriorated on follow-up in SSc suggesting accelerated skin degradation.

Our pilot study documents the frequency of inability of recognizing FPs by a biometric scanner in the digital tips of these patients and their possible social implications. Limitations of our study were its short duration, cross-sectional design, small sample size, and no follow-up data. There is a need to conduct a larger study in this regard so that alternate methods of personal identification can be provided to SSc patients.

To conclude, fingerprint abnormalities occur frequently in patients with SSc and SSc overlap syndromes. The quality of FPs in SSc patients is poor. Documentation of this abnormality may allow the use of other biometric tools for personal identification.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Drahansky M, Dolezel M, Urbanek J, Brezinova E, Kim TH. Influence of skin diseases on fingerprint recognition. J Biomed Biotechnol 2012;2012:626148.  Back to cited text no. 1
Burger B, Fuchs D, Sprecher E, Itin P. The immigration delay disease: Adermatoglyphia-inherited absence of epidermal ridges. J Am Acad Dermatol 2011;64:974-80.  Back to cited text no. 2
van den Hoogen F, Khanna D, Fransen J, Johnson SR, Baron M, Tyndall A, et al. 2013 classification criteria for systemic sclerosis: An American College of Rheumatology/European League Against Rheumatism Collaborative Initiative. Arthritis Rheum 2013;65:2737-47.  Back to cited text no. 3
Nihtyanova SI, Brough GM, Black CM, Denton CP. Clinical burden of digital vasculopathy in limited and diffuse cutaneous systemic sclerosis. Ann Rheum Dis 2008;67:120-3.  Back to cited text no. 4
Merkle J, Schwaiger M, Breitenstein M, Bausinger O, Elwart K, Nuppeney M. Towards improving the NIST fingerprint image quality (NFIQ) algorithm. Biosig 2010. p. 29-44.  Back to cited text no. 5
Popa G, Ionitescu R, Potorac R, Mihai C, Bojinca M, Stoica V. Fingerprints evaluation in systemic sclerosis. Rom J Leg Med 2010;18:155-60.  Back to cited text no. 6


  [Figure 1]

  [Table 1], [Table 2]


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