1
|
Vendhan S, Neema S, Vasudevan B, Malla P. Platelet-rich fibrin therapy assisted split-thickness skin graft in a non-healing morphea ulcer. Indian J Dermatol Venereol Leprol 2024; 0:1-2. [PMID: 39152817 DOI: 10.25259/ijdvl_1173_2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 05/04/2024] [Indexed: 08/19/2024]
Affiliation(s)
- Senkadhir Vendhan
- Consultant, Department of Dermatology, Bharat Ratna Dr Babasaheb Ambedkar Memorial Hospital, Mumbai, Maharashtra, India
| | - Shekhar Neema
- Department of Dermatology Command Hospital, Lucknow, Kolkata, India
| | - Biju Vasudevan
- Department of Dermatology, Armed Forces Medical College, Pune, Wanowrie, Maharashtra, India
| | - Prince Malla
- Department of Dermatology, Armed Forces Medical College, Pune, Wanowrie, Maharashtra, India
| |
Collapse
|
2
|
Albagieh H, Alshagroud RS, Aladnan AM, Aldosari B, Alburaykan YB, Almashham LY, Alqasem AA, Alyahya AA, Aboheimed NI. Morphea Involving the Lips and Gingiva: A Rare Case Report. Cureus 2023; 15:e51202. [PMID: 38155978 PMCID: PMC10754225 DOI: 10.7759/cureus.51202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/27/2023] [Indexed: 12/30/2023] Open
Abstract
Morphea is a subtype of scleroderma that does not involve Raynaud's phenomenon or internal organ involvement. It is a connective tissue disease that features the excessive deposition of collagen in the dermis and subcutaneous tissue, leading to a thickening of the dermis and subcutaneous tissue, eventually forming a scar-like lesion. We represent a 19-year-old male Saudi patient displaying a white patch on the marginal gingiva of tooth #21 and multiple yellowish papules on the outer surface of the lip. Both teeth #21 and #22 have experienced recession and bone loss. The patient's clinical history and histopathology revealed characteristic features of localized scleroderma. A treatment was proposed involving immunosuppressants, methotrexate, and pimecrolimus cream along with topical corticosteroids and excimer laser therapy (308 nm). The patient followed the treatment plan for a full month and the white patch quickly improved for the patient. Afterward, the patient has been taking only methotrexate with a significant but gradual improvement. In this paper, we discuss the differential diagnosis to be considered and present an unusual occurrence of localized scleroderma in the oral cavity.
Collapse
Affiliation(s)
- Hamad Albagieh
- Oral Medicine and Diagnostic Sciences, King Saud University, Riyadh, SAU
| | - Rana S Alshagroud
- Oral Medicine and Diagnostic Sciences, King Saud University, Riyadh, SAU
| | | | - Bader Aldosari
- Oral Medicine and Diagnostic Sciences, King Saud University, Riyadh, SAU
| | | | | | | | | | | |
Collapse
|
3
|
Goldman N, Han J, LaChance A. Diagnosis and Management of Cutaneous Manifestations of Autoimmune Connective Tissue Diseases. Clin Cosmet Investig Dermatol 2022; 15:2285-2312. [PMID: 36320926 PMCID: PMC9618245 DOI: 10.2147/ccid.s360801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/19/2022] [Indexed: 11/20/2022]
Abstract
The cutaneous features of autoimmune connective tissue disease pose a unique challenge to patients and clinicians managing these conditions. In this review, we outline the key elements of diagnosis and treatment of cutaneous lupus erythematosus, dermatomyositis, systemic sclerosis, and morphea. This article also aims to present an update on gold standard as well as new and emerging therapies for these conditions. Overall, dermatologists can play a key role in diagnosing and treating autoimmune connective tissue diseases and this review intends to provide an up-to-date toolkit to guide clinical dermatologists in this endeavor.
Collapse
Affiliation(s)
- Nathaniel Goldman
- Department of Dermatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA,New York Medical College, School of Medicine, Valhalla, NY, USA
| | - Joseph Han
- Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Avery LaChance
- Department of Dermatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA,Correspondence: Avery LaChance, Connective Tissue Diseases Clinic, Health Policy and Advocacy, Department of Dermatology, Brigham and Women’s Hospital, Harvard Medical School, 221 Longwood Avenue, Boston, MA, 02215, USA, Tel +1 617-582-6060, Fax +1 617-532-6060, Email
| |
Collapse
|
4
|
Daneshjou R, Vodrahalli K, Novoa RA, Jenkins M, Liang W, Rotemberg V, Ko J, Swetter SM, Bailey EE, Gevaert O, Mukherjee P, Phung M, Yekrang K, Fong B, Sahasrabudhe R, Allerup JAC, Okata-Karigane U, Zou J, Chiou AS. Disparities in dermatology AI performance on a diverse, curated clinical image set. SCIENCE ADVANCES 2022; 8:eabq6147. [PMID: 35960806 PMCID: PMC9374341 DOI: 10.1126/sciadv.abq6147] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/30/2022] [Indexed: 06/10/2023]
Abstract
An estimated 3 billion people lack access to dermatological care globally. Artificial intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However, most AI models have not been assessed on images of diverse skin tones or uncommon diseases. Thus, we created the Diverse Dermatology Images (DDI) dataset-the first publicly available, expertly curated, and pathologically confirmed image dataset with diverse skin tones. We show that state-of-the-art dermatology AI models exhibit substantial limitations on the DDI dataset, particularly on dark skin tones and uncommon diseases. We find that dermatologists, who often label AI datasets, also perform worse on images of dark skin tones and uncommon diseases. Fine-tuning AI models on the DDI images closes the performance gap between light and dark skin tones. These findings identify important weaknesses and biases in dermatology AI that should be addressed for reliable application to diverse patients and diseases.
Collapse
Affiliation(s)
- Roxana Daneshjou
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Kailas Vodrahalli
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Roberto A. Novoa
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | - Melissa Jenkins
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Weixin Liang
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Veronica Rotemberg
- Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Justin Ko
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Susan M. Swetter
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Elizabeth E. Bailey
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Olivier Gevaert
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Pritam Mukherjee
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Michelle Phung
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Kiana Yekrang
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Bradley Fong
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Rachna Sahasrabudhe
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Johan A. C. Allerup
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | | | - James Zou
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Chan-Zuckerberg Biohub, San Francisco, CA, USA
| | - Albert S. Chiou
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| |
Collapse
|