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Sydney Melanoma Diagnostic Centre Research

The Sydney Melanoma Diagnostic Centre has an international reputation in excellence of care, teaching and research in diagnosing melanoma and skin cancer.

The Centre has been at the forefront of the development dermoscopy, digital monitoring and total body photography in this country with seminal articles cited in our guidelines. The Centre has the most cutting-edge platform of diagnostic tools in Australia with ex vivo and in vivo confocal microscopy and, since 2024, LC-OCT . All these machines allow us to non-invasively diagnose suspicious areas and provide mapping of known melanoma/skin cancers.

A major program of research is on Artificial Intelligence that could differentiate melanoma from other lesions based on simple photography, with a promise to be ubiquitous and cheap. 

Our Research Team

Professor Pascale Guitera Dermatologist
Director, Sydney Melanoma Diagnostic Centre
Clinical Academic, University of Sydney
Dr Amanda Glanz Dermatologist and PhD Candidate
Dr Mary Ann El Sharouni Dermatologist
Dr Bruna Gallo Dermatologist
Milapatabeige (Sampi) Kulasekara Clinical Imaging and Research Assistant

Selected Grants

Amount awarded Grant and project details
US$1,190,000 US Department of Defence, 2024-2027
Generalisable and reliable AI for early detection of Melanoma.
Investigators: MSKCC; Melanoma Institute Australia (Pascale Gutiera); Hospital Clinic Barcelona, Northeastern University.
US$888,000 Melanoma Research Alliance, 2024-2027
Enabling AI for Early Detection of Melanoma in Smartphone Images.
Investigators: MSKCC; Melanoma Institute Australia (Pascale Gutiera); Hospital Clinic Barcelona, Northeastern University; Vienna University.
$555,000 Loreal and Damae Collaborations, 2023-2026
New Lc-OCT machine in Australia and its indication. 
Investigators: Guitera P, El Sharouni M, Matin L, Hravey R, Constanza Ramirez Rondon M, Herro J. 
$100,000 Tour de cure, 2023-2025
Is risk factors algorithm data useful for the diagnosis of melanoma with AI dermoscopy?
Investigators: Lo S, Ma J, Guitera P, Martin L.
$5,276,225 Innovation Fund Denmark, 2019-2024
AI augmented training in Skin Cancer diagnostics 
Investigators: Guitera P, et al.

Our Publications

2024

Lo SN, Varey AHR, El Sharouni MA, Scolyer RA, Thompson JF. Online tools for predicting melanoma survival: Including sentinel node status as a variable improves prediction accuracy. J Eur Acad Dermatol Venereol. 2024 Feb;38(2):e182-e184. doi: 10.1111/jdv.19524. Epub 2023 Oct 14.
Lo SN, Varey AHR, El Sharouni MA, Scolyer RA, Thompson JF. Knowledge of sentinel lymph node status improves accuracy when predicting melanoma mortality and selecting patients for adjuvant immunotherapy. J Eur Acad Dermatol Venereol. 2024 Jul;38(7):e638-e639. doi: 10.1111/jdv.19709. Epub 2023 Dec 26.
van Duin IAJ, Verheijden RJ, van Diest PJ, Blokx WAM, El-Sharouni MA, Verhoeff JJC, Leiner T, van den Eertwegh AJM, de Groot JWB, van Not OJ, Aarts MJB, van den Berkmortel FWPJ, Blank CU, Haanen JBAG, Hospers GAP, Piersma D, van Rijn RS, van der Veldt AAM, Vreugdenhil G, Wouters MWJM, Stevense-den Boer MAM, Boers-Sonderen MJ, Kapiteijn E, Suijkerbuijk KPM, Elias SG. A prediction model for response to immune checkpoint inhibition in advanced melanoma. Int J Cancer. 2024 May 15;154(10):1760-1771. doi: 10.1002/ijc.34853. Epub 2024 Jan 31.
Varey AHR, Li I, El Sharouni MA, Simon J, Dedeilia A, Ch'ng S, Saw RPM, Spillane AJ, Shannon KF, Pennington TE, Rtshiladze M, Stretch JR, Nieweg OE, van Akkooi A, Sullivan RJ, Boland GM, Gershenwald JE, van Diest PJ, Scolyer RA, Long GV, Thompson JF, Lo SN. Predicting Recurrence-Free and Overall Survival for Patients With Stage II Melanoma: The MIA Calculator. J Clin Oncol. 2024 Apr 1;42(10):1169-1180. doi: 10.1200/JCO.23.01020. Epub 2024 Feb 5.
Laeijendecker AE, El Sharouni MA, Stathonikos N, Spoto CPE, van de Wiel BA, Eijken EJE, Mulder M, Mooyaart AL, Szumera-Cieckiewicz A, Mihic-Probst D, Massi D, Cook M, Koljenovic S, Alos L, van Diest PJ, van Akkooi ACJ, Blokx W. The difficulty with measuring the largest melanoma tumour diameter in sentinel lymph nodes. J Clin Pathol. 2024 May 17;77(6):372-377. doi: 10.1136/jcp-2023-209354.
Anderson ADG, Lo SN, Guitera P. Commentary: Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance. Front Med (Lausanne). 2024 Feb 6;11:1345659. doi: 10.3389/fmed.2024.1345659.
Ingvar Å, Oloruntoba A, Sashindranath M, Miller R, Soyer HP, Guitera P, Caccetta T, Shumack S, Abbott L, Arnold C, Lawn C, Button-Sloan A, Janda M, Mar V. Minimum labelling requirements for dermatology artificial intelligence-based Software as Medical Device (SaMD): A consensus statement. Australas J Dermatol. 2024 May;65(3):e21-e29. doi: 10.1111/ajd.14222. Epub 2024 Feb 28.
Anderson ADG, Carswell S, Heath H, Koutsis J, Guitera P. Skin cancer referrals by nonmedical practitioners: a prospective observational study. Clin Exp Dermatol. 2024 Aug 22;49(9):1048-1051. doi: 10.1093/ced/llae115.
Oloruntoba A, Ingvar Å, Sashindranath M, Anthony O, Abbott L, Guitera P, Caccetta T, Janda M, Soyer HP, Mar V. Examining labelling guidelines for AI-based software as a medical device: A review and analysis of dermatology mobile applications in Australia. Australas J Dermatol. 2024 Aug;65(5):409-422. doi: 10.1111/ajd.14269. Epub 2024 May 1.
Smith J, Espinoza D, Smit AK, Gallo B, Smith AL, Lo SN, Guitera P, Martin LK, Cust AE. Patient demographic characteristics and risk factors associated with sun protection behaviours in specialist melanoma clinics. Australas J Dermatol. 2024 Sep;65(6):e156-e163. doi: 10.1111/ajd.14314. Epub 2024 Jun 7.
Kurtansky NR, D'Alessandro BM, Gillis MC, Betz-Stablein B, Cerminara SE, Garcia R, Girundi MA, Goessinger EV, Gottfrois P, Guitera P, Halpern AC, Jakrot V, Kittler H, Kose K, Liopyris K, Malvehy J, Mar VJ, Martin LK, Mathew T, Maul LV, Mothershaw A, Mueller AM, Mueller C, Navarini AA, Rajeswaran T, Rajeswaran V, Saha A, Sashindranath M, Serra-García L, Soyer HP, Theocharis G, Vos A, Weber J, Rotemberg V. The SLICE-3D dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection. Sci Data. 2024 Aug 14;11(1):884. doi: 10.1038/s41597-024-03743-w. 
Martin LK, Guitera P, Long GV, Scolyer RA, Cust AE. Towards evidence-based skin checks. Med J Aust. 2024 Oct 21;221(8):407-409. doi: 10.5694/mja2.52443. Epub 2024 Sep 6.
Thompson JR, Gomes L, Kouvelis G, Smith AL, Lo SN, Kasparian NA, Saw RPM, Dieng M, Seaman L, Martin LK, Guitera P, Milne D, Schmid H, Cust AE, Bartula I. Short-Term Effectiveness of a Stepped-Care Model to Address Fear of Cancer Recurrence in Patients With Early-Stage Melanoma. Psychooncology. 2024 Dec;33(12):e70041. doi: 10.1002/pon.70041.
Dempsey K, Ho G, Lo SN, McKeown J, Watts CG, Cust AE, Guitera P, Scolyer RA, Thompson JF, Morton RL; MPOC (Melanoma Patterns of Care) Study Group. Variation in initial biopsy technique for primary melanoma diagnosis: A population-based cohort study in New South Wales, Australia. JAAD Int. 2024 Oct 18;18:90-100. doi: 10.1016/j.jdin.2024.08.024.