The Additive Value of 3D Total Body Imaging for Sequential Monitoring of Skin Lesions: A Case Series.

BACKGROUND: Timely diagnosis is the cornerstone of melanoma morbidity and mortality reduction. 2D total body photography and dermoscopy are routinely used to assist with early detection of skin malignancies. Polarized 3D total body photography is a novel technique that enables fast image acquisition of almost the entire skin surface. We aimed to determine the added value of 3D total body photography alongside dermoscopy for monitoring cutaneous lesions. METHODS: Lesion images from high-risk individuals were assessed for long-term substantial changes via dermoscopy and 3D total body photography. Three case studies are presented demonstrating how 3D total body photography may enhance lesion analysis alongside traditional dermoscopy. RESULTS: 3D total body photography can assist clinicians by presenting cutaneous lesions in their skin ecosystem, thereby providing additional clinical context and enabling a more holistic assessment to aid dermoscopy interpretation. For lesion cases where previous dermoscopy is unavailable, corresponding 3D images can substitute for baseline dermoscopy. Additionally, 3D total body photography is not susceptible to artificial stretch artefacts. CONCLUSION: 3D total body photography is valuable alongside dermoscopy for monitoring cutaneous lesions. Furthermore, it is capable of surveilling almost the entire skin surface, including areas not traditionally monitored by sequential imaging.

Amelanotic/hypopigmented melanoma in a sibship with oculocutaneous albinism.

Oculocutaneous albinism (OCA) is a rare condition characterized by hypopigmentation. A female proband and her sister, both with primary amelanotic/hypopigmented melanoma, underwent three-dimensional total-body photography and dermoscopy. Both sisters had exome sequencing along with their brother, who had OCA but no history of melanoma. Imaging analysis was consistent with OCA in terms of individual typology angle scores, degree of sun damage, and high naevus counts. Exome data filtered for variants in known OCA and melanoma/naevi susceptibility genes (n = 98) found all siblings were compound heterozygous for TYR mutations (Arg402Ter and Val275Phe), previously reported as causative OCA variants. A rare missense variant in PARP1 (p.Pro377Ser) was solely present in the melanoma-unaffected brother, which is noteworthy as this was previously reported as potentially protective in a familial melanoma pedigree positive for CDKN2A mutations. Evaluation and confirmation of functional impact in larger cohorts could personalize melanoma screening in OCA.

Short-Term Lesion Change Detection for Melanoma Screening With Novel Siamese Neural Network.

Short-term monitoring of lesion changes has been a widely accepted clinical guideline for melanoma screening. When there is a significant change of a melanocytic lesion at three months, the lesion will be excised to exclude melanoma. However, the decision on change or no-change heavily depends on the experience and bias of individual clinicians, which is subjective. For the first time, a novel deep learning based method is developed in this paper for automatically detecting short-term lesion changes in melanoma screening. The lesion change detection is formulated as a task measuring the similarity between two dermoscopy images taken for a lesion in a short time-frame, and a novel Siamese structure based deep network is proposed to produce the decision: changed (i.e. not similar) or unchanged (i.e. similar enough). Under the Siamese framework, a novel structure, namely Tensorial Regression Process, is proposed to extract the global features of lesion images, in addition to deep convolutional features. In order to mimic the decision-making process of clinicians who often focus more on regions with specific patterns when comparing a pair of lesion images, a segmentation loss (SegLoss) is further devised and incorporated into the proposed network as a regularization term. To evaluate the proposed method, an in-house dataset with 1,000 pairs of lesion images taken in a short time-frame at a clinical melanoma centre was established. Experimental results on this first-of-a-kind large dataset indicate that the proposed model is promising in detecting the short-term lesion change for objective melanoma screening.

Using the Integrative Model of Behavioral Prediction to Understand Female Breast Cancer Survivors' Barriers and Facilitators for Adherence to a Community-Based Group-Exercise Program.

OBJECTIVES: To identify facilitators and barriers associated with adherence to the EXPINKT exercise program for breast cancer survivors in a convenience sample of women. DATA SOURCES: Focus groups discussions; The Integrative Model of Behavioral Prediction. CONCLUSION: Findings suggest that program adherence could be achieved by the establishment, via staff and processes, of a positive and safe exercise environment, which instills a sense of accountability while developing exercise self-efficacy. Further, multiple referral pathways and promotion of exercise benefit during and following treatment by oncology nurses may assist in enrolment in the program. IMPLICATIONS FOR NURSING PRACTICE: Oncology nurses may play a unique role in informing and stimulating female breast cancer survivors to partake in breast cancer-specific exercise programs. Results of this study show that most women are unaware of the benefits related to exercising in relation to cancer recovery, as well as the existence of breast cancer-specific exercise programs. Therefore, oncology nurses may play an important role in creating this awareness. Furthermore, shaping a route to adherence to such exercise programs is essential for breast cancer survivors to become and stay sufficiently active.