Robert Warr

Early complications and implant loss in implant-based breast reconstruction with and without acellular dermal matrix (Tecnoss Protexa®): a comparative study.

INTRODUCTION Acellular dermal matrix (ADM) may improve outcomes in implant-based breast reconstruction, but recent evidence suggests complication rates may be higher when ADM is used. We retrospectively compared early complications and implant loss in implant-based breast reconstruction (BR) with and without ADM to evaluate the safety of the procedure in our centre. METHODS Case-notes of consecutive women undergoing implant-based BR from May 2011 to November 2012 were retrospectively reviewed. Data were extracted using a standardised pro-forma and the rate of early complications, major complications and implant loss compared between procedure groups. RESULTS Forty-six implant-based reconstructions were performed for malignancy (n = 31, 67.4%) or prophylaxis (n = 15, 32.6%) in 31 women over the 18-month study period. ADM (Tecnoss Protexa(®), Tecnoss S.r.l.) was used in 31 (67.4%) cases. There were no differences in patient age, BMI, co-morbidities, smoking or chemotherapy between groups, but patients receiving ADM were more likely to have received radiotherapy prior to their reconstruction (n = 6, 30% vs. n = 0, 0%, p = 0.043). The overall rate of early complications was 26.1% (n = 12) but there was no significant difference between procedure groups (standard-n = 4, 27.7% vs. ADM-n = 8, 25.8%; p = 0.950). There were 2 (4.3%) major complications none of which were associated with ADM use (standard-n = 2, 13.3% vs. ADM-n = 0, 0.0%; p = 0.038). There were 6 (13.0%) implant losses of which 4 were in the ADM group (standard-n = 2, 13.3% vs. ADM-n = 4, 12.9%; p = 0.968). All of these were associated with pre-reconstruction radiotherapy. CONCLUSIONS ADM-assisted implant-based reconstruction with Tecnoss Protexa(®) is safe and may improve outcomes for women by facilitating a single-stage procedure. Robust prospective evaluation is now needed to definitively evaluate the role of ADM in implant-based BR.

A new method describing border irregularity of pigmented lesions.

Background/purpose: Automatic quantitative characterization of border irregularity generating useful descriptors is a highly important task for computer‐aided diagnosis of melanoma. This paper proposes a novel approach to describe the border irregularity of melanomas aiming at achieving higher recognition rates.

Sub-lethal effects of exposing the human melanoma cell line Skmel−23 to 532 nm laser light

The human melanoma cell line SKmel‐23 has been used to investigate the sub‐lethal damage that can occur as a result of exposing melanin containing cells to light (532 nm) from a frequency doubled Q‐switched (Nd:YAG) laser. A dose response curve was obtained, which indicates that at energy levels of 0.6 J/cm2 and below no effect on either the viability or growth rate of the cell line was observed. Above this, cells rapidly died and at an energy level of 2.0 J/cm2, only approximately 15% of cells survived. This contrasts with the effects on the G361 melanoma line, which contains far less melanosomes, as an LD50 for this cell line was approximately 5.5 J/cm2. Exposing SKmel‐23 cells to 0.4 J/cm2 of 532 nm light results in a diminution of the number of melanosomes within cells as well as a marked decrease in melanin content, as determined by spectrophotometric assay and electron microscopy. Using the reverse transcriptase polymerase chain reaction technique, the reduction in melanin content of the cells was accompanied by a selective decrease in mRNA coding for tyrosinase, the first enzyme in the biosynthetic pathway for melanin. No decrease in the mRNA coding for the GAPDH protein was observed. Our finding has implications for understanding the control processes that regulate the melanin content of cells and suggests that the model described can be used to further investigate changes that may occur in cells as a result of their exposure to sub‐lethal levels of laser light. Int. J. Cancer 72:1104–1112, 1997.

Obtaining malignant melanoma indicators through statistical analysis of 3D skin surface disruptions

Background/purpose: It has been observed that disruptions in skin patterns are larger for malignant melanoma (MM) than benign lesions. In order to extend the classification results achieved for 2D skin patterns, this work intends to investigate the feasibility of lesion classification using 3D skin surface texture, in the form of surface normals acquired from a previously built six‐light photometric stereo device.

Cutaneous malignant melanoma in the young

Between the years 1967 and 1993, 3246 patients were diagnosed with malignant melanoma at Frenchay Hospital, Bristol. This paper reports 47 patients, 21 years of age or under, including 10 preadolescent cases under 14 years of age. It represents a further follow-up of a cohort originally published from this centre in 1986 in addition to 18 new cases. Most (89%) of the lesions occurred on the trunk and extremities, with females showing a predominance of lesions on the lower limbs. 83% of the melanomas were of the superficial spreading type: 72% invaded to Clark level III and IV. Thickness ranged from 0.29 mm to 50.00 mm (median 1.20 mm). Ulceration was present in 17% of cases and 32% of melanomas arose within a pre-existing small congenital melanocytic naevus. Overall 5-year survival was 81%, with a mean follow-up of 8.5 years. Ulceration and tumour thickness of greater than 1.5 mm were associated with a poor prognosis.

Unsupervised sub‐segmentation for pigmented skin lesions

Background: Early identification of malignant melanoma with the surgical removal of thin lesions is the most effective treatment for skin cancers. A computer‐aided diagnostic system assists to improve the diagnostic accuracy, where segmenting lesion from normal skin is usually considered as the first step. One of the challenges in the automated segmentation of skin lesions arises from the fact that darker areas within the lesion should be considered separate from the more general suspicious lesion as a whole, because these pigmented areas can provide significant additional diagnostic information.

Machine vision 3D skin texture analysis for detection of melanoma

Purpose – The purpose of this paper is to describe innovative machine vision methods that have been employed for the capture and analysis of 3D skin textures; and the resulting potential for assisting with identification of suspicious lesions in the detection of skin cancer.Design/methodology/approach – A machine vision approach has been employed for analysis of 3D skin textures. This involves an innovative application of photometric stereo for the capture of the textures, and a range of methods for analysing and quantifying them, including statistical methods and neural networks.Findings – 3D skin texture has been identified as a useful indicator of skin cancer. It can be used to improve realism of virtual skin reconstructions in tele‐dermatology. 3D texture features can also be combined with 2D features to obtain a more robust classifier for improving diagnostic accuracy, thereby assisting with the long‐term goal of implementing computer‐aided diagnostics for skin cancer.Originality/value – The device d...

A computer assisted diagnosis system for malignant melanoma using 3D skin surface texture features and artificial neural network

It has been observed that disruptions in skin patterns are larger for malignant melanoma than for benign lesions. In contrast to existing work on 2D skin line patterns, this work proposes a computer assisted diagnosis system for malignant melanoma based on acquiring, analysing and classifying 3D skin surface texture features. Specifically, the 3D skin surface texture, in the form of surface normal vectors are acquired from a six-light photometric stereo device, the 3D features from the surface normals are extracted as the residuals between the acquired data and those from a 2D Gaussian model, while a three-layer feedforward neural classifier is used to classify the residuals. Preliminary studies on a sample set including 12 malignant melanomas and 34 benign lesions have given 91.7% sensitivity and 76.4% specificity using the proposed 3D skin surface normal features, which are better than 91.7% sensitivity and 25.7% specificity using the existing 2D skin line pattern features over the same lesion samples. This demonstrates that the proposed computer assisted diagnosis system of malignant melanoma based on 3D features offers an improvement over that based on 2D skin line patterns.

In vivo measurement of skin microrelief using photometric stereo in the presence of interreflections

This paper proposes and describes an implementation of a photometric stereo-based technique for in vivo assessment of three-dimensional (3D) skin topography in the presence of interreflections. The proposed method illuminates skin with red, green, and blue colored lights and uses the resulting variation in surface gradients to mitigate the effects of interreflections. Experiments were carried out on Caucasian, Asian, and African American subjects to demonstrate the accuracy of our method and to validate the measurements produced by our system. Our method produced significant improvement in 3D surface reconstruction for all Caucasian, Asian, and African American skin types. The results also illustrate the differences in recovered skin topography due to the nondiffuse bidirectional reflectance distribution function (BRDF) for each color illumination used, which also concur with the existing multispectral BRDF data available for skin.

Biological indexes based reflectional asymmetry for classifying cutaneous lesions

This paper proposes a novel reflectional asymmetry descriptor to quantize the asymmetry of the cutaneous lesions for the discrimination of malignant melanoma from benign nevi. A pigmentation elevation model of the biological indexes is first constructed, and then the asymmetry descriptor is computed by minimizing the histogram difference of the global point signatures of the pigmentation model. Melanin and Erythema Indexes are used instead of the original intensities in colour space to characterize the pigmentation distribution of the cutaneous lesions. 311 dermoscopy images are used to validate the algorithm performance, where 88.50% sensitivity and 81.92% specificity have been achieved when employing an SVM classifier.