International Consensus Definition and Diagnostic Criteria for Generalized Pustular Psoriasis From the International Psoriasis Council.

Importance: Generalized pustular psoriasis (GPP) lacks internationally accepted definitions and diagnostic criteria, impeding timely diagnosis and treatment and hindering cross-regional clinical and epidemiological study comparisons. Objective: To develop an international consensus definition and diagnostic criteria for GPP using the modified Delphi method. Evidence Review: The rarity of GPP presents a challenge in acquiring comprehensive published clinical data necessary for developing standardized definition and criteria. Instead of relying on a literature search, 43 statements that comprehensively addressed the fundamental aspects of the definitions and diagnostic criteria for GPP were formulated based on expert reviews of 64 challenging GPP cases. These statements were presented to a panel of 33 global GPP experts for voting, discussion, and refinements in 2 virtual consensus meetings. Consensus during voting was defined as at least 80% agreement; the definition and diagnostic criteria were accepted by all panelists after voting and in-depth discussion. Findings: In the first and second modified Delphi round, 30 (91%) and 25 (76%) experts participated. In the initial Delphi round, consensus was achieved for 53% of the statements, leading to the approval of 23 statements that were utilized to develop the proposed definitions and diagnostic criteria for GPP. During the second Delphi round, the final definition established was, "Generalized Pustular Psoriasis is a systemic inflammatory disease characterized by cutaneous erythema and macroscopically visible sterile pustules." It can occur with or without systemic symptoms, other psoriasis types, and laboratory abnormalities. GPP may manifest as an acute form with widespread pustules or a subacute variant with an annular phenotype. The identified essential criterion was, "Macroscopically visible sterile pustules on erythematous base and not restricted to the acral region or within psoriatic plaques." Conclusions and Relevance: The achievement of international consensus on the definition and diagnostic criteria for GPP underscores the importance of collaboration, innovative methodology, and expert engagement to address rare diseases. Although further validation is needed, these criteria can serve as a reference point for clinicians, researchers, and patients, which may contribute to more accurate diagnosis and improved management of GPP.

Segmentation of acne lesion using fuzzy C-means technique with intelligent selection of the desired cluster.

Segmentation is the basic and important step for digital image analysis and understanding. Segmentation of acne lesions in the visual spectrum of light is very challenging due to factors such as varying skin tones due to ethnicity, camera calibration and the lighting conditions. In this approach the color image is transformed into various color spaces. The image is decomposed into the specified number of homogeneous regions based on the similarity of color using fuzzy C-means clustering technique. Features are extracted for each cluster and average values of these features are calculated. A new objective function is defined that selects the cluster holding the lesion pixels based on the average value of cluster features. In this study segmentation results are generated in four color spaces (RGB, rgb, YIQ, I1I2I3) and two individual color components (I3, Q). The number of clusters is varied from 2 to 6. The experiment was carried out on fifty images of acne patients. The performance of the proposed technique is measured in terms of the three mostly used metrics; sensitivity, specificity, and accuracy. Best results were obtained for Q and I3 color components of YIQ and I1I2I3 color spaces with the number of clusters equal to three. These color components show robustness against non-uniform illumination and maximize the gap between the lesion and skin color.

Gemcitabine and vinorelbine treatment in cutaneous T-cell lymphoma in four patients.

Treatment options for advanced stage cutaneous T-cell lymphoma (CTCL) are limited by the their efficacy and side-effects profile. Gemcitabine, a pyrimidine analogue, has been reported to be efficacious in CTCL. Most of the studies published used gemcitabine as a single agent in treating advanced CTCL. Our small case series demonstrated that a combination of gemcitabine and vinorelbine induced partial remission in all four patients with refractory or advanced CTCL, although the effects were not sustained for a long duration (2-6 months). Two patients had neutropenia and one had acute hepatitis, requiring discontinuation of treatment.

3D surface roughness measurement for scaliness scoring of psoriasis lesions.

Psoriasis is an incurable skin disorder affecting 2-3% of the world population. The scaliness of psoriasis is a key assessment parameter of the Psoriasis Area and Severity Index (PASI). Dermatologists typically use visual and tactile senses in PASI scaliness assessment. However, the assessment can be subjective resulting in inter- and intra-rater variability in the scores. This paper proposes an assessment method that incorporates 3D surface roughness with standard clustering techniques to objectively determine the PASI scaliness score for psoriasis lesions. A surface roughness algorithm using structured light projection has been applied to 1999 3D psoriasis lesion surfaces. The algorithm has been validated with an accuracy of 94.12%. Clustering algorithms were used to classify the surface roughness measured using the proposed assessment method for PASI scaliness scoring. The reliability of the developed PASI scaliness algorithm was high with kappa coefficients>0.84 (almost perfect agreement).

Area assessment of psoriasis lesions for PASI scoring.

Psoriasis is a skin disorder which is caused by a genetic fault. Although there is no cure for psoriasis, there are many treatment modalities to help control the disease. To evaluate treatment efficacy, the current gold standard method, PASI (Psoriasis Area and Severity Index), is used to measure psoriasis severity by evaluating the area, erythema, scaliness and thickness of the plaques. However, the determination of PASI can be tedious and subjective. In this work, we develop a computer vision method that determines one of the PASI parameters, the lesion area. The method isolates healthy and healed skin areas from lesion areas by analysing the hue and chroma information in the CIE L*a*b* colour space. Centroids of healthy skin and psoriasis in the hue-chroma space are determined from selected sample. The Euclidean distance of all pixels from each centroid is calculated. Pixels are assigned to either healthy skin or psorasis lesion classes based on the minimum Euclidean distance. The study involves patients from different ethnic origins having three different skin tones. Results obtained show that the proposed method is able to determine lesion areas with accuracy higher than 90% for 28 out of 30 cases.

Objective assessment of psoriasis erythema for PASI scoring.

Skin colour is vital information in dermatological diagnosis. It reflects pathological condition beneath the skin and commonly being used to indicate the extent of a disease. Psoriasis is a skin disease which is indicated by the appearance of red plaques. Although there is no cure for psoriasis, there are many treatment modalities to help control the disease. To evaluate treatment efficacy, PASI (Psoriasis Area and Severity Index) which is the current gold standard method is used to determine severity of psoriasis lesion. Erythema (redness) is one parameter in PASI. Commonly, the erythema is assessed visually, thus leading to subjective and inconsistent result. In this work, we proposed an objective assessment of psoriasis erythema for PASI scoring. The colour of psoriasis lesion is analyzed by DeltaL, Deltahue, and Deltachroma of CIELAB colour space. References of lesion with different scores are obtained from the selected lesions by two dermatologists. Results based on 38 lesions from 22 patients with various level of skin pigmentation show that PASI erythema score can be determined objectively and consistent with dermatology scoring.

Area assessment of psoriasis lesion for PASI scoring.

Psoriasis is a skin disorder which is caused by genetic fault. There is no cure for psoriasis, however, there are many treatment modalities to help control the disease. To evaluate treatment efficacy, PASI (Psoriasis Area and Severity Index) which is the current gold standard method is used to measure psoriasis severity by evaluating the area, erythema, scaliness and thickness of the plaques. However, the calculation of PASI can be tedious and subjective. In this work, we develop a computer vision method that determines one of the PASI parameter, the lesion area. The method isolates healthy (or healed) skin areas from lesion areas by analyzing the hue and chroma information in the CIE L*a*b* colour space. Centroids of healthy skin and psoriasis in the hue-chroma space are determined from selected sample. Euclidean distance of all pixels from each centroid is calculated. Each pixel is assigned to the class with minimum Euclidean distance. The study involves patients from three different ethnic origins having different skin tones. Results obtained show that the proposed method is comparable to the dermatologist visual approach.