Unsupervised feature correlation model to predict breast abnormal variation maps in longitudinal mammograms.

Breast cancer continues to be a significant cause of mortality among women globally. Timely identification and precise diagnosis of breast abnormalities are critical for enhancing patient prognosis. In this study, we focus on improving the early detection and accurate diagnosis of breast abnormalities, which is crucial for improving patient outcomes and reducing the mortality rate of breast cancer. To address the limitations of traditional screening methods, a novel unsupervised feature correlation network was developed to predict maps indicating breast abnormal variations using longitudinal 2D mammograms. The proposed model utilizes the reconstruction process of current year and prior year mammograms to extract tissue from different areas and analyze the differences between them to identify abnormal variations that may indicate the presence of cancer. The model incorporates a feature correlation module, an attention suppression gate, and a breast abnormality detection module, all working together to improve prediction accuracy. The proposed model not only provides breast abnormal variation maps but also distinguishes between normal and cancer mammograms, making it more advanced compared to the state-of-the-art baseline models. The results of the study show that the proposed model outperforms the baseline models in terms of Accuracy, Sensitivity, Specificity, Dice score, and cancer detection rate.

Granulomatous secondary syphilis: Another diagnostic pitfall for the dermatopathologist.

Syphilis is growing ever more prevalent in the United States with its incidence rising every year. Dermatopathologists need to maintain a high index of suspicion to avoid delayed diagnosis of this treatable disease. Accordingly, it is imperative to be aware of its myriad of presentations-including secondary syphilis with granulomatous inflammation. Most cases show aggregations of epithelioid histiocytes associated with plasma cells. Other patterns include an interstitial granuloma-annulare-like pattern, sarcoidal, and tuberculoid pattern. Immunohistochemical stains for Treponema pallidum may be negative, especially in late secondary or tertiary syphilis. We present a case of nodular secondary syphilis with granulomatous inflammation with negative T. pallidum staining.

Considering a Biologic: What's a Clinician to Do? Screening and Laboratory Monitoring for Biologic Therapies in the Treatment of Psoriasis.

Biologic therapies have revolutionized the treatment of psoriasis; however, these immunomodulatory therapies may increase the risk of reactivation of latent and chronic infections. Tumor necrosis factor alpha (TNF-α) inhibitors, in particular, have been associated with the increased risk of reactivation of tuberculosis (TB) in patients with latent TB, as well as hepatitis B virus (HBV), in patients with chronic HBV infections. Currently, baseline TB tests are the only screening tests supported with strong evidence. High-grade evidence for HBV screening tests is lacking; however, these tests are sometimes performed in clinical practice. We describe current recommendations for screening tests prior to the initiation of biologic therapy.

Feature fusion Siamese network for breast cancer detection comparing current and prior mammograms.

PURPOSE: Automatic detection of very small and nonmass abnormalities from mammogram images has remained challenging. In clinical practice for each patient, radiologists commonly not only screen the mammogram images obtained during the examination, but also compare them with previous mammogram images to make a clinical decision. To design an artificial intelligence (AI) system to mimic radiologists for better cancer detection, in this work we proposed an end-to-end enhanced Siamese convolutional neural network to detect breast cancer using previous year and current year mammogram images. METHODS: The proposed Siamese-based network uses high-resolution mammogram images and fuses features of pairs of previous year and current year mammogram images to predict cancer probabilities. The proposed approach is developed based on the concept of one-shot learning that learns the abnormal differences between current and prior images instead of abnormal objects, and as a result can perform better with small sample size data sets. We developed two variants of the proposed network. In the first model, to fuse the features of current and previous images, we designed an enhanced distance learning network that considers not only the overall distance, but also the pixel-wise distances between the features. In the other model, we concatenated the features of current and previous images to fuse them. RESULTS: We compared the performance of the proposed models with those of some baseline models that use current images only (ResNet and VGG) and also use current and prior images (long short-term memory [LSTM] and vanilla Siamese) in terms of accuracy, sensitivity, precision, F1 score, and area under the curve (AUC). Results show that the proposed models outperform the baseline models and the proposed model with the distance learning network performs the best (accuracy: 0.92, sensitivity: 0.93, precision: 0.91, specificity: 0.91, F1: 0.92 and AUC: 0.95). CONCLUSIONS: Integrating prior mammogram images improves automatic cancer classification, specially for very small and nonmass abnormalities. For classification models that integrate current and prior mammogram images, using an enhanced and effective distance learning network can advance the performance of the models.

Considering a Biologic: What's a Clinician to Do? Management of Biologics in Surgery, Vaccinations, and Cancer.

In the past two decades, biologic therapy has become ubiquitous in the treatment of psoriasis; however, important considerations should be taken with regard to biologic use in the context of surgery, vaccinations, and cancers. With conflicting evidence on the effects of perioperative biologic use, we recommend withholding tumor necrosis factor alpha (TNF-α) inhibitor therapy for one dose prior to surgical procedures.1 Although no studies have shown a direct link between live vaccines and infection in patients receiving biologics, due to the theoretical risk of live vaccines producing infection in patients with altered immune responses, we recommend withholding biologic therapy for 4 to 5 half-lives prior to the administration of live or live-attenuated vaccines.2,3 Finally, although an increased rate of cancer recurrence has not been demonstrated with biologic use, experts recommend withholding biologic therapy for 2 years after the completion of treatment for invasive cancers and 5 years after the completion of treatment for aggressive malignancies (including melanomas, breast cancers, sarcomas, urinary tract cancers, and myelomas)4; however, exceptions should be considered depending on the patient's circumstances and severity of the psoriasis. (SKINmed. 2021;19:17-0).

Topical rapamycin reduces markers of senescence and aging in human skin: an exploratory, prospective, randomized trial.

Aging is a major risk factor for the majority of human diseases, and the development of interventions to reduce the intrinsic rate of aging is expected to reduce the risk for age-related diseases including cardiovascular disease, cancer, and dementia. In the skin, aging manifests itself in photodamage and dermal atrophy, with underlying tissue reduction and impaired barrier function. To determine whether rapamycin, an FDA-approved drug targeting the mechanistic target of rapamycin (mTOR) complex, can reduce senescence and markers of aging in human skin, an exploratory, placebo-controlled, interventional trial was conducted in a clinical dermatology setting. Participants were greater than 40 years of age with evidence of age-related photoaging and dermal volume loss and no major morbidities. Thirty-six participants were enrolled in the study, and nineteen discontinued or were lost to follow-up. A significant (P = 0.008) reduction in p16INK4A protein levels and an increase in collagen VII protein levels (P = 0.0077) were observed among participants at the end of the study. Clinical improvement in skin appearance was noted in multiple participants, and immunohistochemical analysis revealed improvement in histological appearance of skin tissue. Topical rapamycin reduced the expression of the p16INK4A protein consistent with a reduction in cellular senescence. This change was accompanied by relative improvement in clinical appearance of the skin and histological markers of aging and by an increase in collagen VII, which is critical to the integrity of the basement membrane. These results indicate that rapamycin treatment is a potential anti-aging therapy with efficacy in humans.Trial registration ClinicalTrials.gov Identifier: NCT03103893.

Chronic Pruritus Responding to Dupilumab-A Case Series.

BACKGROUND: Chronic pruritus is defined as itch lasting for greater than six weeks. Pruritus is a burdensome manifestation of several internal and external disease states with a significant impact on quality of life. Dupilumab has shown promise in treating a number of conditions including atopic dermatitis (AD) and asthma. Its success in reducing pruritus in AD has generated interest regarding its potential application in other pruritic conditions, such as chronic pruritus of unknown origin, uremic pruritus, and pruigo nodularis. METHODS: In this retrospective analysis, we present a series of 20 recalcitrant pruritus patients seen at a tertiary center treated with off-label dupilumab at standard AD dosing. RESULTS: Dupilumab was successful at reducing itch in all treated patients, leading to complete resolution in 12/20 patients and an overall mean NRSi reduction of 7.55. Dupilumab was well tolerated with no significant adverse effects. CONCLUSIONS: Our case series suggests dupilumab may be a safe and efficacious therapeutic option in several pruritic conditions and demonstrates the need for further studies to better ascertain its place in the pruritus treatment armamentarium.