Face and scalp basal cell carcinoma treatment: A review of the literature

Basal cell carcinoma (BCC) is the most frequent skin cancer and is characterized by slow growth, even if it can be locally invasive and rarely metastasizes. Many different phenotypic presentations and histopathologic subtypes have been described, and the current guidelines subdivide BCCs into low-risk (nodular and superficial) and high-risk subtypes (micronodular, infiltrating, and morphoeic BCC and those with squamous differentiation). Dermoscopy allows the identification of the features associated with these different subtypes. Compared with the low-risk forms of BCC, more aggressive ones tend to undergo more frequently incomplete surgical excision and perineural invasion, so the identification of these lesions before surgery is extremely important. The gold standard of treatment is surgery, particularly for the H region of the face and infiltrative lesions, but other options are available and selected according to many variables, including body area, age, comorbidities, and clinical, dermoscopic, and histopathological features of the lesion. Moreover, the possible complications of surgical approaches, namely healing defects, failure of skin grafts, and wound infection, should be considered. In this review we discuss the management of BCC localized on the face and scalp, according to the currently available treatment options. </p

Therapeutic Options for the Treatment of Actinic Keratosis with Scalp and Face Localization

Actinic keratosis (AK) is a common skin disease related to ultraviolet chronic exposure, that is now considered a squamous cell carcinoma in situ. Primary skin cancer prevention strategies should be recommended for high risk patients. There is a wide spectrum of treatment options available for AKs, and several variables should be taken into account regarding the best therapeutic choice for each patient. The purpose of this article is to review the current treatment strategies for AKs localized on the face and scalp, with a focus on the practical point of view that could be useful for choosing the best therapeutic option. The two main therapeutic approaches will be distinguished first: lesiondirected and field-directed. Afterwards, the treatment based on clinical type and patient comorbidity will be discussed

Therapeutic Options for the Treatment of Actinic Keratosis with Scalp and Face Localization

Actinic keratosis (AK) is a common skin disease related to ultraviolet chronic exposure, that is now considered a squamous cell carcinoma in situ. Primary skin cancer prevention strategies should be recommended for high risk patients. There is a wide spectrum of treatment options available for AKs, and several variables should be taken into account regarding the best therapeutic choice for each patient. The purpose of this article is to review the current treatment strategies for AKs localized on the face and scalp, with a focus on the practical point of view that could be useful for choosing the best therapeutic option. The two main therapeutic approaches will be distinguished first: lesiondirected and field-directed. Afterwards, the treatment based on clinical type and patient comorbidity will be discussed

Deep learning-based overall survival prediction model in patients with rare cancer: a case study for primary central nervous system lymphoma

Purpose Primary central nervous system lymphoma (PCNSL) is a rare, aggressive form of extranodal non-Hodgkin lymphoma. To predict the overall survival (OS) in advance is of utmost importance as it has the potential to aid clinical decision-making. Though radiomics-based machine learning (ML) has demonstrated the promising performance in PCNSL, it demands large amounts of manual feature extraction efforts from magnetic resonance images beforehand. deep learning (DL) overcomes this limitation.Methods In this paper, we tailored the 3D ResNet to predict the OS of patients with PCNSL. To overcome the limitation of data sparsity, we introduced data augmentation and transfer learning, and we evaluated the results using r stratified k-fold cross-validation. To explain the results of our model, gradient-weighted class activation mapping was applied.Results We obtained the best performance (the standard error) on post-contrast T1-weighted (T1Gd)-area under curve = 0.81(0.03), accuracy = 0.87(0.07), precision = 0.88(0.07), recall = 0.88(0.07) and F1-score = 0.87(0.07), while compared with ML-based models on clinical data and radiomics data, respectively, further confirming the stability of our model. Also, we observed that PCNSL is a whole-brain disease and in the cases where the OS is less than 1 year, it is more difficult to distinguish the tumor boundary from the normal part of the brain, which is consistent with the clinical outcome.Conclusions All these findings indicate that T1Gd can improve prognosis predictions of patients with PCNSL. To the best of our knowledge, this is the first time to use DL to explain model patterns in OS classification of patients with PCNSL. Future work would involve collecting more data of patients with PCNSL, or additional retrospective studies on different patient populations with rare diseases, to further promote the clinical role of our model