bims-netuvo Biomed News
on Nerves in tumours of visceral organs
Issue of 2022‒05‒01
three papers selected by
Maksym V. Kopanitsa
The Francis Crick Institute

  1. Arch Dermatol Res. 2022 Apr 25.
      Incidence of basal cell carcinoma (BCC) with perineural invasion (PNI) ranges from 0.178 to 10% depending upon whether conventional pathology (formalin fixed, paraffin embedded) or Mohs micrographic surgery (MMS) (frozen sections) is used. To determine the incidence of BCC with PNI determined by conventional pathology versus MMS. A review of PubMed and EMBASE databases, from their inception to December 18th, 2020, identified articles that determined the incidence of BCC with PNI using conventional pathology or MMS. The general (average) incidence of BCC with PNI as determined by studies that used conventional histopathology and MMS was 0.85 and 2.51%, respectively. The observed incidence of BCC with PNI was not significantly higher using MMS compared to conventional pathology (p = 0.82).
    Keywords:  Basal cell carcinoma; Nonmelanoma skin cancer; Perineural invasion; Perineural spread
  2. Cancer Invest. 2022 Apr 25. 1-25
      We searched international databases to identify evidence that refer to the impact of perineural invasion on survival outcomes of patients with squamous cell vulvar cancer. We identified six retrospective cohort studies that investigated 887 patients. Of those, 234 (26.4%) had perineural invasion in the pathology analysis. Women with perineural invasion were more likely to have inguinal lymph node metastases (HR 3.45, 95% CI 1.12, 10.67). The impact of perineural invasion on progression-free survival rates was significant (HR 1.61, 95% CI 1.21, 2.15) as well as its impact on overall survival rates (HR 2.73, 95% CI 1.94, 3.84).
    Keywords:  meta-analysis; perineural invasion; squamous; vulvar cancer
  3. Front Oncol. 2022 ;12 828904
      Objectives: To compare the predictive performance of different radiomics signatures from multiparametric magnetic resonance imaging (mpMRI), including four sequences when used individually or combined, and to establish and validate an optimal nomogram for predicting perineural invasion (PNI) in rectal cancer (RC) patients.Methods: Our retrospective study included 279 RC patients without preoperative antitumor therapy (194 in the training dataset and 85 in the test dataset) who underwent preoperative mpMRI scan between January 2017 and January 2021. Among them, 72 cases were PNI-positive. Then, clinical and radiological variables were collected, including carcinoembryonic antigen (CEA), radiological tumour stage (T1-4), lymph node stage (N0-2) and so on. Quantitative radiomics features were extracted and selected from oblique axial T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), apparent diffusion coefficient (ADC), and enhanced T1WI (T1CE) sequences. The clinical model was constructed by integrating the final selected clinical and radiological variables. The radiomics signatures included four single-sequence signatures and one fusion signature were built using the respective remaining optimized features. And the nomogram was constructed based on the independent predictors by using multivariable logistic regression. The area under curve (AUC), DeLong test, calibration curve, and decision curve analysis (DCA) were used to evaluate the performance.
    Results: Ultimately, 20 radiomics features were retained from the four sequences-T1WI (n = 4), T2WI (n = 5), ADC (n = 5), and T1CE (n = 6)-to construct four single-sequence radiomics signatures and one fusion radiomics signature. The fusion radiomics signature performed better than four single-sequence radiomics signatures and clinical model (AUCs of 0.835 and 0.773 vs. 0.680-0.737 and 0.666-0.709 in the training and test datasets, respectively). The nomogram constructed by incorporating CEA, tumour stage and rad-score performed best, with AUCs of 0.869 and 0.864 in the training and test datasets, respectively. Delong test showed that the nomogram was significantly different from the clinical model and four single-sequence radiomics signatures (P < 0.05). Moreover, calibration curves demonstrated good agreement, and DCA highlighted benefits of the nomogram.
    Conclusions: The comprehensive nomogram can preoperatively and noninvasively predict PNI status, provide a convenient and practical tool for treatment strategy, and help optimize individualized clinical decision-making in RC patients.
    Keywords:  multiparametric magnetic resonance imaging; nomogram; perineural invasion; radiomics; rectal cancer