ABSTRACT
BACKGROUND AND OBJECTIVES: In breast carcinoma, epithelial-stromal interactions play a pivotal role in tumor formation and progression, and it must be accurately assessed for a correct extraction of predictive and prognostic biomarkers. Evaluation of preoperative (baseline) neoplasia/stroma ratio and the enumeration of tumor infiltrating lymphocytes (TIL) represent only two conditions in which precise discrimination of cancer epithelium and stromal reaction are relevant. However, subjectivity and expertise of the operators may lead to different degrees of assessment. METHODS: In this paper, we present a fully automated method for the discrimination between neoplastic epithelium and stromal reaction in breast carcinoma. Starting from cell nuclei, the proposed method implements computer vision strategies to split the neoplastic epithelium tissue from the stromal reaction. RESULTS: The algorithm is tested on 100â¯H&E (hematoxylin and eosin) stained images representative of 10 different cases of invasive carcinoma. The algorithm performance in the detection of neoplastic epithelium (compared to manual annotations by an expert pathologist) gave a F1SCORE of 0.8894 and mean jaccardINDEX of 0.8481. CONCLUSIONS: To the best of our knowledge, the proposed method is the first fully automated algorithm for the discrimination between neoplastic epithelium and stromal reaction in H&E stained images of breast tissue. The proposed approach paves the way for an automated and quantitative analysis of predictive and prognostic biomarkers in breast carcinoma.
Subject(s)
Algorithms , Breast Neoplasms , Breast , Cell Nucleus , Image Interpretation, Computer-Assisted , Image Processing, Computer-Assisted , Breast/metabolism , Breast/pathology , Breast Neoplasms/metabolism , Breast Neoplasms/pathology , Cell Nucleus/metabolism , Cell Nucleus/pathology , Female , HumansABSTRACT
OBJECTIVE: The prognostic influence of neuroendocrine (NE) differentiation in prostate cancer patients is not yet properly established. In a series of primary hormone-naive prostate cancers from a patient population that underwent radical prostatectomy, we wanted to determine the relationship between NE phenotype expression and Gleason sum, disease stage, and serum PSA concentration. METHODS: Chromogranin A (CgA) expression was scored and compared in 105 consecutive primary prostate cancers with their homologous preoperative tumor prostate biopsies. RESULTS: High grade or high stage prostate cancers expressed a significantly higher CgA score than low grade or localized diseases (p < 0.005). Both the CgA score of the surgical specimens and the PSA level in the serum increased linearly (p = 0.001). In the samples of many corresponding tumor biopsies no significant CgA staining was found. CONCLUSION: NE differentiation in primary untreated prostate cancer is closely associated with the major prognostic parameters of survival. This association cannot be shown by evaluating the CgA staining in tumor biopsies.
Subject(s)
Chromogranins/metabolism , Prostatic Neoplasms/metabolism , Prostatic Neoplasms/pathology , Aged , Aged, 80 and over , Biomarkers, Tumor/metabolism , Biopsy , Chi-Square Distribution , Humans , Immunohistochemistry , Male , Middle Aged , Neurosecretory Systems/pathology , Phenotype , Prognosis , Prostate-Specific Antigen/blood , Prostatectomy , Prostatic Neoplasms/surgeryABSTRACT
The authors report a case of a large tumour, located in the right hepatic lateral segments, (size: 15 cm), consisting of a hepatocellular carcinoma (size: 10 cm) and an intrahepatic cholangiocarcinoma (size: 5 cm). The mass was detected by ultrasonography during an examination for abdominal pain in an 80-year-old female. After tumour biopsy and histological examination, hepatic resection was performed. The postoperative course was uneventful and the patient was discharged 6 days after surgery. The rarity of this double cancer is stressed.
