In the era of precision medicine, the identification of several predictive biomarkers and the development of innovative therapies have dramatically increased the request of tests to identify specific targets on cytological or histological samples, revolutionizing the management of the tumoral biomaterials. The Food and Drug Administration (FDA) has recently approved a selective neurotrophic tyrosine receptor kinase (NTRK) inhibitor, larotrectinib. Contemporarily, the development of multi-kinase inhibitors with activity in tumors carrying TRK fusions is ongoing. Chromosomal translocations involving the NTRK1, NTRK2, and NTRK3 genes result in constitutive activation and aberrant expression of TRK kinases in numerous cancer types. In this context, the identification of tumors harboring TRK fusions is crucial. Several methods of detection are currently available. We revise the advantages and disadvantages of different techniques used for identifying TRK alterations, including immunohistochemistry, fluorescence in situ hybridization, reverse transcriptase polymerase chain reaction, and next generation sequencing-based approaches. Finally, we propose a diagnostic algorithm based on histology and the relative frequency of TRK fusions in each specific tumor, considering also the economic feasibility in the clinical practice.

Background: Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in colon cancer during the staging phase in order to improve communication between the radiologist, members of multidisciplinary teams and patients. Materials and methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. Results: The final SR version was built by including n = 18 items in the “Patient Clinical Data” section, n = 7 items in the “Clinical Evaluation” section, n = 9 items in the “Imaging Protocol” section and n = 29 items in the “Report” section. Overall, 63 items were included in the final version of the SR. Both in the first and second round, all sections received a higher than good rating: a mean value of 4.6 and range 3.6–4.9 in the first round; a mean value of 5.0 and range 4.9–5 in the second round. In the first round, Cronbach’s alpha (Cα) correlation coefficient was a questionable 0.61. In the first round, the overall mean score of the experts and the sum of scores for the structured report were 4.6 (range 1–5) and 1111 (mean value 74.07, STD 4.85), respectively. In the second round, Cronbach’s alpha (Cα) correlation coefficient was an acceptable 0.70. In the second round, the overall mean score of the experts and the sum of score for structured report were 4.9 (range 4–5) and 1108 (mean value 79.14, STD 1.83), respectively. The overall mean score obtained by the experts in the second round was higher than the overall mean score of the first round, with a lower standard deviation value to underline greater agreement among the experts for the structured report reached in this round. Conclusions: A wide implementation of SR is of critical importance in order to offer referring physicians and patients optimum quality of service and to provide researchers with the best quality data in the context of big data exploitation of available clinical data. Implementation is a complex procedure, requiring mature technology to successfully address the multiple challenges of user-friendliness, organization and interoperability.

(1) Background: Oral potentially malignant disorders (OPMD) represent a fundamental challenge for clinicians, considering the possibility of progression into oral epithelial dysplasia (OED) and oral squamous cell carcinoma (OSCC). Several studies have examined the expression of miRNAs in humans as diagnostic and prognostic biomarkers. Among these, miR-21, miR-27b, and miR-181b proved to be promising. This cohort study evaluated the different expressions of those miRNAs in the saliva of patients with OPMD and OSCC. (2) Methods: Patients with a clinical diagnosis of OPMD and/or OSCC were enrolled; saliva samples were collected; miRNAs were extracted and quantified via qRT-PCR was performed. Data were analyzed by subgroups based on the histopathological diagnosis (OSCC and the grade of OED) using the ΔΔCt method. Saliva from 10 healthy donors was used as the control. One-way ANOVA and Kruskal–Wallis tests were performed to assess the differences between groups. (3) Results: 23 patients for the OPMD group (6 with no dysplasia, 7 with low-grade, and 10 with high-grade dysplasia) and 10 with OSCC were analyzed. MiR-21 did not show any variation among groups; miR-27b was under-expressed in dysplastic lesions (p = 0.046); miR-181b was upregulated in high-grade dysplasia (p = 0.006), increasing with the degree of dysplasia, and decreasing in OSCCs. (4) Conclusions: Salivary miR-27b and miR-181b could be promising biomarkers for oral dysplasia. Further studies are needed to clarify their feasibility.

Background: Radiology is an essential tool in the management of a patient. The aim of this manuscript was to build structured report (SR) Mammography based in Breast Cancer. Methods: A working team of 16 experts (group A) was composed to create a SR for Mammography Breast Cancer. A further working group of 4 experts (group B), blinded to the activities of the group A, was composed to assess the quality and clinical usefulness of the SR final draft. Modified Delphi process was used to assess level of agreement for all report sections. Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency and to measure quality analysis according to the average inter-item correlation. Results: The final SR version was built by including n = 2 items in Personal Data, n = 4 items in Setting, n = 2 items in Comparison with previous breast examination, n = 19 items in Anamnesis and clinical context; n = 10 items in Technique; n = 1 item in Radiation dose; n = 5 items Parenchymal pattern; n = 28 items in Description of the finding; n = 12 items in Diagnostic categories and Report and n = 1 item in Conclusions. The overall mean score of the experts and the sum of score for structured report were 4.9 and 807 in the second round. The Cronbach’s alpha (Cα) correlation coefficient was 0.82 in the second round. About the quality evaluation, the overall mean score of the experts was 3.3. The Cronbach’s alpha (Cα) correlation coefficient was 0.90. Conclusions: Structured reporting improves the quality, clarity and reproducibility of reports across departments, cities, countries and internationally and will assist patient management and improve breast health care and facilitate research.

Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports for lymphoma patients during the staging phase to improve communication between radiologists, members of multidisciplinary teams, and patients. A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology (SIRM), was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. The final SR version was divided into four sections: (a) Patient Clinical Data, (b) Clinical Evaluation, (c) Imaging Protocol, and (d) Report, including n = 13 items in the “Patient Clinical Data” section, n = 8 items in the “Clinical Evaluation” section, n = 9 items in the “Imaging Protocol” section, and n = 32 items in the “Report” section. Overall, 62 items were included in the final version of the SR. A dedicated section of significant images was added as part of the report. In the first Delphi round, all sections received more than a good rating (≥3). The overall mean score of the experts and the sum of score for structured report were 4.4 (range 1–5) and 1524 (mean value of 101.6 and standard deviation of 11.8). The Cα correlation coefficient was 0.89 in the first round. In the second Delphi round, all sections received more than an excellent rating (≥4). The overall mean score of the experts and the sum of scores for structured report were 4.9 (range 3–5) and 1694 (mean value of 112.9 and standard deviation of 4.0). The Cα correlation coefficient was 0.87 in this round. The highest overall means value, highest sum of scores of the panelists, and smallest standard deviation values of the evaluations in this round reflect the increase of the internal consistency and agreement among experts in the second round compared to first round. The accurate statement of imaging data given to referring physicians is critical for patient care; the information contained affects both the decision-making process and the subsequent treatment. The radiology report is the most important source of clinical imaging information. It conveys critical information about the patient’s health and the radiologist’s interpretation of medical findings. It also communicates information to the referring physicians and records this information for future clinical and research use. The present SR was generated based on a multi-round consensus-building Delphi exercise and uses standardized terminology and structures, in order to adhere to diagnostic/therapeutic recommendations and facilitate enrolment in clinical trials, to reduce any ambiguity that may arise from non-conventional language, and to enable better communication between radiologists and clinicians.