Cytomolecular Classification of Thyroid Nodules Using Fine-Needle Washes Aspiration Biopsies

Fine-needle aspiration biopsies (FNA) represent the gold standard to exclude the malignant nature of thyroid nodules. After cytomorphology, 20-30% of cases are deemed "indeterminate for malignancy" and undergo surgery. However, after thyroidectomy, 70-80% of these nodules are benign. The identification of tools for improving FNA's diagnostic performances is explored by matrix-assisted laser-desorption ionization mass spectrometry imaging (MALDI-MSI). A clinical study was conducted in order to build a classification model for the characterization of thyroid nodules on a large cohort of 240 samples, showing that MALDI-MSI can be effective in separating areas with benign/malignant cells. The model had optimal performances in the internal validation set (n = 70), with 100.0% (95% CI = 83.2-100.0%) sensitivity and 96.0% (95% CI = 86.3-99.5%) specificity. The external validation (n = 170) showed a specificity of 82.9% (95% CI = 74.3-89.5%) and a sensitivity of 43.1% (95% CI = 30.9-56.0%). The performance of the model was hampered in the presence of poor and/or noisy spectra. Consequently, restricting the evaluation to the subset of FNAs with adequate cellularity, sensitivity improved up to 76.5% (95% CI = 58.8-89.3). Results also suggest the putative role of MALDI-MSI in routine clinical triage, with a three levels diagnostic classification that accounts for an indeterminate gray zone of nodules requiring a strict follow-up

Natural Language Processing to extract SNOMED-CT codes from pathological reports

Objective. The use of standardized structured reports (SSR) and suitable terminologies like SNOMED-CT can enhance data retrieval and analysis, fostering large-scale studies and collaboration. However, the still large prevalence of narrative reports in our laboratories warrants alternative and automated labeling approaches. In this project, natural language processing (NLP) methods were used to associate SNOMED-CT codes to structured and unstructured reports from an Italian Digital Pathology Department. Methods. Two NLP-based automatic coding systems (support vector machine, SVM, and long-short term memory, LSTM) were trained and applied to a series of narrative reports. Results. The 1163 cases were tested with both algorithms, showing good performances in terms of accuracy, precision, recall, and F1 score, with SVM showing slightly better performances as compared to LSTM (0.84, 0.87, 0.83, 0.82 vs 0.83, 0.85, 0.83, 0.82, respectively). The integration of an explainability allowed identification of terms and groups of words of importance, enabling fine-tuning, balancing semantic meaning and model performance. Conclusions. AI tools allow the automatic SNOMED-CT labeling of the pathology archives, providing a retrospective fix to the large lack of organization of narrative reports

Spatially Resolved Molecular Approaches for the Characterisation of Non-Invasive Follicular Tumours with Papillary-like Features (NIFTPs)

Noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) are low-risk thyroid lesions most often characterised by RAS-type mutations. The histological diagnosis may be challenging, and even immunohistochemistry and molecular approaches have not yet provided conclusive solutions. This study characterises a set of NIFTPs by Matrix-Assisted Laser Desorption/Ionisation (MALDI)-Mass Spectrometry Imaging (MSI) to highlight the proteomic signatures capable of overcoming histological challenges. Archived formalin-fixed paraffin-embedded samples from 10 NIFTPs (n = 6 RAS-mutated and n = 4 RAS-wild type) were trypsin-digested and analysed by MALDI-MSI, comparing their profiles to normal tissue and synchronous benign nodules. This allowed the definition of a four-peptide signature able to distinguish RAS-mutant from wild-type cases, the latter showing proteomic similarities to hyperplastic nodules. Moreover, among the differentially expressed signals, Peptidylprolyl Isomerase A (PPIA, 1505.8 m/z), which has already demonstrated a role in the development of cancer, was found overexpressed in NIFTP RAS-mutated nodules compared to wild-type lesions. These results underlined that high-throughput proteomic approaches may add a further level of biological comprehension for NIFTPs. In the future, thanks to the powerful single-cell detail achieved by new instruments, the complementary NGS-MALDI imaging sequence might be the correct methodological approach to confirm that the current NIFTP definition encompasses heterogeneous lesions that must be further characterised

Benchmarking digital displays (monitors) for histological diagnoses: the Nephropathology use case

Granular data from the assessment of non-inferiority of different monitors/scanners combination for the evaluation of whole slide images (WSI) for the primary diagnosis of renal diseases on histology following the College of American Pathologists (CAP) guidelines.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Improving the annotation process in computational pathology: from manual to semi-automatic approaches in digital nephropathology

The development of reliable artificial intelligence (AI) algorithms in pathology depends on solid ground truth provided by meticulous annotation of whole slide images (WSI), a time-consuming and operator-dependent process. A benchmark of the available annotation tools is performed to standardize and streamline this process.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Benchmarking digital displays (monitors) for histological diagnoses: the Nephropathology use case

Granular data from the assessment of non-inferiority of different monitors/scanners combination for the evaluation of whole slide images (WSI) for the primary diagnosis of renal diseases on histology following the College of American Pathologists (CAP) guidelines.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Benchmarking digital displays (monitors) for histological diagnoses: the Nephropathology use case

Granular data from the assessment of non-inferiority of different monitors/scanners combination for the evaluation of whole slide images (WSI) for the primary diagnosis of renal diseases on histology following the College of American Pathologists (CAP) guidelines.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Current role of cytopathology in the molecular and computational era: The perspective of young pathologists

: Cytopathology represents a well established diagnostic approach because of its limited cost, reliability, and minimal invasiveness with respect to other methodologies. The evolving complexity of the different classifications systems and the implementation of ancillary techniques to refine the diagnosis is progressively helping in the risk of malignancy stratification, and the adoption of next-generation sequencing techniques contributes to enrich this valuable tool with predictive information, which is always more essential in the tailored medicine era. The recent introduction of digital and computational pathology is further boosting the potentialities of cytopathology, aiding in the interpretation of samples to improve the cost effectiveness of large screening programs and the diagnostic efficiency within intermediate/atypical categories. Moreover, the adoption of artificial intelligence tools is promising to complement molecular investigations, representing a stimulating perspective in the cytopathology field. In this work, the authors tried to summarize the multifaceted nature of this complex and evolving field of pathology, synthesizing the most recent advances and providing the young pathologists' perspective on this fascinating world