Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland

Selected Topics on Lymphoid Lesions in the Head and Neck Regions

Lymphoid tissue located in the head and neck region include multiple regional lymph node chains as well as mucosa associated lymphoid tissue of the conjunctiva, buccal and nasopharyngeal cavities (Waldeyer’s ring), and thyroid and salivary glands. This region is a rich source of antigenic stimuli including infectious agents coming from the outside environment. Many reactive conditions that affect lymphoid tissue in this region may mimic neoplasia. In fact, distinguishing between benign and malignant lymphoid proliferations in the head and neck region is a relatively frequent diagnostic challenge and in many instances, this distinction is not straightforward. It therefore behooves the practicing pathologist to be able to recognize the benign lymphoproliferative disorders that affect this region so as to effectively guide the appropriate clinical management of such patients. Kimura disease, Epstein Barr lymphadenitis, HIV associated salivary gland disease and chronic sialadenitis are benign conditions that not infrequently affect lymphoid tissue in the head and neck region and that share certain overlapping features with malignant lymphoma. In this brief review, we discuss these conditions and highlight clinicopathological features that may help distinguish them from neoplastic lymphoproliferations that may share similar features