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Lymphocytic panniculitis: an algorithmic approach to lymphocytes in subcutaneous tissue
Carolyn J Shiau1, Marie S Abi Daoud2, Se Mang Wong3
1Department of Pathology, Royal Columbian Hospital, New Westminster, British Columbia, Canada Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Insights
Diagnosing lymphocyte-predominant panniculitis can be challenging due to its mimicry of T cell lymphoma. This review offers an algorithmic approach to accurately classify panniculitis, guiding appropriate clinical management.
Area of Science:
- Dermatopathology
- Oncology
- Immunology
Background:
- Panniculitis diagnosis is infrequent for pathologists.
- Lymphocyte-predominant panniculitis poses diagnostic challenges, often mimicking T cell lymphoma.
- Accurate classification is vital for appropriate patient management.
Purpose of the Study:
- To provide an algorithmic approach for diagnosing lymphocyte-predominant panniculitis.
- To differentiate inflammatory panniculitis from subcutaneous T cell lymphoma.
- To aid pathologists and clinicians in challenging cases.
Main Methods:
- Review of diagnostic criteria for panniculitis subtypes.
- Histological feature analysis for septal and lobular patterns.
- Integration of clinical and pathological findings.
Main Results:
- Presents a diagnostic algorithm for lymphocyte-predominant panniculitis.
- Differentiates septal panniculitis (e.g., erythema nodosum) from lobular panniculitis (e.g., lupus panniculitis, subcutaneous panniculitis-like T cell lymphoma).
- Highlights key entities within each pattern.
Conclusions:
- An algorithmic approach facilitates accurate diagnosis of lymphocyte-predominant panniculitis.
- Distinguishing inflammatory causes from T cell lymphoma is crucial for treatment.
- Adequate biopsy and clinician-pathologist collaboration are essential.
Abstract:
The diagnosis of panniculitis is a relatively rare occurrence for many practising pathologists. The smaller subset of lymphocyte-predominant panniculitis is further complicated by the diagnostic consideration of T cell lymphoma involving the subcutaneous tissue, mimicking inflammatory causes of panniculitis. Accurate classification of the panniculitis is crucial to direct clinical management as treatment options may vary from non-medical therapy to immunosuppressive agents to aggressive chemotherapy. Many diseases show significant overlap in clinical and histological features, making the process of determining a specific diagnosis very challenging. However, with an adequate biopsy including skin and deep subcutaneous tissue, a collaborative effort between clinician and pathologist can often lead to a specific diagnosis. This review provides an algorithmic approach to the diagnosis of lymphocyte-predominant panniculitis, including entities of septal-predominant pattern panniculitis (erythema nodosum, deep necrobiosis lipoidica, morphea profunda and sclerosing panniculitis) and lobular-predominant pattern panniculitis (lupus erythematous panniculitis/lupus profundus, subcutaneous panniculitis-like T cell lymphoma, cutaneous γ-δ T cell lymphoma, Borrelia infection and cold panniculitis).
