American journal of clinical pathology最新文献

Objectives: Salivary gland aspirates classified as salivary gland neoplasm of uncertain malignant potential (SUMP) under the Milan System for Reporting Salivary Gland Cytopathology pose a diagnostic challenge due to their indeterminate cytologic features. We evaluate the utility of intraoperative frozen section in risk stratification and in guiding surgical management in SUMP cases.

Methods: We retrospectively reviewed 75 SUMP cases from 2019 to 2024 with paired frozen section and final pathology. Frozen section diagnoses, final pathology, and intraoperative decision-making processes were analyzed.

Results: Frozen section reclassified 89% (67/75) of cases as benign or malignant, while 11% (8/75) remained indeterminate. Excluding indeterminate cases, frozen section demonstrated a diagnostic accuracy of 96% (64/67), with a sensitivity of 81% (13/16) and a specificity of 100% (51/51). Frozen section refined risk stratification by decreasing the baseline risk of malignancy from 23% before frozen section to 6% in benign frozen section cases. Malignant and indeterminate frozen section cases had risks of malignancy of 100% and 13%, respectively (χ2 = 53.84, P < .001). The combination of intraoperative findings and frozen section results influenced surgical management: More extensive resections were performed in 15% (11/75) of patients, whereas the remainder underwent conservative surgery.

Conclusions: Intraoperative frozen section substantially improves risk stratification and informs surgical management in SUMP, though persistent indeterminate cases underscore the need for enhanced preoperative diagnostic strategies.

Objective: Castleman disease represents a heterogeneous group of hematologic conditions with a broad spectrum of histopathologic features. Historically, 2 major Castleman disease subgroups have been described-unicentric Castleman disease and multicentric Castleman disease, based on the extent of the disease. More recently, oligocentric Castleman disease, a subtype that falls between unicentric and multicentric, has been identified. Due to the overlapping features of each category, similarities to other conditions, and a lack of objective diagnostic biomarkers, the diagnosis of Castleman disease remains a challenge. Here, we review the diagnostic criteria of each entity and discuss the features that distinguish them from overlapping diseases.

Methods: This review highlights the clinicopathologic features of multiple cases to depict the wide spectrum of clinical and laboratory characteristics of Castleman disease. It also outlines the diagnostic workup for each subtype.

Results: In Castleman disease, the morphologic findings are nonspecific and represent a histologic pattern rather than a pathognomonic feature that allows definitive separation from other morphologically overlapping entities; therefore, correlation with clinical history, radiologic studies, and laboratory findings is essential to arrive at the correct diagnosis.

Conclusion: Castleman disease represents a spectrum of clinical syndromes with overlapping morphological features.

Objective: Contemporary reporting guidelines require assessment for intraductal carcinoma of the prostate (IDC-P), given its recognition as an adverse prognostic factor. While several benign and malignant mimickers of intraductal carcinoma have been reported and studied, the potential for intraductal aggregates of histiocytes to simulate or complicate assessment of this process has not been addressed in the literature.

Methods: The authors performed a retrospective multi-institutional review of challenging prostate lesions in which intraductal histiocytic aggregates simulated involvement by IDC-P. Pathology reports and slides were reviewed by 3 fellowship-trained genitourinary pathologists, and clinicopathologic features, immunohistochemistry use, and relative difficulty of the diagnosis were assessed.

Results: A total of 47 cases of intraductal histiocytes simulating IDC-P were identified, including 27 needle biopsy, 9 transurethral resection, and 6 radical prostatectomy cases. Overall, 19 cases showed histiocytic aggregates in cases with carcinoma, while 28 occurred in otherwise benign settings. Immunohistochemistry was performed in 14 cases for resolution of the diagnosis. When categorized by the authors in terms of difficulty of the diagnosis, 20 of 47 cases were considered "moderate" or "difficult."

Conclusions: Based on their solid appearance spanning an intact duct, aggregates of histiocytes within prostatic ducts may closely simulate IDC-P. Given the prognostic significance of IDC-P, this potential pitfall merits consideration and targeted use of immunohistochemistry in challenging cases.

Objective: High-grade neuroendocrine neoplasms of the pancreas (PanNENs), which comprise well-differentiated pancreatic neuroendocrine tumors, grade 3 (PanNET G3s) and pancreatic neuroendocrine carcinomas (PanNECs), are rare but aggressive tumors. Accurate differentiation between PanNET G3s and PanNECs remains a diagnostic challenge, despite their distinct biological behavior and treatment strategies. This study aimed to develop a scoring system to improve diagnostic accuracy using readily available clinicopathologic and immunohistochemical data.

Methods: Sixty-six high-grade PanNEN cases underwent clinicopathologic review, immunohistochemistry, and next-generation sequencing. After exclusion of 4 mixed acinar-neuroendocrine carcinomas, 1 diagnostically ambiguous case, and 3 cases with insufficient tissue for next-generation sequencing, 58 cases (29 PanNET G3, 29 PanNEC) were analyzed.

Results: Lasso logistic regression identified predictive features of PanNEC, and multivariable logistic regression was used to assign weights to each factor. Positive predictors of PanNEC included p53 alterations (+4), Rb1 loss (+3), interstitial reaction (+3), co-existing non-neuroendocrine carcinoma (+3), abundant mitoses (+2), and a Ki67 proliferation index greater than 40% (+1). Negative predictors included co-existing PanNET G1/2 (-2), plasmacytoid cells (-1), DAXX/ATRX loss (-1), and somatostatin receptor subtype 2A 3+ (-1). In validation, the average score for PanNEC was 9.52 (median, 10.0); the average score of PanNET G3s was -1.31 (median, -1.0). Using a cutoff of 5.0, the model achieved an area under the curve of 0.989 for distinguishing PanNEC from PanNET G3.

Conclusions: This novel scoring system demonstrated excellent diagnostic performance in differentiating PanNEC from PanNET by integrating morphologic and immunohistochemical features. Prospective studies with larger cohorts are warranted to validate its clinical utility.

Objective: Idiopathic multicentric Castleman disease (iMCD) is a rare condition with a wide range of signs and symptoms that often overlap with other conditions that cause lymphadenopathy. The diagnosis of iMCD remains challenging, even among experts. Our aim is to highlight the heterogeneity of histopathologic features and presentations of iMCD and to provide tools to help diagnose and raise awareness of this rare condition.

Methods: We review the most relevant clinicopathologic aspects of iMCD and present our process to accurately diagnose this condition using a case-based approach. We describe how to incorporate the iMCD diagnostic criteria, including grading of histomorphology, laboratory, and clinical findings.

Results: Here, we describe our system to grade histopathologic features in iMCD. Together with radiologic findings and laboratory and clinical information, this system helps clinicians accurately identify iMCD and its subtypes, leading to more appropriate and timely diagnosis and treatment.

Conclusions: The diagnosis of iMCD can be challenging and requires a multidisciplinary team of hematologists, pathologists/hematopathologists, and other specialists. There is a pressing and unmet clinical need for a harmonized system to grade the histopathologic features of iMCD. This condition should be included in the differential diagnosis when other causes of a lymphoproliferative disorder (eg, infections, autoimmune/inflammatory disorders, malignancy) have been ruled out.

Objective: To identify molecular markers that predict advanced disease in mucin-producing cystic neoplasms of the pancreas.

Methods: In this single-institution study, 454 pancreatic cystic fluid specimens were examined by a clinical next-generation sequencing assay.

Results: TP53 mutations were detected in 25 (7.9%) of 318 specimens harboring KRAS (BRAF or GNAS) mutation(s). Of the 25, 12 had advanced cytology/histology (positive group), and 5 did not have advanced cytology/histology (negative group). Eight cases were classified as indeterminate. Since KRAS and TP53 variant allele frequencies (VAFs) can be as low as 1% to 5%, we analyzed the TP53/KRAS VAF ratio and demonstrated a significantly higher VAF ratio in the positive group (P = .005). A VAF ratio of 1 or higher, interpreted as an indicator of a dominant TP53 clone, and concurrent TP53, CDKN2A, and SMAD4 mutations were seen only in the positive group. Lower TP53 ratios, interpreted as a minor TP53 clone, were seen in all 5 negative group specimens.

Conclusions: These results suggest that VAF ratios and concurrent mutations can be incorporated into multimodality assessments of pancreatic cysts. Longitudinal studies in patients with a lower initial TP53 VAF ratio are warranted to elucidate whether serial VAF ratios are more accurate markers than a single VAF measurement.

Objective: Colorectal cancer surveillance recommendations rely on polyp counts to determine optimal intervals. This study aims to uncover discrepancies in polyp counts between colonoscopy and pathology reports and their clinical implications.

Methods: A retrospective review of 1293 polyp cases from October 1 to December 31, 2019, was performed, comparing the reported number of polyps removed to the number identified pathologically (gross and microscopic). Cases with discrepant polyp counts prompted additional reviews, including colonoscopy reports and glass slides. The potential impact on surveillance interval decisions was further assessed.

Results: Of the 1293 polyp specimens from 600 patients, 1072 (83%) contained a single polyp per container, with no discrepancies. However, in the remaining 221 (17%) specimens that had multiple polyps submitted per container, an exact polyp count was indeterminable in 54 (24%) of these 221 specimens. Among these, polyp count discrepancies in 15 patients potentially influenced surveillance intervals. Overall, the most common discrepancy was a higher number of fragments on gross description and/or glass slides compared to colonoscopy reports and/or a container designator.

Conclusions: Discrepancies in polyp counts more often occur when more than 1 polyp is submitted in a single container. These discrepancies may alter the recommended surveillance colonoscopy intervals. Therefore, close collaboration between pathology and colonoscopy providers-through improved endoscopic documentation, specimen handling, reporting strategies, and feedback-is essential to ensure accurate polyp counts and mitigate these effects. Adopting a single polyp per container approach in those cases where polyp count matters would significantly improve report accuracy and ensure the most appropriate surveillance intervals.

Objective: Myelodysplastic syndrome (MDS) is a heterogeneous set of neoplasms that require careful exclusion of potential mimics before diagnosis. In the absence of identified recurrent cytogenetic or molecular genetic alterations, low-grade MDS can be particularly challenging to diagnose. Despite years of accumulating data demonstrating atypical flow cytometry findings associated with MDS, flow cytometry fails to find significant widespread use for diagnosing MDS primarily due to the varied and often subtle altered flow cytometry findings observed. To address this issue, several groups have developed and reported scoring systems to help discriminate MDS from non-MDS using flow cytometry. Our objective in this article is to review the published scoring systems, as well as emerging role of machine learning in MDS diagnosis.

Methods: Herein, we review many of the recurrent flow cytometric findings and associated reported scoring systems. We also review recent applications of machine learning to MDS and discuss its potential for enabling widespread use of the technology to assist in diagnosing MDS.

Results: Several of the published scoring systems are modified versions of or additions to the Ogata scoring system, with the ELN iFS score performing well in comparison studies. New and evolving machine learning approaches have the potential to facilitate improved use of flow cytometry for faster and more accurate MDS detection and have helped identify more useful features, such as erythroid cell SSC.

Conclusions: Flow cytometry provides additional information that can help in diagnosis of MDS. Multiple scoring systems now exist that have significant potential to improve the standard approach to diagnosing MDS. Although requiring further development and validation, machine learning methods appear promising as an even more sensitive, specific, and rapid approach to using clinical flow cytometry for identification of MDS than the various prior reported scoring methods. We look forward to furthering improvements in flow cytometry for evaluation of patients with MDS, particularly through the developing use of machine learning approaches and other computational methods.