American journal of clinical pathology最新文献

Objectives: The high incidence of prostate cancer causes prostatic samples to significantly affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging (WSI) and artificial intelligence (AI) have both gained approval for primary diagnosis in prostate pathology, providing physicians with novel tools for their daily routine.

Methods: A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was carried out in electronic databases to gather the available evidence on the application of AI-based algorithms to prostate cancer.

Results: Of 6290 articles, 80 were included, mostly (59%) dealing with biopsy specimens. Glass slides were digitized to WSI in most studies (89%), roughly two-thirds of which (66%) exploited convolutional neural networks for computational analysis. The algorithms achieved good to excellent results about cancer detection and grading, along with significantly reduced TATs. Furthermore, several studies showed a relevant correlation between AI-identified histologic features and prognostic predictive variables such as biochemical recurrence, extraprostatic extension, perineural invasion, and disease-free survival.

Conclusions: The published evidence suggests that AI can be reliably used for prostate cancer detection and grading, assisting pathologists in the time-consuming screening of slides. Further technologic improvement would help widening AI's adoption in prostate pathology, as well as expanding its prognostic predictive potential.

Objectives: Informal payments (IPs) are unofficial cash or in-kind payments for goods or services that should be covered by the health care system. They are a common but regressive method of financing health care in low- and lower-middle-income countries (LMICs). This study aims to characterize the prevalence and impact of IPs on pathology and laboratory medicine (PALM) services.

Methods: From September 2021 to September 2022, PALM staff were surveyed about the frequency, determinants, and impacts of IPs in their respective workplaces.

Results: In total, 268 responses were received, and 46.6% (125/268) reported experience with IPs. These 125 participants were more likely to work in the public sector and in LMICs. Approximately 65% reported accepting IPs to perform tests or release results. Obtaining faster results was the most commonly perceived reason for patients offering IPs. Overall, participants reported that IPs had more negative than positive impacts on their workplace.

Conclusions: This represents a first step in characterizing IPs within PALM and how this practice may affect access to these services in LMICs. Specifically, the fact that faster turnaround time was the most frequently perceived reason for offering IPs uncovers a potential barrier to improving PALM capacity in these regions.

Objectives: The human papillomavirus (HPV) screening assays from Atila Biosystems, including the new AmpFire (14 type) and ScreenFire RS (13 type), were subjected to a series of validation tests.

Methods: We used a set of samples from the Chinese Multi-Site Screening Trial (previously tested with cobas 4800 and the next-generation SeqHPV) to satisfy Meijer's criteria for clinical end-point validation. We selected 556 self-collected specimens composed of 273 high-risk HPV (hrHPV) positives and 283 hrHPV negatives on the cobas 4800 and SeqHPV. Of the 273 hrHPV-positive cases, 108 had a disease end point of cervical intraepithelial neoplasia grade 2 (CIN2) or higher, including 47 with cervical intraepithelial neoplasia grade 3 (CIN3+) or higher. We simulated the VALGENT framework for inter- and intralaboratory validation and evaluated the new 4-channel risk-stratified ScreenFire assay in a hierarchal fashion.

Results: Both AmpFire and ScreenFire detected 106 (98.1%) of 108 cases with CIN2 or higher, with specificities of 56.7% and 58.1%, respectively. Intralaboratory concordance for 2 runs of AmpFire and ScreenFire was 95.13% and 96.03%, respectively, for overall hrHPV types and 99.10% and 99.46%, respectively, for HPV 16. The interlaboratory concordance of AmpFire and ScreenFire was 93.68% and 94.04% for overall hrHPV and 98.92% and 99.28%, respectively, for HPV 16. Other genotype correlation percentages were similarly high, with κs ranging from 0.86 to 0.94. The ScreenFire RS assay demonstrated excellent "genotype-specific concordance" when evaluated for "clinical guidance" in a hierarchal fashion (noting only the highest risk channel) with both the cobas 4800 and SeqHPV for less than CIN2, CIN2, and CIN3 or higher.

Conclusions: The excellent intra- and interlaboratory reproducibility and the established clinical performance, together with the platforms' simplicity, make these assays particularly applicable to low-resource settings.

Objectives: We conducted the first Irish national study assessing the value of multidisciplinary team meeting review in pathology practice and its impact on error detection before treatment.

Methods: Public and private pathology laboratories across Ireland capture their quality activities using standardized codes and submit their data to a centralized database (National Quality Assurance Intelligence System) overseen by the National Histopathology Quality Improvement (NHQI) program. A total of 1,437,746 histopathology and cytopathology cases submitted to the NHQI program over a 60-month period (January 2017 to December 2021) were included in this study. Cases were analyzed with respect to multidisciplinary team meeting peer review and the presence of a revised report (amended or corrected report), a surrogate marker for error detection before treatment.

Results: Across all cases assessed, 13.74% (197,587) underwent multidisciplinary team meeting discussion. Cases discussed at review had a statistically significantly higher rate of revised reports (1.25% [2470]) than cases not discussed at review (0.16% [1959]) (Pearson χ2, 6619.26; P < .0001; odds ratio, 8.00 [95% CI, 7.54-8.49]). Overall, multidisciplinary team meeting review made it 8 times more likely to detect an error before treatment. Cancer resections had the highest rate of review at 55.29% (46,806), reflecting the prioritization of oncology case discussion at review meetings.

Conclusions: The multidisciplinary team meeting review process plays a valuable role in pathology error detection. A pathologist's participation in the review process comes with a clinically significant workload that needs to be recognized for future workforce planning. This study highlighted the positive role pathologists play in enhancing patient safety.

Objectives: Artificial intelligence-based robotic systems are increasingly used in medical laboratories. This study aimed to test the performance of KANKA (Labenko), a stand-alone, artificial intelligence-based robot that performs sorting and preanalytical quality control of blood tubes.

Methods: KANKA is designed to perform preanalytical quality control with respect to error control and preanalytical sorting of blood tubes. To detect sorting errors and preanalytical inappropriateness within the routine work of the laboratory, a total of 1000 blood tubes were presented to the KANKA robot in 7 scenarios. These scenarios encompassed various days and runs, with 5 repetitions each, resulting in a total of 5000 instances of sorting and detection of preanalytical errors. As the gold standard, 2 experts working in the same laboratory identified and recorded the correct sorting and preanalytical errors. The success rate of KANKA was calculated for both the accurate tubes and those tubes with inappropriate identification.

Results: KANKA achieved an overall accuracy rate of 99.98% and 100% in detecting tubes with preanalytical errors. It was found that KANKA can perform the control and sorting of 311 blood tubes per hour in terms of preanalytical errors.

Conclusions: KANKA categorizes and records problem-free tubes according to laboratory subunits while identifying and classifying tubes with preanalytical inappropriateness into the correct error sections. As a blood acceptance and tube sorting system, KANKA has the potential to save labor and enhance the quality of the preanalytical process.

Objectives: Pathologists interpreting kidney allograft biopsies using the Banff system usually start by recording component scores (eg, i, t, cg) using histopathologic criteria committed to memory. Component scores are then melded into diagnoses using the same manual/mental processes. This approach to complex Banff rules during routine sign-out produces a lack of fidelity and needs improvement.

Methods: We constructed a web-based "smart template" (software-assisted sign-out) system that uniquely starts with upstream Banff-defined additional diagnostic parameters (eg, infection) and histopathologic criteria (eg, percent interstitial inflammation) collectively referred to as feeder data that is then translated into component scores and integrated into final diagnoses using software-encoded decision trees.

Results: Software-assisted sign-out enables pathologists to (1) accurately and uniformly apply Banff rules, thereby eliminating human inconsistencies (present in 25% of the cohort); (2) document areas of improvement; (3) show improved correlation with function; (4) examine t-Distributed Stochastic Neighbor Embedding clustering for diagnosis stratification; and (5) ready upstream incorporation of artificial intelligence-assisted scoring of biopsies.

Conclusions: Compared with the legacy approach, software-assisted sign-out improves Banff accuracy and fidelity, more closely correlates with kidney function, is practical for routine clinical work and translational research studies, facilitates downstream integration with nonpathology data, and readies biopsy scoring for artificial intelligence algorithms.

Objectives: Myeloid neoplasms require comprehensive characterization of genetic abnormalities, including single-nucleotide variants, small insertions and deletions, and fusions and translocations for management. The Oncomine Myeloid Assay GX v2 (Thermo Fisher Scientific) analyzes 17 full genes, 28 hotspot genes, 30 fusion driver genes, and 5 expression genes.

Methods: The validation set included 192 DNA samples, 28 RNA samples, and 9 cell lines and contrived controls. The DNA and RNA were extracted from both peripheral blood and bone marrow. Library preparation, templating, and sequencing was performed on the fully automated Genexus Integrated Sequencer (Thermo Fisher Scientific). The sequencing data were analyzed by manual curation, default Oncomine filters and the Oncomine Reporter (Thermo Fisher Scientific).

Results: Of the 600 reference pathogenic DNA variants targeted by the assay, concordance was seen in 98.3% of unfiltered variant call format files. Precision and reproducibility were 100%, and the lower limit of detection was 2% variant allele frequency for DNA. Inability to detect variants in long homopolymer regions intrinsic to the Ion Torrent chemistry led to 7 missed variants; 100% concordance was seen with reference RNA samples.

Conclusions: This extensive clinical validation of the Oncomine Myeloid Assay GX v2 on the Genexus Integrated Sequencer with its built-in bioinformatics pipeline and Ion Torrent Oncomine Reporter shows robust performance in terms of variant calling accuracy, precision, and reproducibility, with the advantage of a rapid turnaround time of 2 days. The greatest limitation is the inability to detect variants in long homopolymer regions.

Objectives: Large granular lymphocytic leukemia (LGLL) represents a rare neoplasm of mature T cells or natural killer (NK) cells, with an indolent clinical course. Diagnosing LGLL can be challenging because of overlapping features with reactive processes and other mimickers.

Methods: By presenting 2 challenging cases, we elucidate the differentiation of LGLL from its mimics and highlight potential diagnostic pitfalls. A comprehensive review of the clinicopathologic features of LGLL was conducted.

Results: Large granular lymphocytic leukemia displays a diverse spectrum of clinical presentations, morphologies, flow cytometric immunophenotypes, and molecular profiles. These features are also encountered in reactive conditions, T-cell clones of uncertain significance, and NK cell clones of uncertain significance.

Conclusions: In light of the intricate diagnostic landscape, LGLL workup must encompass clinical, morphologic, immunophenotypic, clonal, and molecular findings. Meeting major and minor diagnostic criteria is imperative for the accurate diagnosis of LGLL.

Objectives: We sought to characterize the immunophenotype of acute myeloid leukemia (AML) with CBFB rearrangement and correlate the results with cytogenetic and molecular data.

Methods: Sixty-one cases of AML with CBFB rearrangement were evaluated.

Results: The sample population consisted of 33 men and 28 women, with a median age of 49 years. Flow cytometry immunophenotypic analysis showed that myeloblasts were positive for CD34 and CD117 in all cases, and myeloperoxidase was positive in 52 of 55 (95%) cases. The most common abnormalities included decreased CD38 in 90%, increased CD13 in 85%, increased CD123 in 84%, and decreased HLA-DR in 84% of cases. Monocytes were increased, with a mature immunophenotype, and accounted for 23.7% of total cells. Among 60 cases with available karyotype, inv(16)(p13.1q22) was most common in 50 (83%) cases, followed by t(16;16) (p13.1;q22) in 6 (10%). Type A CBFB::MYH11 transcript was most common, detected in 84% of cases. Mutational analysis showed mutations of NRAS in 37%, FLT3 in 25%, and KIT in 24% of cases. Comparing cases with type A vs non-type A transcripts, blasts in type A cases more frequently exhibited CD64 positivity and increased CD13 levels while showing a lower frequency of CD7 and CD56 expression. Trisomy 22 and mutations in KIT, NF1, and TET2 were identified only in cases with type A transcript.

Conclusions: Myeloblasts of AML with CBFB rearrangement are positive for CD34, CD117, and myeloperoxidase. These neoplasms most frequently carry inv(16)(p13.1q22) and type A fusion transcript. NRAS mutation was the most common mutation. Some immunophenotypic and genetic correlations occurred with different types of transcripts.

Objectives: To evaluate the effectiveness of ChatGPT 4 in generating multiple-choice questions (MCQs) with explanations for pathology board examinations, specifically for digestive system pathology.

Methods: The customized ChatGPT 4 model was developed for MCQ and explanation generation. Expert pathologists evaluated content accuracy and relevance. These MCQs were then administered to pathology residents, followed by an analysis focusing on question difficulty, accuracy, item discrimination, and internal consistency.

Results: The customized ChatGPT 4 generated 80 MCQs covering various gastrointestinal and hepatobiliary topics. While the MCQs demonstrated moderate to high agreement in evaluation parameters such as content accuracy, clinical relevance, and overall quality, there were issues in cognitive level and distractor quality. The explanations were generally acceptable. Involving 9 residents with a median experience of 1 year, the average score was 57.4 (71.8%). Pairwise comparisons revealed a significant difference in performance between each year group (P < .01). The test analysis showed moderate difficulty, effective item discrimination (index = 0.15), and good internal consistency (Cronbach's α = 0.74).

Conclusions: ChatGPT 4 demonstrated significant potential as a supplementary educational tool in medical education, especially in generating MCQs with explanations similar to those seen in board examinations. While artificial intelligence-generated content was of high quality, it necessitated refinement and expert review.