Multimodal Approach in the Diagnosis of Urologic Malignancies: Critical Assessment of ChatGPT-4V's Image-Reading Capabilities.

ChatGPT-4V model with image interpretation tested for distinguishing kidney & prostate tumors from normal tissue.

A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing.

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (N = 80) and basal (N = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67-0.99), 0.8 (95% CI: 0.62-0.99), and 0.81 (95% CI: 0.65-0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (p < 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (p < 0.001) and FGFR3 mutational status (p = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of FGFR3-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&E slides.

Exosomal circRNAs: Novel biomarkers and therapeutic targets for urinary tumors.

Exosomal circRNAs have emerged as promising biomarkers and therapeutic targets for urinary tumors. In this review, we explored the intricate role of exosomal circRNAs in urological cancers, focusing on their biological functions, dysregulation in tumors, and potential clinical applications. The review delves into the mechanisms by which exosomal circRNAs contribute to tumor progression and highlights their diagnostic and therapeutic implications. By synthesizing current research findings, we present a compelling case for the significance of exosomal circRNAs in the context of urinary tumors. Furthermore, the review discusses the challenges and opportunities associated with utilizing exosomal circRNAs as diagnostic tools and targeted therapeutic agents. There is a need for further research to elucidate the specific mechanisms of exosomal circRNA secretion and delivery, as well as to enhance the detection methods for clinical translational applications. Overall, this comprehensive review underscores the pivotal role of exosomal circRNAs in urinary tumors and underscores their potential as valuable biomarkers and therapeutic tools in the management of urological cancers.

Utility of The Paris System (TPS) for upper urinary tract cytopathology: correlation with histology follow-up and UroVysion fluorescence in situ hybridization (FISH) analysis.

INTRODUCTION: The Paris System (TPS) provides a uniform reporting system of urine cytology based on well-defined cytologic criteria. Due to their rarity, there are limited data on the utility of TPS in upper urinary tract (UUT) lesions and follow-up histology of cases with abnormal cytology. We aimed to evaluate the utility of TPS for UUT lesions by correlating the cytologic diagnoses using TPS criteria with subsequent histology. Additionally, the diagnostic utility of UroVysion (Abbott) fluorescence in situ hybridization (FISH) was assessed. MATERIALS AND METHODS: A total of 148 UUT cytology specimens were retrospectively identified (2018-2022). Cytologic interpretation was performed using TPS, and then correlated with the findings of concurrent or subsequent histologic specimens. The performance of UroVysion FISH was analyzed. Sensitivity and specificity, positive predictive value (PPV) and negative predictive value (NPV) for detecting high-grade urothelial carcinoma (HGUC) were determined. RESULTS: Among 83 patients who had concurrent or subsequent histologic specimens, cyto-histologic discrepancy was seen in 7 cases (8.4%). The sensitivity, specificity, PPV, and NPV using TPS criteria for detecting HGUC were 87%, and 92%, 96.4%, and 73%, respectively. UroVysion FISH was performed in 21 patients with atypical cytologic findings. The sensitivity and specificity of UroVysion for detecting HGUC was 75% and 86%, respectively, while PPV and NPV were 86% and 75%, respectively. CONCLUSIONS: In our experience, the application of TPS criteria for reporting upper urinary cytology was reliable at detecting UUT lesions, especially HGUC. UroVysion FISH was a valuable ancillary test for detecting HGUC of UUT.

Multiple Fluorescences in Situ Hybridization Status in Excreted Urine Improve Diagnostic Efficacy for Upper Urinary Tract Urothelial Carcinomas.

PURPOSE: To evaluate the diagnostic accuracy of single and multiple fluorescence in situ hybridization (FISH) tests for upper urinary tract cancer (UTUC), we analyzed the diagnostic efficacy of FISH in patients with UTUC and the difference between it and the Tumor Node Metastasis (TNM) stage and grade of the tumor. MATERIALS AND METHODS: Patients treated for UTUC at our institution between 2011 and 2021 who had not been previously diagnosed with UTUC were included. Patients were divided into single, two, and multiple (three times or four times) FISH groups based on the number of FISH tests performed on different samples from the same patient, and the diagnostic efficiency of single, two, and multiple FISH tests for muscle-invasive tumors and highgrade tumors were assessed. RESULTS: We included a total of 207 patients with UTUC, and when compared to single FISH, the sensitivity of multiple and double FISH for the diagnosis of UTUC increased from 62% to 76% and 78%, respectively. It went from 67% to 78% and 80% for muscle-invasive UTUC (> = pT2) and from 71% to 79% and 81% for the highest- grade UTUC. CONCLUSION: Multiple FISH improves the diagnostic efficacy of UTUC and helps to differentiate aggressive tumors.

Implementation of The Paris System for Reporting Urine Cytology improves diagnostic accuracy of selective upper urinary tract cytology.

BACKGROUND: The Paris System for Reporting Urine Cytology (TPS) recommends diagnostic criteria for urinary tract cytology, focusing primarily on the detection of high-grade urothelial carcinoma (HGUC) in the lower urinary tract. The second edition of TPS (TPS 2.0), published in 2022, extends these recommendations to the upper urinary tract (UUT); however, there is a lack of comprehensive data on this subject. METHODS: In total, 223 consecutive UUT cytology specimens from 137 patients were retrieved and reclassified according to TPS 2.0 criteria and were compared with the original diagnosis based on the conventional system (CS). Histologic follow-up within a 3-month period was conducted for 43 patients. RESULTS: Histologic follow-up revealed 30 HGUCs, five low-grade urothelial carcinomas (LGUCs), and eight nonneoplastic fibrotic tissues. The risk of high-grade malignancy for each TPS diagnostic category was 16.7% for nondiagnostic/unsatisfactory, 2.3% for negative for HGUC (NHGUC), 42.1% for atypical urothelial cells, 50.0% for suspicious for HGUC (SHGUC), and 81.8% for HGUC. In all five cases of histologically diagnosed LGUC, the cytologic diagnosis was NHGUC. When SHGUC/HGUC was considered positive, the diagnostic accuracy of TPS had 63% sensitivity, 95% specificity, a 90% negative predictive value, and a 79% positive predictive value, which were better than those of CS. In addition, the TPS indices did not differ significantly between the specimens obtained before and after the application of contrast reagents. CONCLUSIONS: TPS implementation improved the accuracy of UUT cytology in predicting histologic HGUC, which was unaffected by the application of contrast reagents. These data indicate the usefulness of TPS for UUT cytology in routine clinical settings.

Predictive and prognostic biomarkers in urological tumours.

Advancements in cutting-edge molecular profiling techniques, such as next-generation sequencing and bioinformatic analytic tools, have allowed researchers to examine tumour biology in detail and stratify patients based on factors linked with clinical outcome and response to therapy. This manuscript highlights the most relevant prognostic and predictive biomarkers in kidney, bladder, prostate and testicular cancers with recognised impact in clinical practice. In bladder and prostate cancer, new genetic acquisitions concerning the biology of tumours have modified the therapeutic scenario and led to the approval of target directed therapies, increasing the quality of patient care. Thus, it has become of paramount importance to choose adequate molecular tests, i.e., FGFR screening for urothelial cancer and BRCA1-2 alterations for prostate cancer, to guide the treatment plan for patients. While no tissue or blood-based biomarkers are currently used in routine clinical practice for renal cell carcinoma and testicular cancers, the field is quickly expanding. In kidney tumours, gene expression signatures might be the key to identify patients who will respond better to immunotherapy or anti-angiogenic drugs. In testicular germ cell tumours, the use of microRNA has outperformed conventional serum biomarkers in the diagnosis of primary tumours, prediction of chemoresistance, follow-up monitoring, and relapse prediction.

The National Health Service urgent cancer referral pathway for suspected urological cancers: early economic evaluation of a risk prediction test.

OBJECTIVES: In the UK, the number of patients urgently referred for suspected cancer is increasing, and providers are struggling to cope with demand. We explore the potential cost-effectiveness of a new risk prediction test - the PinPoint test - to triage and prioritize patients urgently referred with suspected urological cancers. METHODS: Two simulation models were developed to reflect the diagnostic pathways for patients with (i) suspected prostate cancer, and (ii) bladder or kidney cancer, comparing the PinPoint test to current practice. An early economic analysis was conducted from a UK National Health Service (NHS) perspective. The primary outcomes were the percentage of individuals seen within 2 weeks and health care costs. An exploratory analysis was conducted to understand the potential impact of the Pinpoint test on quality-adjusted life years gained. RESULTS: Across both models and applications, the PinPoint test led to more individuals with urological cancer being seen within 2 weeks. Using PinPoint only to prioritize patients led to increased costs overall, whereas using PinPoint to both triage and prioritize patients led to cost savings. The estimated impact on life years gained/lost was very small and highly uncertain. CONCLUSIONS: Using the PinPoint test to prioritize urgent referrals meant that more individuals with urological cancer were seen within 2 weeks, but at additional cost to the NHS. If used as a triage and prioritization tool, the PinPoint test shortens wait times for referred individuals and is cost saving. More data on the impact of short-term delays to diagnosis on health-related quality of life is needed.

Cytologic evaluation of upper urinary tract specimens: An institutional retrospective study using The Paris System for Reporting Urine Cytology second edition with histopathologic follow-up.

OBJECTIVE: Cytologic evaluation of the upper urinary tract (UUT) can be challenging due to instrumentation artefacts. This study retrospectively reviewed UUT specimens using The Paris System for Reporting Urinary Cytopathology, second edition (TPS 2.0), compared it with the original reporting system (ORS) and correlated it with histopathologic follow-up. METHODS: An institutional database was reviewed for the UUT biopsy/resection histopathologic specimens, and we included 52 UUT cytology specimens pertinent to these cases in the study. These specimens were blindly reviewed and reclassified using TPS 2.0. The correlation between TPS 2.0, ORS and histopathologic follow-up was assessed. RESULTS: The UUT cytology specimens corresponded to 21 (40.4%) high-grade urothelial carcinoma (HGUC), 27 (51.9%) low-grade urothelial carcinoma (LGUC) and 4 (7.7%) benign cases on follow-up. For HGGC cases, the associated TPS categories included unsatisfactory (n = 1, 4.8%), negative for HGUC (NHGUC; n = 3, 14.3%), atypical urothelial cells (AUC; n = 6, 28.6%), suspicious for HGUC (SHGUC; n = 3, 14.3%) and HGUC (n = 8, 38.1%), while ORS categorised the specimens as unsatisfactory (n = 1, 4.8%), negative for malignant cells (NFMC; n = 3, 14.3%), AUC (n = 5, 23.8%), low-grade urothelial carcinoma (LGUC; n = 0, 0%), SHGUC (n = 5, 23.8%) and HGUC (n = 7, 33.3%). The risks of high-grade malignancy among cytologic categories were similar between ORS and TPS (p > 0.05). The majority of LGUC were classified as AUC similarly by ORS and TPS (55.6% vs. 59.3%). CONCLUSIONS: Our study demonstrated comparable performance between TPS 2.0 and ORS for UUT cytology specimens. Cytological diagnosis of UUT specimens remains challenging, especially for LGUC.

Urinary tract cytology showing variant morphology and divergent differentiation.

Urothelial carcinoma represents a diverse group of tumours with distinct histologic subtypes, each exhibiting unique cytomorphologic features, architectural growth patterns, and/or well-developed aberrant differentiation. In fact, there are more than 13 subtypes of urothelial carcinoma recognized in the 2022 WHO classification of tumours in the urinary tract. The identification of these subtypes is crucial for an accurate diagnosis of urothelial carcinoma, and many have important clinical implications. Variant/divergent features may coexist with conventional high-grade urothelial carcinoma (HGUC) or present with 100% variant morphology. In urinary tract cytology (UTC), urothelial carcinoma can display divergent differentiation, such as squamous, glandular, or small cell carcinoma differentiation. The use of cell block preparations and immunohistochemistry with available residual urine can enhance diagnostic accuracy. On the other hand, identifying urothelial carcinoma variants, including nested, micropapillary, and plasmacytoid subtypes, poses significant challenges in UTC. Many cases of these variants are only detected retrospectively after variant histology has been established from resection specimens. Moreover, some variants exhibit features inconsistent with the diagnostic criteria for HGUC according to the Paris System for Reporting Urinary Tract Cytology. Nevertheless, the rarity of pure variant morphology and the occurrence of some false negatives for these variant cases are essential to maintain the specificity of UTC overall. This review covers the histology, cytomorphology, and important clinical aspects observed in urothelial carcinoma exhibiting divergent differentiation and various urothelial carcinoma variants detected in UTC.

Smartphone-Based Fluorescent Profiling of Quaternary MicroRNAs in Urine for Rapid Diagnosis of Urological Cancers Using a Multiplexed Isothermal Exponential Amplification Reaction.

Urological cancers such as bladder or prostate cancer represent one of the most malignant tumors that accounts for an extremely high mortality. However, conventionally standard diagnostics for urological cancers are hardly available in low-resource settings. We developed herein a hand-held fluorescent imaging platform by integrating a multiplexed isothermal exponential amplification reaction (EXPAR) with a microgel-enriched methodology for sensitive profiling of quaternary microRNAs (miRNAs) in urine and quick diagnosis of urological cancers at the early stage. The target miRNA mixtures in the urine underwent four parallel EXPARs without cross-reactivity, followed by surface concentration and hybridization by the encoded polyacrylamide microgels. This mix-and-read strategy allowed for one-pot analysis of several key miRNAs simultaneously and provided 5-fold enhancement in fluorescent detection sensitivities compared to the individual EXPAR-based assays. Four urinary miRNAs (let-7a, miRNA-155, -223, and -143) could be quantitatively determined in a wide linear range from 50 fM to 30 nM, with the limits of detection at femtomolar levels. Using a smartphone-based imaging microreader, healthy and cancerous cohorts with prostate, bladder, and renal cell cancers could be discriminated in 30 min with the accuracy >83% using linear discriminant analysis. The developed detection platform has proven to be a portable, noninvasive, and useful complement to the toolbox for miRNA-based liquid biopsies, which holds immense potential and advantage for regular and large-scale applications in early cancer diagnosis.

[Application and evaluation of artificial intelligence TPS-assisted cytologic screening system in urine exfoliative cytology].

Objective: To explore the application of manual screening collaborated with the Artificial Intelligence TPS-Assisted Cytologic Screening System in urinary exfoliative cytology and its clinical values. Methods: A total of 3 033 urine exfoliated cytology samples were collected at the Henan People's Hospital, Capital Medical University, Beijing, China. Liquid-based thin-layer cytology was prepared. The slides were manually read under the microscope and digitally presented using a scanner. The intelligent identification and analysis were carried out using an artificial intelligence TPS assisted screening system. The Paris Report Classification System of Urinary Exfoliated Cytology 2022 was used as the evaluation standard. Atypical urothelial cells and even higher grade lesions were considered as positive when evaluating the recognition sensitivity, specificity, and diagnostic accuracy of artificial intelligence-assisted screening systems and human-machine collaborative cytologic screening methods in urine exfoliative cytology. Among the collected cases, there were also 1 100 pathological tissue controls. Results: The accuracy, sensitivity and specificity of the AI-assisted cytologic screening system were 77.18%, 90.79% and 69.49%; those of human-machine coordination method were 92.89%, 99.63% and 89.09%, respectively. Compared with the histopathological results, the accuracy, sensitivity and specificity of manual reading were 79.82%, 74.20% and 95.80%, respectively, while those of AI-assisted cytologic screening system were 93.45%, 93.73% and 92.66%, respectively. The accuracy, sensitivity and specificity of human-machine coordination method were 95.36%, 95.21% and 95.80%, respectively. Both cytological and histological controls showed that human-machine coordination review method had higher diagnostic accuracy and sensitivity, and lower false negative rates. Conclusions: The artificial intelligence TPS assisted cytologic screening system has achieved acceptable accuracy in urine exfoliation cytologic screening. The combination of manual screening and artificial intelligence TPS assisted screening system can effectively improve the sensitivity and accuracy of cytologic screening and reduce the risk of misdiagnosis.

Advancements and prospects of Raman spectroscopy in urological tumors: a bibliometric analysis.

Raman spectroscopy exhibits potential as a tool for identifying the chemical composition of substances and has witnessed a growing application in urological oncology. This study undertook a bibliometric analysis to chart the present state and future prospects of Raman spectroscopy applications in urological tumors. The present study retrieved literature on the utilization of Raman spectroscopy in urological oncology from the Science Citation Index Expanded of Web of Science Core Collection, spanning from its inception to June 2023. Data from included studies were analyzed using CiteSpace, Python, and Excel. Our study examined 897 articles from 65 countries and identified a significant exponential growth in annual publications. The USA and China were prominent contributors to this field, with high publication rates and funding agencies. Shanghai Jiao Tong University emerged as the most influential institution. The journals Analytical Chemistry and Analyst were found to be the most productive. Our keyword analysis revealed an intense interest for "gold nanoparticle" and "pathology," with the most recent bursts occurring for "surface-enhanced Raman scattering (SERS)," "biomarkers," and "prostate specific antigen." As a detection tool, Raman spectroscopy holds the potential to assist in the identification, management, and prognostication of urological tumors. Notably, adjuvant diagnosis and prognosis evaluation based on SERS of tumor markers is a hot research topic. These findings offer valuable insights into the current state of Raman spectroscopy research in urological oncology, which could inform future studies and clinical practice.

Detection of urological cancers by the signature of organic volatile compounds in urine, from dogs to electronic noses.

PURPOSE OF REVIEW: Urine volatile organic compound (VOC) testing for early detection of urological cancers is a minimally invasive and promising method. The objective of this review was to present the results of recently published work on this subject. RECENT FINDINGS: Organic volatile compounds are produced through oxidative stress and peroxidation of cell membranes, and they are eliminated through feces, urine, and sweat. Studies looking for VOCs in urine for the diagnosis of urological cancers have mostly focused on bladder and prostate cancers. However, the number of patients included in the studies was small. The electronic nose was the most widely used means of detecting VOCs in urine for the detection of urological cancers. MOS sensors and pattern recognition machine learning were more used for the composition of electronic noses. Early detection of urological cancers by detection of VOCs in urine is a method with encouraging results with sensitivities ranging from 27 to 100% and specificities ranging from 72 to 94%. SUMMARY: The olfactory signature of urine from patients with urological cancers is a promising biomarker for the early diagnosis of urological cancers. The electronic nose with its ability to recognize complex odors is an excellent alterative to canine diagnosis and analytical techniques. Nevertheless, additional research improving the technology of Enoses and the methodology of the studies is necessary for its implementation in daily clinical practice.

OncoUroMiR: Circulating miRNAs for Detection and Discrimination of the Main Urological Cancers Using a ddPCR-Based Approach.

The three most common genitourinary malignancies (prostate/kidney/bladder cancers) constitute a substantial proportion of all cancer cases, mainly in the elderly population. Early detection is key to maximizing the patients' survival, but the lack of highly accurate biomarkers that might be used through non-/minimally invasive methods has impaired progress in this domain. Herein, we sought to develop a minimally invasive test to detect and discriminate among those urological cancers based on miRNAs assessment through ddPCR. Plasma samples from 268 patients with renal cell (RCC; n = 119), bladder (BlCa; n = 73), and prostate (PCa; n = 76) carcinomas (UroCancer group), and 74 healthy donors were selected. Hsa-miR-126-3p, hsa-miR-141-3p, hsa-miR-153-5p, hsa-miR-155-5p, hsa-miR-182-5p, hsa-miR-205-5p, and hsa-miR-375-3p levels were assessed. UroCancer cases displayed significantly different circulating hsa-miR-182-5p/hsa-miR-375-3p levels compared to healthy donors. Importantly, the hsa-miR-155-5p/hsa-miR-375-3p panel detected RCC with a high specificity (80.54%) and accuracy (66.04%). Furthermore, the hsa-miR-126-3p/hsa-miR-375-3p panel identified BlCa with a 94.87% specificity and 76.45% NPV whereas higher hsa-miR-126-3p levels were found in PCa patients. We concluded that plasma-derived miRNAs can identify and discriminate among the main genitourinary cancers, with high analytical performance. Although validation in a larger cohort is mandatory, these findings demonstrate that circulating miRNA assessment by ddPCR might provide a new approach for early detection and risk stratification of the most common urological cancers.

Urinary MicroRNAs as Biomarkers of Urological Cancers: A Systematic Review.

MicroRNAs (miRNAs) are emerging as biomarkers for the detection and prognosis of cancers due to their inherent stability and resilience. To summarize the evidence regarding the role of urinary miRNAs (umiRNAs) in the detection, prognosis, and therapy of genitourinary cancers, we performed a systematic review of the most important scientific databases using the following keywords: (urinary miRNA) AND (prostate cancer); (urinary miRNA) AND (bladder cancer); (urinary miRNA) AND (renal cancer); (urinary miRNA) AND (testicular cancer); (urinary miRNA) AND (urothelial cancer). Of all, 1364 articles were screened. Only original studies in the English language on human specimens were considered for inclusion in our systematic review. Thus, a convenient sample of 60 original articles was identified. UmiRNAs are up- or downregulated in prostate cancer and may serve as potential non-invasive molecular biomarkers. Several umiRNAs have been identified as diagnostic biomarkers of urothelial carcinoma and bladder cancer (BC), allowing us to discriminate malignant from nonmalignant forms of hematuria. UmiRNAs could serve as therapeutic targets or recurrence markers of non-muscle-invasive BC and could predict the aggressivity and prognosis of muscle-invasive BC. In renal cell carcinoma, miRNAs have been identified as predictors of tumor detection, aggressiveness, and progression to metastasis. UmiRNAs could play an important role in the diagnosis, prognosis, and therapy of urological cancers.

Large-scale validation study of an improved semiautonomous urine cytology assessment tool: AutoParis-X.

BACKGROUND: Adopting a computational approach for the assessment of urine cytology specimens has the potential to improve the efficiency, accuracy, and reliability of bladder cancer screening, which has heretofore relied on semisubjective manual assessment methods. As rigorous, quantitative criteria and guidelines have been introduced for improving screening practices (e.g., The Paris System for Reporting Urinary Cytology), algorithms to emulate semiautonomous diagnostic decision-making have lagged behind, in part because of the complex and nuanced nature of urine cytology reporting. METHODS: In this study, the authors report on the development and large-scale validation of a deep-learning tool, AutoParis-X, which can facilitate rapid, semiautonomous examination of urine cytology specimens. RESULTS: The results of this large-scale, retrospective validation study indicate that AutoParis-X can accurately determine urothelial cell atypia and aggregate a wide variety of cell-related and cluster-related information across a slide to yield an atypia burden score, which correlates closely with overall specimen atypia and is predictive of Paris system diagnostic categories. Importantly, this approach accounts for challenges associated with the assessment of overlapping cell cluster borders, which improve the ability to predict specimen atypia and accurately estimate the nuclear-to-cytoplasm ratio for cells in these clusters. CONCLUSIONS: The authors developed a publicly available, open-source, interactive web application that features a simple, easy-to-use display for examining urine cytology whole-slide images and determining the level of atypia in specific cells, flagging the most abnormal cells for pathologist review. The accuracy of AutoParis-X (and other semiautomated digital pathology systems) indicates that these technologies are approaching clinical readiness and necessitates full evaluation of these algorithms in head-to-head clinical trials.