Current state of whole slide imaging use in cytopathology: Pros and pitfalls

Viability of Whole-Slide Imaging for Intraoperative Touch Imprint Cytological Diagnosis of Axillary Sentinel Lymph Nodes in Breast Cancer Patients

BACKGROUND

Whole-slide imaging (WSI) is a promising tool in pathology. However, the use of WSI in cytopathology has lagged behind that in histology. We aimed to evaluate the utility of WSI for the intraoperative touch imprint cytological diagnosis of axillary sentinel lymph nodes (SLNs) in breast cancer patients.

METHODS

Glass slides from touch imprint cytology of 480 axillary SLNs were scanned using two different WSI scanners. The intra- and interobserver concordance, accuracy, possible reasons for misdiagnosis, scanning time, and review time for three cytopathologists were compared between WSI and light microscopy (LM).

RESULTS

A total of 4320 diagnoses were obtained. There was substantial to strong intraobserver concordance when comparing reads among paired LM slides and WSI digital slides (κ coefficient ranged from 0.63 to 0.88, and concordance rates ranged from 94.58% to 98.33%). Substantial to strong interobserver agreement was also observed among the three cytopathologists (κ coefficient ranged from 0.67 to 0.85, and concordance rates ranged from 95.42% to 97.92%). The accuracy of LM was slightly higher (average of 98.06%) than that of WSI (averages of 96.81% and 97.78%). The majority of misdiagnoses were false negative diagnoses due to the following top three causes: few cancer cells, confusing cancer cells with histiocytes, and confusing cancer cells with lymphocytes.

CONCLUSIONS

This study is the first to address the feasibility of WSI in touch imprint cytology. The use of WSI for intraoperative touch imprint cytological diagnosis of SLNs is a practical option when experienced staff are not available on-site.

Rapid on-site evaluation and cell blocks: getting the most from the least invasive method in cytopathology

INTRODUCTION

Fine needle aspiration cytology (FNAC) sampling is a minimally invasive procedure done to identify the pathology behind superficial and deep-seated lesions. Rapid on-site evaluation (ROSE) can be an adjunct to the FNACs. Our study aimed to identify the role of ROSE in diagnostic adequacy and to check the benefit of cell block (CB)/cell buttons prepared from the ROSE samples.

MATERIAL AND METHODS

A prospective study was conducted where all patients referred for FNAC were included. ROSE using 1% aqueous toluidine blue stain and CB/cell button preparations were done for the identification of various cytological lesions.

RESULTS

Among 600 cases included in the study most common age group was third and fourth decades with a mean age of 41.6 years and M: F ratio of 1:1.7. Ultrasound-guided procedures were done in 20% of cases. CB preparation was available in 14% of cases. Most CBs were from the cases wherein ROSE was performed 81% (77 out of 86), with CB helping in making an accurate diagnosis in 17% of cases. Lymph nodes 26%, and thyroid 23% were the most common sites for sampling with the highest number of repeat procedures from non-ROSE cases (14%). The non-diagnostic rate for non-ROSE cases was 7.7% (23/300) even after the repeat procedures as compared to 1.3% (4/300) for ROSE. Three slides on average were consumed in ROSE-performed procedures, as compared to an average of 5 slides in non-ROSE. The average turnaround time was 1.7 days for non-ROSE cases and 1.05 for ROSE cases respectively. Cyto-histopathological correlation was available in 40% of cases with a sensitivity of 98.1%, specificity of 96.7%, positive predictive value of 90%, negative predictive value of 99.4%, and diagnostic accuracy of 97%. The correlation of CB, number of slides consumed, and turnaround time among the 2 groups were statistically significant (P value < 0.001).

CONCLUSIONS

ROSE is a method used to assess material aspirated at the time of FNAC procedures to determine the adequacy and to an extent to identify whether the lesion is neoplastic or non-neoplastic. CBs have helped in increasing diagnostic accuracy apart from the fact that the paraffin-embedded tissue material can be used for further studies.

Optimizing the management of thyroid specimens to efficiently generate whole slide images for diagnosis

Transition from optical to digital observation requires an additional procedure in the pathology laboratory, the scanning of glass slides, leading to increased time and digital archive consumption. Thyroid surgical samples often carry the need to collect several tissue fragments that generate many slides to be scanned. This study evaluated the impact of using different inking colours for the surgical margin, section thickness, and glass slide type, in the consumption of time and archive. The series comprehended 40 nodules from 30 patients, including 34 benign nodules in follicular nodular disease, 1 NIFTP, and 5 papillary carcinomas. In 12 nodules, the dominant pattern was microfollicular/solid and in 28 it was macrofollicular. Scanning times/mm2 were longer in red-inked fragments in comparison to green (p = 0.04) and black ones (p = 0.024), and in blue-inked in comparison to green ones (p = 0.043). File sizes/mm2 were larger in red-inked fragments in comparison to green (p = 0.008) and black ones (p = 0.002). The dominant pattern microfollicular/solid was associated with bigger file size/mm2 in comparison with the macrofollicular one (p < 0.001). All scanner outputs increase significantly with the thickness of the section. All scanning outputs increase with the usage of adhesive glass slides in comparison to non-adhesive ones. Small interventions in thyroid sample management that can help optimizing the digital workflow include to prefer black and green inking colours for the surgical margins and 2 µm section in non-adhesive glass slides for increased efficiency.

BD SurePath Direct to Slide (DTS) cervical cytology: Migrating the benefits of liquid-based cytology to low-resource settings

OBJECTIVES

The benefits of liquid-based cytology (LBC) in routine cervical cancer screening are often associated with the availability of instrumented platforms and economic considerations. A low-cost alternative to LBC in low-volume settings remains an unmet need.

METHODS

A multisite evaluation of the BD SurePath (SurePath) LBC Direct to Slide (DTS) method was conducted. The DTS preparations were evaluated across 3 sites. Cytology features for DTS preparation included predetermined thresholds for total cellularity, cell distribution, cellular preservation, and stain quality. Rare event detection was evaluated using SiHa cells spiked into pools from negative cytology specimens. Concordance between Bethesda classification results was evaluated for SurePath LBC and DTS methods using routinely collected SurePath specimens in a split-sample study design.

RESULTS

The DTS specimens met criteria for total cellularity, cell distribution, cellular preservation, and stain quality in more than 98% of all cases. Rare event detection was observed with an average detection of 5 SiHa cells per 2 mL of specimen. Concordant cervical cytology classifications were observed between SurePath LBC and DTS methods.

CONCLUSIONS

The results demonstrate that the DTS process is suitable for routine cervical cytology evaluation. The procedure is reproducible and detected abnormal cervical cells in concordance with standard SurePath LBC preparation.

Changing digital and telecytology practices post COVID-19 comparing ASC survey results from 2016 to 2023

INTRODUCTION

During the COVID-19 pandemic, the need for digital pathology tools became more urgent. However, there needs to be more knowledge of the use in cytology. We aimed to evaluate current digital cytology practices and attitudes and compare the results with a pre-COVID-19 American Society of Cytopathology (ASC) survey.

MATERIALS AND METHODS

Fourteen survey questions assessing current attitudes toward digital cytology were developed from a 2016 ASC Digital Pathology Survey. Ten new survey questions were also created to evaluate telecytology use. The survey was e-mailed to ASC members over 6 weeks in 2023.

RESULTS

A total of 123 individuals responded (116 in 2016). Attitudes toward digital cytology were unchanged; most participants stated digital cytology is beneficial (87% 2023 versus 90% 2016). The percentage of individuals using digital cytology was unchanged (56% in 2016 and 2023). However, telecytology for rapid onsite assessment (ROSE) is now considered the best application (55% 2023 versus 31% 2016). Forty-three institutions reported using digital and telecytology tools; 40% made implementations after 2020; most did not feel that COVID-19 affected digital cytology (56%). Telecytology for ROSE is the most common application now (78%) compared with education (30%) in 2016. Limitations for implementing digital imaging in cytology included inability to focus (38%) and expense (33%).

CONCLUSIONS

General attitudes toward digital tools by the cytology community have essentially remained the same between 2016 and now. However, telecytology for ROSE is increasingly being used, which supports a need for validation and competency guidelines.

The current state of digital cytology and artificial intelligence (AI): global survey results from the American Society of Cytopathology Digital Cytology Task Force

INTRODUCTION

The integration of whole slide imaging (WSI) and artificial intelligence (AI) with digital cytology has been growing gradually. Therefore, there is a need to evaluate the current state of digital cytology. This study aimed to determine the current landscape of digital cytology via a survey conducted as part of the American Society of Cytopathology (ASC) Digital Cytology White Paper Task Force.

MATERIALS AND METHODS

A survey with 43 questions pertaining to the current practices and experiences of WSI and AI in both surgical pathology and cytology was created. The survey was sent to members of the ASC, the International Academy of Cytology (IAC), and the Papanicolaou Society of Cytopathology (PSC). Responses were recorded and analyzed.

RESULTS

In total, 327 individuals participated in the survey, spanning a diverse array of practice settings, roles, and experiences around the globe. The majority of responses indicated there was routine scanning of surgical pathology slides (n = 134; 61%) with fewer respondents scanning cytology slides (n = 150; 46%). The primary challenge for surgical WSI is the need for faster scanning and cost minimization, whereas image quality is the top issue for cytology WSI. AI tools are not widely utilized, with only 16% of participants using AI for surgical pathology samples and 13% for cytology practice.

CONCLUSIONS

Utilization of digital pathology is limited in cytology laboratories as compared to surgical pathology. However, as more laboratories are willing to implement digital cytology in the near future, the establishment of practical clinical guidelines is needed.

Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime

Screening Papanicolaou test samples has proven to be highly effective in reducing cervical cancer-related mortality. However, the lack of trained cytopathologists hinders its widespread implementation in low-resource settings. Deep learning-assisted telecytology diagnosis emerges as an appealing alternative, but it requires the collection of large annotated training datasets, which is costly and time-consuming. In this paper, we demonstrate that the abundance of unlabeled images that can be extracted from Pap smear test whole slide images presents a fertile ground for self-supervised learning methods, yielding performance improvements compared to off-the-shelf pre-trained models for various downstream tasks. In particular, we propose Cervical Cell Copy-Pasting (C3P) as an effective augmentation method, which enables knowledge transfer from public and labeled single-cell datasets to unlabeled tiles. Not only does C3P outperforms naive transfer from single-cell images, but we also demonstrate its advantageous integration into multiple instance learning methods. Importantly, all our experiments are conducted on our introduced in-house dataset comprising liquid-based cytology Pap smear images obtained using low-cost technologies. This aligns with our long-term objective of deep learning-assisted telecytology for diagnosis in low-resource settings.

E-learning module for cytopathology education based on virtual microscopy

INTRODUCTION

In cytopathology education, Virtual Microscopy e-learning modules (VM-eLM) have achieved remarkable results in the improvement and personalization of learning. However, it remains to be determined whether these modules can significantly contribute to improving the accuracy of cytological diagnosis. The aim of this work was to create a VM-eLM for gynecologic cytopathology education designed to improve screening and interpretation skills in two groups of cytologists: experienced and nonexperienced.

MATERIALS AND METHODS

The module was designed in Moodle with both Whole Slide Images and Static Images taken from Papanicolaou smears that were diagnosed as: negative for intraepithelial lesion, low-grade squamous intraepithelial lesion, high-grade squamous intraepithelial lesion, squamous cell carcinoma, or adenocarcinoma. We assessed the effectiveness of the module using 1) clinical quality indicators to measure skill development and 2) a user survey.

RESULTS

After training, participants significantly improved their cytological screening skills, decreasing their false negative diagnosis by 78% in the non-experienced group and eliminating them entirely in the experienced group. Nonexperienced participants also significantly increased their recognition of low-grade squamous intraepithelial lesion and high-grade squamous intraepithelial lesion by 31% and 50%, respectively. Participants positively evaluated the module, highlighting its novelty, the possibility to train remotely, the immediate feedback and the quality of the Whole Slide Images.

CONCLUSIONS

We designed, implemented and tested a VM-eLM for Gynecologic Cytopathology Education that improved cytological screening skills for both non-experienced and experienced cytologists, also increasing the diagnostic accuracy of preinvasive lesions by less experienced cytologists. The module was positively evaluated by participants, who perceived an improvement in their interpretive skills.

Inking cell blocks improves scanner detection for diagnosis in pathology

Cell blocks may be hard to be totally automatically detected by the scanner (ADS), generating incomplete whole slide images (WSIs), with areas that are not scanned, leading to possible false negative diagnosis. The aim of this study is to test if inking the cell blocks helps increasing ADS. Test 1: 15 cell blocks were sectioned, one half inked black (1HB) and the other inked green (1HG). Each of the halves was individually processed to generate a WSI stained by the H&E. 1HBs and 1HGs had similar scanning time (median 59 s vs. 65 s, p = .126) and file sizes (median 382 Mb vs. 381 Mb, p = .567). The black ink interfered less in the observation (2.2% vs. 44.4%; p < .001) than in the green one. Test 2: 15 cell blocks were sectioned, one half inked black (2HB) and the other left unstained/null (2HN). Each of the halves was individually processed to generate three WSIs-one HE, one periodic-acid Schiff (PAS), and one immunostained by cytokeratin AE1&AE3 (CKAE1AE3). HE and PAS WSIs from both 2HN and 2HB groups were all totally ADS and had similar scanning times and file sizes. Concerning immunostaining with CKAE1AE3: ADS (46.7% vs. 93.3%; p = .014), median time for scanning (57 s vs. 83 s; p < .001) and file size (178 Mb vs. 338 Mb; p < .001) were reduced significantly in the 2HN group in comparison with the 2HB. Although increasing scanning time and file size, inking the cell blocks helps increasing ADS after immunostaining, improving the safety and efficiency of the digital pathology workflow.

One nodule-one punction-one slide: Optimizing thyroid fine-needle aspiration for a digital workflow

OBJECTIVE

Interventional pathologists have expanded their expertise by acquiring proficiency in ultrasound-guided thyroid fine-needle aspiration biopsy (FNAB) and are now required to optimize punction procedures due to low resources and digital workflows. The aim of this study is to compare FNAB sample adequacy in two series with one versus two slides available for cytopathological analysis and its influence on diagnosis categorization, time taken to reach a final diagnosis, scanning time and size of the digital files produced.

METHODS

Patients were retrospectively selected based on the sampling of thyroid nodules using either two glass slides (two-slide group) or one slide only (one-slide group) and cytological diagnosis was performed using the second edition of the Bethesda system. For each group, the initial 15 cases were sorted to be scanned.

RESULTS

From a total of 713 procedures, 328 were sampled into two slides and 385 on one slide only. No significant differences were found regarding nodule size, location or EU-TIRADS classification between the two groups. The one-slide group did not exhibit a higher prevalence of non-diagnostic or atypia of undetermined significance (AUS) categories. As expected, the mean time taken to finalize diagnoses in cases where only one slide was prepared was 1.2 days faster. Scanning time and total file size were also significantly smaller in the one-slide group.

CONCLUSIONS

Adopting the 'one nodule-one puncture-one slide' strategy for thyroid FNAB optimization enhances procedural efficiency in digital workflows, leading to cost savings without compromising diagnostic accuracy.

Delphi expert consensus for whole slide imaging in thyroid cytopathology

OBJECTIVE

Despite an increase in thyroid fine needle aspiration (FNA) and advances in whole slide imaging (WSI) adoption, digital pathology is still considered inadequate for primary diagnosis of these cases. Herein, we aim to validate the utility of WSI in thyroid FNAs employing the Delphi method strategy.

METHODS

A panel of experts from seven reference cytology centres was recruited. The study consisted of two consecutive rounds: (1) an open-ended, free-response questionnaire generating a list of survey items; and (2) a consensus analysis of 80 selected shared WSIs from 80 cases by six investigators answering six morphological questions utilising a 1 to 5 Likert scale.

RESULTS

High consensus was achieved for all parameters, with an overall average score of 4.27. The broad majority of items (84%) were ranked either 4 or 5 by each physician. Two badly scanned cases were responsible for more than half of the low-ranked (≤2) values (57%). Good to excellent (≥3) diagnostic confidence was reached in more than 95.2% of cases. For most cases (78%) WSI assessment was not limited by technical issues linked to the image acquisition process.

CONCLUSION

This systematic Delphi study indicates broad consensus among participating physicians on the application of DP to thyroid cytopathology, supporting expert opinion that WSI is reliable and safe for primary diagnostic purposes.

Digital Examination of LYmph node CYtopathology Using the Sydney system (DELYCYUS): An international, multi-institutional study

BACKGROUND

After a series of standardized reporting systems in cytopathology, the Sydney system was recently introduced to address the need for reproducibility and standardization in lymph node cytopathology. Since then, the risk of malignancy for the categories of the Sydney system has been explored by several studies, but no studies have yet examined the interobserver reproducibility of the Sydney system.

METHODS

The authors assessed interobserver reproducibility of the Sydney system on 85 lymph node fine-needle aspiration cytology cases reviewed by 15 cytopathologists from 12 institutions in eight different countries, resulting in 1275 diagnoses. In total, 186 slides stained with Diff-Quik, Papanicolaou, and immunocytochemistry were scanned. A subset of the cases included clinical data and results from ultrasound examinations, flow cytometry immunophenotyping, and fluorescence in situ hybridization analysis. The study participants assessed the cases digitally using whole-slide images.

RESULTS

Overall, the authors observed an almost perfect agreement of cytopathologists with the ground truth (median weighted Cohen κ = 0.887; interquartile range, κ = 0.210) and moderate overall interobserver concordance (Fleiss κ = 0.476). There was substantial agreement for the inadequate and malignant categories (κ = 0.794 and κ = 0.729, respectively), moderate agreement for the benign category (κ = 0.490), and very slight agreement for the suspicious (κ = 0.104) and atypical (κ = 0.075) categories.

CONCLUSIONS

The Sydney system for reporting lymph node cytopathology shows adequate interobserver concordance. Digital microscopy is an adequate means to assess lymph node cytopathology specimens.

Rapid Remote Online Evaluation in Endoscopic Diagnostics: An Analysis of Biopsy-Proven Respiratory Cytopathology

BACKGROUND

This prospective study assesses the use of rapid remote online cytological evaluation for diagnosing endoscopical achieved biopsies. It focuses on its effectiveness in identifying benign and malignant conditions using digital image processing.

METHODS

The study was conducted between April 2021 and September 2022 and involved analyses of 314 Rapid Remote Online Cytological Evaluations in total (154 imprint cytologies, 143 fine needle aspirations and 17 brush cytologies) performed on 239 patients at the LungenClinic Grosshansdorf. During on-site evaluation via telecytology, the time requirement was recorded and the findings were compared with the cyto-/histological and final diagnoses.

RESULTS

By means of rapid remote online evaluation, findings of 86 cytological benign, 190 malignant and 38 unclear diagnoses were recorded (Ø assessment time, 100 s; range, 11-370 s). In 27 of the 37 specimens with unclear diagnoses, the final findings were malignant tumours and only 6 were benign changes. The diagnosis of another 4 of these 37 findings remained unclear. Excluding these 37 specimens, rapid remote online evaluation achieved a sensitivity of 90.5% with a specificity of 98.5% and a correct classification rate of 92.4% with regard to the final diagnosis of all cases. As expected, an increase in the sensitivity rate for the cytological detection of malignant tumours (76.1% vs. 92.5%) was found especially in fine-needle aspirations.

CONCLUSIONS

Rapid remote online analysis allows the fast quantitative and qualitative evaluation of clinically obtained cytological specimens. With a correct classification rate of more than 93%, sampling deficiencies can be corrected promptly and diagnostic and therapeutic approaches can be derived.

Integrating cytology into routine digital pathology workflow: a 5-year journey

Despite recent advances in digital imaging, the adoption of digital cytology is challenging due to technical limitations. This study describes our 5-year institutional experience with the implementation of digital cytology. The routine cytology workflow included conventional two-step screening by cytotechnologists, followed by sign out by pathologists. We introduced sign out of cytologic cases using a microscopic digital imaging platform operated by cytotechnologists, which allowed for remote review of slides by cytopathologists via video streaming. We also provided cytologic correlation to support the virtual slide-based sign out of histopathological specimens and for a weekly pathology-radiology conference. In addition, positive cytology cases were archived for integration into the laboratory information system and for prospective computational pathology studies. We also summarized lessons learned over the years and outlined our vision for future developments. This unique experience may serve as a role model for other institutions.

International survey of cytopathology training during the pandemic: Water under the bridge?

The purpose of this study was to assess the impact of the COVID-19 pandemic on cytopathology training at an international level. An anonymous online questionnaire was distributed by members of the international cytopathological community to medical practitioners in cytopathology. The survey explored perceived changes in cytology workload and workflow during the pandemic, and its effect on both non-cervical and cervical cytology reporting and teaching. A total of 82 responses were received from seven countries. Approximately half of the respondents reported a decrease in the number and range of cytology cases during the pandemic. Nearly half (47%) saw a reduction in the opportunity to co-report with consultants/attendings, and 72% of the respondents reported that their consultants/attendings were working remotely during the pandemic. Another 34% of the respondents were redeployed for 3 weeks to 1 year, with 96% stating that this period was only partially compensated for during their training, if at all. The pandemic negatively affected the opportunity to report cervical cytology, perform fine needle aspirations, and participate in multidisciplinary team meetings. Most respondents (69%) saw a decrease in the amount and quality (52%) of face-to-face departmental cytology teaching, whereas remote departmental teaching improved in amount (54%) and quality (49%). Almost half (49%) reported that cytology teaching in the regional, national, and international settings increased in both amount and quality. The pandemic catalysed many changes in cytopathology training, affecting the trainees' exposure to cases, the use of remote reporting, consultant/attending working practices, redeployment, and local as well as external teaching.

Digital diagnostic cytopathology: Has the pandemic brought us closer?

The COVID-19 pandemic has acted as a powerful change driver in the field of pathology and has had relevant consequences on the practice of cytopathology, in terms of changes in workload, rates of malignancy, and the performance of cytology. At the same time, regulatory authorities have relaxed their requirements for the deployment of digital pathology for remote diagnostic reporting. However, most of these improvements have concerned digital histopathology. Data from a literature search show that experiences in digital cytopathology during the pandemic have concerned mainly educational and academic activities. From a broader point of view, when searching for all published literature on digital pathology, only a minority of papers deal with cytopathology, but a noticeable increase in publications has been seen in the last 10 years, with an upward trend toward a maximum of papers in 2021. Indeed, the pandemic has led to greater awareness of the possibility of digital for cytopathology as well.

Validation of full-remote reporting for cervicovaginal cytology: the Caltagirone-Acireale distributed lab

INTRODUCTION

Cervical cancer is the fourth most common cancer in women, and its prevention is based on vaccination and screening. Screening consists of molecular human papillomavirus (HPV) testing and cytologic analysis of cervical smears, which require expensive equipment and the interaction of numerous professionals such as biologists, cytologists, laboratory technicians, and pathologists.

MATERIALS AND METHODS

We centralize the cervical samples from more than 51 clinics in 1 main laboratory, where automated HPV testing is performed. HPV-positive cases are collected and used to prepare a liquid-based cytology slide, which is stained and immediately scanned. The resulting whole-slide images (WSIs) are immediately available in a remote laboratory where they are examined by experienced cytologists using virtual microscopy. This setup was validated by making each of the 3 readers independently diagnose 506 specimens in random order, using both conventional light microscopy (CLM) and WSIs, with a minimum wash-out period of 3 weeks and with a final discussion for all cases.

RESULTS

Intraobserver agreement among CLM and WSI ranged from 0.71 to 0.79, and interobserver agreement for the 3 readers compared with the consensus diagnosis was similar for the 2 modes of assessment. Readers subjectively felt confident in their WSI diagnosis for inadequate and negative cases, but less so in other cases. The perceived difficulty was slightly higher in WSI readings.

CONCLUSIONS

Interobserver agreement in cervicovaginal cytology is moderate and does not vary if the slides are examined conventionally or digitally. Despite higher reported subjective difficulty and lower confidence in the WSI diagnosis, we did not observe a deterioration in diagnostic performance using WSI compared with CLM.

Validation of cytopathology specimens for digital pathology

INTRODUCTION

Digital cytopathology is being progressively implemented in centres worldwide, but impediments such as the three-dimensionality of specimens and the size of scanned images have prevented its use from becoming widespread. This study aimed to validate the use of digital whole slide image scanning of cytopathology samples for routine sign-out.

METHODS

Specimens were scanned using the Leica Aperio GT 450 System. The following sample types were used: liquid-based cytology, direct conventional smears from fine needle aspirates and cytospins. Cases were validated by the same pathologist who originally rendered the conventional diagnosis, with a washout of at least 3 months. Final digital diagnoses were compared to the original analogical diagnoses, and cases were considered concordant up to a one-degree difference between the original and digital diagnoses. Reasons for the unsuccessful scanning of slides were also noted. The technical procedures followed the College of American Pathologists' guidelines for digital pathology validation.

RESULTS

A total of 730 slides from 383 cases (337 female, 51 male; median age 42) were successfully scanned. These cases consisted of the following sample types: 81 (21.1%) conventional smears, 240 (62.7%) liquid-based cytology samples and 62 (16.2%) cytospins. There were only five discordant cases, with a 98.7% agreement between original and digital diagnoses using the difference rate of up to one degree. Seventy-seven slides (10.5%) had to be rescanned due to technical problems. The main reasons for unsuccessful scanning were paucicellular samples (44; 57.1%), the thickness of the smears (18; 23.4%) and issues with the coverslip (15; 19.5%).

CONCLUSION

Cytological specimens can be successfully scanned and used for digital pathology, with excellent agreement with the original diagnoses.

The slow-paced digital evolution of pathology: lights and shadows from a multifaceted board

Objective

The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. Barriers include concerns about initial costs, lack of confidence in using whole slide images for primary diagnosis, and lack of guidance on transition. To address these challenges and develop a programme to facilitate the introduction of digital pathology (DP) in Italian pathology departments, a panel discussion was set up to identify the key points to be considered.

Methods

On 21 July 2022, an initial conference call was held on Zoom to identify the main issues to be discussed during the face-to-face meeting. The final summit was divided into four different sessions: (I) the definition of DP, (II) practical applications of DP, (III) the use of AI in DP, (IV) DP and education.

Results

Essential requirements for the implementation of DP are a fully tracked and automated workflow, selection of the appropriate scanner based on the specific needs of each department, and a strong commitment combined with coordinated teamwork (pathologists, technicians, biologists, IT service and industries). This could reduce human error, leading to the application of AI tools for diagnosis, prognosis and prediction. Open challenges are the lack of specific regulations for virtual slide storage and the optimal storage solution for large volumes of slides.

Conclusion

Teamwork is key to DP transition, including close collaboration with industry. This will ease the transition and help bridge the gap that currently exists between many labs and full digitisation. The ultimate goal is to improve patient care.

The experience of introducing telepathology in Mongolia

Background

Anatomical pathology care services play an essential role in cancer diagnosis through histological analysis, effective treatment of patients, and determination of prognosis. Therefore, quality control is necessary for the diagnosis of pathology. Based on this need, telepathology technology is rapidly developing in the world. This study aimed to share the experience of implementing telepathology case consultation between Mongolian and Japanese expert pathologists.

Methods

The study included 173 cases that required telepathology consultation, which was complicated and doubtful in diagnosis, submitted by Mongolian pathologists between May 2019 and April 2022. The scanned digital slides were transmitted with the help of the LOOKREC cloud-based system, and the expert pathologists of Hiroshima University Hospital, Japan, browsed the images through the data on the internet and their advice and made a mutual diagnosis.

Results

During the study period, 173 cases were consulted. Out of 58.4% of all cases, consultation reports were released in 2022. The majority of the cases in 2020 had a mean standard deviation turn-around time of 4.2±6.2 days. The most cases were from the lung and mediastinum were 29.4%, followed by head and neck at 12.6%, the bone at 11.9%, lymph nodes at 8.4%, GIT at 7.7%, soft tissues at 6.3%, etc. Comparing the sample submission of biopsy and cytology was significantly higher in the under 10 years of an experienced group than over 10 years of an experienced group (p<.005). The diagnostic agreement between submitter Mongolian pathologists and expert Japanese pathologists was 82.7%, and disagreement was 17.3% of all cases, with a sensitivity of 67.3% and specificity of 85.5%.

Conclusions

Telepathology could save many lost opportunities and play an essential role in developing quality control and surgical pathology in Mongolia. This digital technology and the appropriate strategy and policy of the government could accelerate the overall pathology field development.

Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases

Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patient and public health management. Identification of many microbes still relies on manual microscopic examination, a time-consuming process requiring skilled staff. Thus, artificial intelligence (AI) has been exploited for identification of microorganisms. A systematic search was carried out using electronic databases looking for studies dealing with the application of AI to pathology microbiology specimens. Of 4596 retrieved articles, 110 were included. The main applications of AI regarded malaria (54 studies), bacteria (28), nematodes (14), and other protozoa (11). Most publications examined cytological material (95, 86%), mainly analyzing images acquired through microscope cameras (65, 59%) or coupled with smartphones (16, 15%). Various deep-learning strategies were used for the analysis of digital images, achieving highly satisfactory results. The published evidence suggests that AI can be reliably utilized for assisting pathologists in the detection of microorganisms. Further technologic improvement and availability of datasets for training AI-based algorithms would help expand this field and widen its adoption, especially for developing countries.

Application of Digital Imaging and Artificial Intelligence to Pathology of the Placenta

Digital imaging, including the use of artificial intelligence, has been increasingly applied to investigate the placenta and its related pathology. However, there has been no comprehensive review of this body of work to date. The aim of this study was to therefore review the literature regarding digital pathology of the placenta. A systematic literature search was conducted in several electronic databases. Studies involving the application of digital imaging and artificial intelligence techniques to human placental samples were retrieved and analyzed. Relevant articles were categorized by digital image technique and their relevance to studying normal and diseased placenta. Of 2008 retrieved articles, 279 were included. Digital imaging research related to the placenta was often coupled with immunohistochemistry, confocal microscopy, 3D reconstruction, and/or deep learning algorithms. By significantly increasing pathologists' ability to recognize potentially prognostic relevant features and by lessening inter-observer variability, published data overall indicate that the application of digital pathology to placental and perinatal diseases, along with clinical and radiology correlation, has great potential to improve fetal and maternal health care including the selection of targeted therapy in high-risk pregnancy.

Digital pathology world tour

Objective

Digital pathology (DP) is currently in the spotlight and is rapidly gaining ground, even though the history of this field spans decades. Despite great technological progress, the adoption of DP for routine clinical diagnostic use remains limited.

Methods

A systematic search was conducted in the electronic databases Pubmed-MEDLINE and Embase. Inclusion criteria were all published studies that encompassed any application of DP.

Results

Of 4888 articles retrieved, 4041 were included. Relevant articles were categorized as "diagnostic" (147/4041, 4%) where DP was utilized for routine diagnostic workflow and "non-diagnostic" (3894/4041, 96%) for all other applications. The "non-diagnostic" articles were further categorized according to DP application including "artificial intelligence" (33%), "education" (5%), "narrative" (17%) for reviews and editorials, and "technical" (45%) for pure research publications.

Conclusion

This manuscript provided temporal and geographical insight into the global adoption of DP by analyzing the published scientific literature.

Relevance of the College of American Pathologists guideline for validating whole slide imaging for diagnostic purposes to cytopathology

Whole slide imaging (WSI) allows pathologists to view virtual versions of slides on computer monitors. With increasing adoption of digital pathology, laboratories have begun to validate their WSI systems for diagnostic purposes according to reference guidelines. Among these the College of American Pathologists (CAP) guideline includes three strong recommendations (SRs) and nine good practice statements (GPSs). To date, the application of WSI to cytopathology has been beyond the scope of the CAP guideline due to limited evidence. Herein we systematically reviewed the published literature on WSI validation studies in cytology. A systematic search was carried out in PubMed-MEDLINE and Embase databases up to November 2021 to identify all publications regarding validation of WSI in cytology. Each article was reviewed to determine if SRs and/or GPSs recommended by the CAP guideline were adequately satisfied. Of 3963 retrieved articles, 25 were included. Only 4/25 studies (16%) satisfied all three SRs, with only one publication (1/25, 4%) fulfilling all three SRs and nine GPSs. Lack of a suitable validation dataset was the main missing SR (16/25, 64%) and less than a third of the studies reported intra-observer variability data (7/25, 28%). Whilst the CAP guideline for WSI validation in clinical practice helped the widespread adoption of digital pathology, more evidence is required to routinely employ WSI for diagnostic purposes in cytopathology practice. More dedicated validation studies satisfying all SRs and/or GPSs recommended by the CAP are needed to help expedite the use of WSI for primary diagnosis in cytopathology.

Automated staining analysis in digital cytopathology and applications

The progress of digital pathology in recent years has been an opportunity for the development of automated image analysis algorithms for quantitative measurements and computer aided diagnosis. With those new methods comes the need for high staining quality and reproducibility, as image analysis tools are typically more sensible to slight stain variations than trained pathologists. This article presents a method for the automated analysis of cytology slides stains specifically adapted to the challenges encountered in digital cytopathology. In particular, the variety of cell types in cytology slides, the 3D distribution of the cellular material, the presence of superposed cells and the need for independent analysis of sub-cellular compartments are addressed. The proposed method is applied to the quantification of staining variations for quality control, resulting from changes in the staining protocol such as reagent immersion time or a reagent change. Another demonstrated application is the selection of staining protocol parameters that maximize the visible details in nucleus. Finally the analysis pipeline is also used to compare different stain normalization algorithms on digital cytology slides. Code available at: https://gitlab.com/vitadx/articles/automated_staining_analysis.

A self-supervised contrastive learning approach for whole slide image representation in digital pathology

Image analysis in digital pathology has proven to be one of the most challenging fields in medical imaging for AI-driven classification and search tasks. Due to their gigapixel dimensions, whole slide images (WSIs) are difficult to represent for computational pathology. Self-supervised learning (SSL) has recently demonstrated excellent performance in learning effective representations on pretext objectives, which may improve the generalizations of downstream tasks. Previous self-supervised representation methods rely on patch selection and classification such that the effect of SSL on end-to-end WSI representation is not investigated. In contrast to existing augmentation-based SSL methods, this paper proposes a novel self-supervised learning scheme based on the available primary site information. We also design a fully supervised contrastive learning setup to increase the robustness of the representations for WSI classification and search for both pretext and downstream tasks. We trained and evaluated the model on more than 6000 WSIs from The Cancer Genome Atlas (TCGA) repository provided by the National Cancer Institute. The proposed architecture achieved excellent results on most primary sites and cancer subtypes. We also achieved the best result on validation on a lung cancer classification task.

Technical and Diagnostic Issues in Whole Slide Imaging Published Validation Studies

Objective

Digital pathology with whole-slide imaging (WSI) has many potential clinical and non-clinical applications. In the past two decades, despite significant advances in WSI technology adoption remains slow for primary diagnosis. The aim of this study was to identify common pitfalls of WSI reported in validation studies and offer measures to overcome these challenges.

Methods

A systematic search was conducted in the electronic databases Pubmed-MEDLINE and Embase. Inclusion criteria were all validation studies designed to evaluate the feasibility of WSI for diagnostic clinical use in pathology. Technical and diagnostic problems encountered with WSI in these studies were recorded.

Results

A total of 45 studies were identified in which technical issues were reported in 15 (33%), diagnostic issues in 8 (18%), and 22 (49%) reported both. Key technical problems encompassed slide scan failure, prolonged time for pathologists to review cases, and a need for higher image resolution. Diagnostic challenges encountered were concerned with grading dysplasia, reliable assessment of mitoses, identification of microorganisms, and clearly defining the invasive front of tumors.

Conclusion

Despite technical advances with WSI technology, some critical concerns remain that need to be addressed to ensure trustworthy clinical diagnostic use. More focus on the quality of the pre-scanning phase and training of pathologists could help reduce the negative impact of WSI technical difficulties. WSI also seems to exacerbate specific diagnostic tasks that are already challenging among pathologists even when examining glass slides with conventional light microscopy.

DigiPatICS: Digital Pathology Transformation of the Catalan Health Institute Network of 8 Hospitals—Planification, Implementation, and Preliminary Results

Complete digital pathology transformation for primary histopathological diagnosis is a challenging yet rewarding endeavor. Its advantages are clear with more efficient workflows, but there are many technical and functional difficulties to be faced. The Catalan Health Institute (ICS) has started its DigiPatICS project, aiming to deploy digital pathology in an integrative, holistic, and comprehensive way within a network of 8 hospitals, over 168 pathologists, and over 1 million slides each year. We describe the bidding process and the careful planning that was required, followed by swift implementation in stages. The purpose of the DigiPatICS project is to increase patient safety and quality of care, improving diagnosis and the efficiency of processes in the pathological anatomy departments of the ICS through process improvement, digital pathology, and artificial intelligence tools.

Digital validation of breast biomarkers (ER, PR, AR, and HER2) in cytology specimens using three different scanners

Progression in digital pathology has yielded new opportunities for a remote work environment. We evaluated the utility of digital review of breast cancer immunohistochemical prognostic markers (IHC) using whole slide images (WSI) from formalin fixed paraffin embedded (FFPE) cytology cell block specimens (CB) using three different scanners.CB from 20 patients with breast cancer diagnosis and available IHC were included. Glass slides including 20 Hematoxylin and eosin (H&E), 20 Estrogen Receptor (ER), 20 Progesterone Receptor (PR), 16 Androgen Receptor (AR), and 20 Human Epidermal Growth Factor Receptor 2 (HER2) were scanned on 3 different scanners. Four breast pathologists reviewed the WSI and recorded their semi-quantitative scoring for each marker. Kappa concordance was defined as complete agreement between glass/digital pairs. Discordances between microscopic and digital reads were classified as a major when a clinically relevant change was seen. Minor discordances were defined as differences in scoring percentages/staining pattern that would not have resulted in a clinical implication. Scanner precision was tabulated according to the success rate of each scan on all three scanners.In total, we had 228 paired glass/digital IHC reads on all 3 scanners. There was strong concordance kappa ≥0.85 for all pathologists when comparing paired microscopic/digital reads. Strong concordance (kappa ≥0.86) was also seen when comparing reads between scanners.Twenty-three percent of the WSI required rescanning due to barcode detection failures, 14% due to tissue detection failures, and 2% due to focus issues. Scanner 1 had the best average precision of 92%. HER2 IHC had the lowest intra-scanner precision (64%) among all stains.This study is the first to address the utility of WSI in breast cancer IHC in CB and to validate its reporting using 3 different scanners. Digital images are reliable for breast IHC assessment in CB and offer similar reproducibility to microscope reads.

Frozen section telepathology service: Efficiency and benefits of an e-health policy in South Tyrol

Objective/Background

Telepathology has been widely adopted to allow intraoperative pathology examinations to be performed remotely and for obtaining second opinion teleconsultation. In the Italian northern region of South Tyrol, the widespread geographical distances and consequent cost for the health system of having a travelling pathologist cover intraoperative consultations in peripheral hospitals was a key driver for the implementation of a telepathology system.

Methods

In 2010, four Menarini D-Sight whole slide scanners to digitize entire pathology slides were placed in the peripheral hospitals of Merano, Bressanone, Brunico, and in the hub hospital of Bolzano. Digital workstations were also installed to allow pathologists to remotely perform intraoperative consultations with digital slides. This study reviews the outcome after 12 years of telepathology for this intended clinical use.

Results

After an initial validation phase with 100 cases which yielded a sensitivity of 65% (CI 43–84%) and specificity of 100% (CI 95–100%), there were 2058 intraoperative consultations handled by telepathology. The cases evaluated were mainly breast sentinel lymph nodes, followed by urological, gynecological and general surgical pathology frozen section specimens. There were no false-positive cases and 165 (8%) false-negative cases, yielding an overall sensitivity and specificity of 65% (CI 61–69%) and 100% (CI 99–100%), respectively.

Conclusion

Telepathology is reliable for remote intraoperative diagnosis and, despite technical issues and initial acquaintance issues, proved beneficial for patient care in satellite hospitals, improved standardization, promoted innovation, and resulted in cost savings for the health system.

On the acceptance of “fake” histopathology: A study on frozen sections optimized with deep learning

Background:

The fast acquisition process of frozen sections allows surgeons to wait for histological findings during the interventions to base intrasurgical decisions on the outcome of the histology. Compared with paraffin sections, however, the quality of frozen sections is often strongly reduced, leading to a lower diagnostic accuracy. Deep neural networks are capable of modifying specific characteristics of digital histological images. Particularly, generative adversarial networks proved to be effective tools to learn about translation between two modalities, based on two unconnected data sets only. The positive effects of such deep learning-based image optimization on computer-aided diagnosis have already been shown. However, since fully automated diagnosis is controversial, the application of enhanced images for visual clinical assessment is currently probably of even higher relevance.

Methods:

Three different deep learning-based generative adversarial networks were investigated. The methods were used to translate frozen sections into virtual paraffin sections. Overall, 40 frozen sections were processed. For training, 40 further paraffin sections were available. We investigated how pathologists assess the quality of the different image translation approaches and whether experts are able to distinguish between virtual and real digital pathology.

Results:

Pathologists’ detection accuracy of virtual paraffin sections (from pairs consisting of a frozen and a paraffin section) was between 0.62 and 0.97. Overall, in 59% of images, the virtual section was assessed as more appropriate for a diagnosis. In 53% of images, the deep learning approach was preferred to conventional stain normalization (SN).

Conclusion:

Overall, expert assessment indicated slightly improved visual properties of converted images and a high similarity to real paraffin sections. The observed high variability showed clear differences in personal preferences.

Advantages of Using a Web-based Digital Platform for Kidney Preimplantation Biopsies

BACKGROUND

In the setting of kidney transplantation, histopathology of kidney biopsies is a key element in the organ assessment and allocation. Despite the broad diffusion of the Remuzzi-Karpinski score on preimplantation kidney biopsies, scientific evidence of its correlation to the transplantation outcome is controversial. The main issues affecting the prognostic value of histopathology are the referral to general on-call pathologists and the semiquantitative feature of the score, which can raise issues of interpretation. Digital pathology has shown very reliable and effective in the oncological diagnosis and treatment; however, the spread of such technologies is lagging behind in the field of transplantation. The aim of our study was to create a digital online platform where whole-slide images (WSI) of preimplantation kidney biopsies could be uploaded and stored.

METHODS

We included 210 kidney biopsies collected between January 2015 and December 2019 from the joint collaboration of the transplantation centers of Padua and Verona. The selected slides, stained with hematoxylin and eosin, were digitized and uploaded on a shared web platform. For each case, the on-call pathologists' Remuzzi grades were obtained from the original report, together with the clinical data and the posttransplantation follow-up.

RESULTS

The storage of WSI of preimplantation kidney biopsies would have several clinical, scientific, and educational advantages. The clinical utility relies on the possibility to consult online expert pathologists and real-time quality checks of diagnosis. From the perspective of follow-up, the archived digitized biopsies can offer a useful comparison to posttransplantation biopsies. In addition, the digital online platform is a precious tool for multidisciplinary meetings aimed both at the clinical discussion and at the design of research projects. Furthermore, this archive of readily available WSI is an important educational resource for the training of professionals.

CONCLUSIONS

Finally, the web platform lays the foundation for the introduction of artificial intelligence in the field of transplantation that would help create new diagnostic algorithms and tools with the final aim of increasing the precision of organ assessment and its predictive value for transplant outcome.

Impact of mobile devices on cancer diagnosis in cytology

BACKGROUND

Digital pathology has widened pathologists' opportunities to examine both surgical and cytological samples. Recently, portable mobile devices like tablets and smartphones have been tested for application with digital technologies including static, dynamic, and more recently whole slide imaging. This study aimed to review the published literature on the impact of mobile devices on cancer diagnoses in cytology. This analysis focused on their diagnostic potential, technical details, critical issues and pitfalls, and economical aspects.

METHODS

A systematic search was carried out in the electronic databases Embase and PubMed. Studies dealing with the application of mobile devices for diagnosing cancer on cytological specimens were included. The quality of studies was assessed with the QUADAS-2 tool. The main themes addressed were the comparison of manual examination with light microscopy and the use of mobile tools for primary diagnosis. The technical features of different models of smartphones and tablets, software, and adapters were also studied in terms of feasibility and costs-analysis.

RESULTS

Of 2458 retrieved articles, 18 were included. Concordance with light microscopy was good and diagnostic performance comparable with an expert pathologist's diagnosis. The mobile devices studied differed, sometimes significantly, in terms of speed and cost. The utility was improved by employing specifically designed adapters. Image acquisition and transmission represent the main critical points in almost all studies.

CONCLUSION

The use of mobile devices demonstrated promising results regarding the digital evaluation of cytological samples. Widespread adoption even in underserved areas is anticipated following validation studies, technology improvements, and reduction in the costs.

Development and Validation of an Ultrasonic Diagnostic Model for Differentiating Follicular Thyroid Carcinoma from Follicular Adenoma

Background

High-resolution ultrasound is the first choice for the diagnosis of thyroid nodules, but it is still difficult to distinguish between follicular thyroid carcinoma (FTC) and follicular adenoma (FA). Our research aimed to develop and validate an ultrasonic diagnostic model for differentiating FTC from FA.

Methods

This study retrospectively analyzed 196 patients who were diagnosed as FTC (n=83) and FA (n=113). LASSO regression analysis was used to screen clinical and ultrasonic features. Multivariate logistic regression analysis was used to establish the ultrasonic diagnostic model of FTC. Nomogram was used for the visualization of diagnostic models. C-index, ROC, and calibration curves analysis were used to evaluate the accuracy of the diagnostic model. Decision curve analysis (DCA) was used to evaluate the net benefits of the ultrasonic diagnostic model for FTC diagnosis under different threshold probabilities. The bootstrap method was used to verify the ultrasonic diagnostic model.

Results

After Lasso regression analysis, 10 clinical and ultrasonic features were used to construct the ultrasonic diagnostic model of FTC. The C-index and AUC of the model were 0.868 and 0.860, respectively. DCA showed that the ultrasonic model had good clinical application value. The C-index in the validation group was 0.818, which was close to the C-index in the model.

Conclusion

Ultrasonic diagnostic model constructed with 10 clinical and ultrasonic features can better distinguish FTC from FA.

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center

OBJECTIVE

Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes.

MATERIALS AND METHODS

We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent.

RESULTS

The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases.

CONCLUSIONS

We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.

Advances in Imaging Modalities, Artificial Intelligence, and Single Cell Biomarker Analysis, and Their Applications in Cytopathology

Several advances in recent decades in digital imaging, artificial intelligence, and multiplex modalities have improved our ability to automatically analyze and interpret imaging data. Imaging technologies such as optical coherence tomography, optical projection tomography, and quantitative phase microscopy allow analysis of tissues and cells in 3-dimensions and with subcellular granularity. Improvements in computer vision and machine learning have made algorithms more successful in automatically identifying important features to diagnose disease. Many new automated multiplex modalities such as antibody barcoding with cleavable DNA (ABCD), single cell analysis for tumor phenotyping (SCANT), fast analytical screening technique fine needle aspiration (FAST-FNA), and portable fluorescence-based image cytometry analyzer (CytoPAN) are under investigation. These have shown great promise in their ability to automatically analyze several biomarkers concurrently with high sensitivity, even in paucicellular samples, lending themselves well as tools in FNA. Not yet widely adopted for clinical use, many have successfully been applied to human samples. Once clinically validated, some of these technologies are poised to change the routine practice of cytopathology.

Image Analysis Using Machine Learning for Automated Detection of Hemoglobin H Inclusions in Blood Smears - A Method for Morphologic Detection of Rare Cells

Background

Morphologic rare cell detection is a laborious, operator-dependent process which has the potential to be improved by the use of image analysis using artificial intelligence. Detection of rare hemoglobin H (HbH) inclusions in red cells in the peripheral blood is a common screening method for alpha-thalassemia. This study aims to develop a convolutional neural network-based algorithm for the detection of HbH inclusions.

Methods

Digital images of HbH-positive and HbH-negative blood smears were used to train and test the software. The software performance was tested on images obtained at various magnifications and on different scanning platforms. Another model was developed for total red cell counting and was used to confirm HbH cell frequency in alpha-thalassemia trait. The threshold minimum red cells to image for analysis was determined by Poisson modeling and validated on image sets.

Results

The sensitivity and specificity of the software for HbH+ cells on images obtained at ×100, ×60, and ×40 objectives were close to 91% and 99%, respectively. When an AI-aided diagnostic model was tested on a pilot of 40 whole slide images (WSIs), good inter-rater reliability and high sensitivity and specificity of slide-level classification were obtained. Using the lowest frequency of HbH+ cells (1 in 100,000) observed in our study, we estimated that a minimum of 2.4 × 10⁶ red cells would need to be analyzed to reduce misclassification at the slide level. The minimum required smear size was validated on 78 image sets which confirmed its validity.

Conclusions

WSI image analysis can be utilized effectively for morphologic rare cell detection. The software can be further developed on WISs and evaluated in future clinical validation studies comparing AI-aided diagnosis with the routine diagnostic method.

Programmed cell death ligand 1 pathologist training in the time of COVID-19: Our experience using a digital solution

The COVID-19 pandemic presented numerous challenges to the continuity of programmed cell death ligand 1 (PD-L1) assay training events conducted by our organization. Under typical conditions, these training events are face-to-face affairs, where participants are trained to assay algorithms on glass slides during multi-headed scope sessions. Social distancing measures undertaken to slow pandemic spread necessitated the adaptation of our training methods to facilitate assay training and subsequent continuation of clinical trials. The present report details the creation and use of the Roche pathology training portal (PTP) that allowed for remote training to diagnostic assay algorithms. The PTP is a web-based system comprised of a learning management system (LMS) coupled to an image management system (IMS). Whole slide images (WSIs) were produced using a DP200 instrument (Roche, Pleasanton, CA) and these scan files were then uploaded to an IMS. Courses were created on the LMS using annotated WSIs that were shared with enrolled pathologists worldwide during assay training events. These courses culminated in assay certification examinations, where pathologists evaluated test-case WSIs and evaluated these cases within the LMS. Trainee submissions were analyzed for pass/fail status by comparing user data entries with consensus scores on these test-case WSIs. To date, 47 pathologist trainings have occurred and of these, 44 have successfully passed the associated assay certification exam on the first attempt (93% 1^st-try pass rate). The PTP allowed roche to continue training sites during the COVID-19 pandemic, and these early results demonstrate the capability of this digital solution regarding PD-L1 diagnostic assay training events.

Utilization of cytology smears improves success rates of RNA-based next-generation sequencing gene fusion assays for clinically relevant predictive biomarkers

BACKGROUND

The use of RNA-based next-generation sequencing (NGS) assays to detect gene fusions for targeted therapy has rapidly become an essential component of comprehensive molecular profiling. For cytology specimens, the cell block (CB) is most commonly used for fusion testing; however, insufficient cellularity and/or suboptimal RNA quality are often limiting factors. In the current study, the authors evaluated the factors affecting RNA fusion testing in cytology and the added value of smears in cases with a suboptimal or inadequate CB.

METHODS

A 12-month retrospective review was performed to identify cytology cases that were evaluated by a targeted RNA-based NGS assay. Samples were sequenced by targeted amplicon-based NGS for 51 clinically relevant genes on a proprietary platform. Preanalytic factors and NGS quality parameters were correlated with the results of RNA fusion testing.

RESULTS

The overall success rate of RNA fusion testing was 92%. Of the 146 cases successfully sequenced, 14% had a clinically relevant fusion detected. NGS testing success positively correlated with RNA yield (P = .03) but was independent of the tumor fraction, the tumor size, or the number of slides used for extraction. CB preparations were adequate for testing in 45% cases, but the inclusion of direct smears increased the adequacy rate to 92%. There was no significant difference in testing success rates between smears and CB preparations.

CONCLUSIONS

The success of RNA-based NGS fusion testing depends on the quality and quantity of RNA extracted. The use of direct smears significantly improves the adequacy of cytologic samples for RNA fusion testing for predictive biomarkers.