Translating AI to digital pathology workflow: Dealing with scarce data and high variation by minimising complexities in data and models

The recent conversion to digital pathology using Whole Slide Images (WSIs) from conventional pathology opened the doors for Artificial Intelligence (AI) in pathology workflow. The recent interests in machine learning and deep learning have gained a high interest in medical image processing. However, WSIs differ from generic medical images. WSIs are complex images which can reveal various information to support different diagnosis varying from cancer to unknown underlying conditions which were not discovered in other medical investigations. These investigations require expert knowledge spending a long time for investigations, applying different stains to the WSIs, and comparing the WSIs. Differences in WSI differentiate general machine learning methods that are applied for medical image processing. Co-analysing multistained WSIs, high variation of the WSIs from different sites, and lack of labelled data are the main key interest areas that directly influence in developing machine learning models that support pathologists in their investigations. However, most of the state-ofthe- art machine learning approaches cannot be applied in the general clinical workflow without using high compute power, expert knowledge, and time. Therefore, this thesis explores avenues to translate the highly computational and time intensive model to a clinical workflow. Co-analysing multi-stained WSIs require registering differently stained WSI together. In order to get a high precision in the registration exploring nonrigid and rigid transformation is required. The non-rigid transformation requires complex deep learning approaches. Using super-convergence on a small Convolutional Neural Network model it is possible to achieve high precision compared to larger auto-encoders and other state-of-the-art models. High variation of the WSIs from different sites heavily effect machine learning models in their predictions. The thesis presents an approach of using a pre-trained model by using only a small number of samples from the new site. Therefore, re-training larger deep learning models are not required which saves expert time for re-labelling and computational power. Finally, lack of labelled data is one of the main issues in training any supervised machine learning or deep learning model. Using a Generative Adversarial Networks (GAN) is an approach which can be easily implemented to avoid this issue. However, GANs are time and computationally expensive. These are not applicable in a general clinical workflow. Therefore, this thesis presents an approach using a simpler GANthat can generate accurate sample labelled data. The synthetic data are used to train classifier and the thesis demonstrates that the predictive model can generate higher accuracy in the test environment. This thesis demonstrates that machine learning and deep learning models can be applied to a clinical workflow, without exploiting expert time and high computing power

Future perspectives of digital pathology

Technological advances have enabled innovative solutions to be achieved in pathology based on digital imaging, now superseding those of conventional microscopy. Digital pathology has been defined as ‘virtual microscopy’ and depends on computer-generated digital imaging of microscope slides (WSI — whole slide imaging) which are in turn created, reviewed, managed, shared, analysed and interpreted. Such WSI systems and digital consulting platforms are now used for teaching, scientific research, telepathology / teleconsultation and diagnostics. They also permit easy and interactive sharing of WSI that can be integrated into other medical information systems. The software for automated image analysis and computer aided diagnosis can thereby make highly accurate diagnoses and help standardise study findings. Despite the technique’s many advantages, its noted drawbacks include high equipment and software costs, image quality issues of standardisation and most importantly, that pathologists are reluctant to use it routinely for making diagnoses

Breast carcinoma detection in ex vivo fresh human breast surgical specimens using a fast slide-free confocal microscopy scanner: HIBISCUSS project

Background: New generation ultra-fast fluorescence confocal microscopy allows the ex vivo intraoperative analysis of fresh tissue. The High resolution Imaging for Breast carcInoma detection in ex vivo Specimens after breast Conserving sUrgery by hiStolog Scanner (HIBISCUSS) project aimed to develop an online learning program to recognize the main breast tissue features on ultra-fast fluorescence confocal microscopy images and to evaluate the performance of surgeons and pathologists in diagnosing cancerous and non-cancerous breast tissue in ultra-fast fluorescence confocal microscopy images. Methods: Patients who underwent conservative surgery or mastectomy for breast carcinoma (invasive or in situ lesions) were included. The fresh specimens were stained with a fluorescent dye and imaged using a large field-of-view (20 cm2) ultra-fast fluorescence confocal microscope. Results: One hundred and eighty-one patients were included. The images from 55 patients were annotated to generate learning sheets and images from 126 patients were blindly interpreted by seven surgeons and two pathologists. The time for tissue processing and ultra-fast fluorescence confocal microscopy imaging was between 8 and 10 min. The training program was composed of 110 images divided into nine learning sessions. The final database for blind performance assessment comprised 300 images. The mean duration for one training session and one performance round was 17 and 27 min respectively. The performance of pathologists was almost perfect with 99.6 per cent (standard deviation (s.d.) 5.4 per cent) accuracy. Surgeons' accuracy significantly increased (P = 0.001) from 83 per cent (s.d. 8.4 per cent) in round 1 to 98 per cent (s.d. 4.1 per cent) in round 7 as well as the sensitivity (P = 0.004). Specificity increased without significance from 84 per cent (s.d. 16.7 per cent) in round 1 to 87 per cent (s.d. 16.4 per cent) in round 7 (P = 0.060). Conclusion: Pathologists and surgeons showed a short learning curve in differentiating breast cancer from non-cancerous tissue in ultra-fast fluorescence confocal microscopy images. Performance assessment for both specialties supports ultra-fast fluorescence confocal microscopy evaluation for intraoperative management. Registration number: NCT04976556 (http://www.clinicaltrials.gov)

Investigating the effectiveness and efficiency of forensic pathology practice in Western Cape, South Africa

Introduction: In South Africa (SA), the forensic sector faces significant challenges including how to meet increasing public expectations for high quality, reliable and valid scientific and medico legal results, whilst dealing with increasing caseloads and restricted resources in a developing country. Internationally, lean six-sigma and/or business-based frameworks have been developed to define, measure and analyse the efficiency, effectiveness and output of forensic laboratories, so as to assess performance to meet such challenges. Aim: This pilot project aimed to investigate the effectiveness and efficiency of forensic pathology practice at Salt River Mortuary (SRM) by applying lean six sigma principles (define, measure, analyse and improve) and FORESIGHT metric analyses to retrospective case and staffing data, as well as prospective observational analyses. Methods: A retrospective analysis of cases admitted to Salt River Mortuary in 2015 was conducted to define and measure a snapshot of forensic pathology practice in Cape Town. In addition, observations of autopsy processes were conducted to identify bottlenecks in the system and provide suggestions for improvement. Results: An analysis of post-mortem report turn-around for 3567 cases admitted to SRM in 2015 showed that approximately 10% of cases were closed (cause of death was determined) on the day of the post-mortem, 65% within 14 days and 80% closed within a 30 day period. Certain requested ancillary investigations delayed the finalisation of cause of death; for example, only 8.33% of carbon monoxide testing and 30.31% of histological examinations were completed within the year. A process map outlining autopsy practices at SRM was generated through observational data, which also identified key bottlenecks in the process (e.g.: equipment issues). Preliminary financial data suggested that it cost on average R16 155.03 per case. Staff data demonstrated a lack of pathologists compared to other staff categories and high case load requirements. Discussion: This pilot study investigates the utilization of metrics and strategic frameworks to assess forensic pathology processes in Cape Town. This study offers a cross-sectional insight into financial performance, efficiency and effectiveness of post-mortem investigations at SRM, highlighting bottlenecks and inefficiencies, and providing suggestions for improvement. The findings will assist in forming a basis for future work into the development of a framework for monitoring performance and progress, and developing benchmark standards for the death investigation system in South Afric

Hydrophilic intraocular lens opacification after posterior lamellar keratoplasty - a material analysis with special reference to optical quality assessment

Background: Laboratory analysis and optical quality assessment of explanted hydrophilic intraocular lenses (IOLs) with clinically significant opacification after posterior lamellar keratoplasty (DMEK and DSAEK). Methods: Thirteen opacified IOLs after posterior lamellar keratoplasty, 8 after descemet stripping automated endothelial keratoplasty (DSAEK), 3 after descemet membrane endothelial keratoplasty (DMEK) and 2 after both DSAEK and DMEK were analysed in our laboratory. Analyses included optical bench assessment for optical quality, light microscopy, scanning electron microscopy (SEM) and energy dispersive X-Ray spectroscopy (EDS). Results: In all IOLs the opacification was caused by a thin layer of calciumphosphate that had accumulated underneath the anterior optical surface of the IOLs in the area spared by the pupil/anterior capsulorhexis. The calcifications lead to a significant deterioration of the modulation transfer function across all spatial frequencies of the affected IOLs. Conclusions: The instillation of exogenous material such as air or gas into the anterior chamber increases the risk for opacification of hydrophilic IOLs irrespective of the manufacturer or the exact composition of the hydrophilic lens material. It is recommended to avoid the use of hydrophilic acrylic IOLs in patients with endothelial dystrophy that will likely require procedures involving the intracameral instillation of air or gas, such as DMEK or DS(A)EK

Process control and data handling in clinical chemistry by a laboratory computer

The thesis describes the development and assessment of a clinical chemistry computer system based on the Elliott 903C computer obtained for the on-line monitoring of automated equipment and the subsequent processing of the data derived. The special hardware required for interfacing the automated equipment with the computer was designed and constructed by Elliott Medical Automation Limited. All the software required for the operation of the system was written by the manufacturer's programming staff and my part was to be closely involved with general systems analysis. A detailed account is given of the evaluation of all the parameters required for the on-line monitoring of AutoAnalyzers and the provision of information required for calculation routines, checking quality control results, defining ranges for the automatic flagging of abnormal results, etc. The development work, including the testing, proving and where necessary, the modification of programs, was carried out in the Royal Infirmary, Edinburgh, with the assistance of the technical staff of the laboratory. In the initial stages of development the computer system was run in parallel with the existing laboratory equipment to enable a full assessment of the system to be carried out. This included assessing the performance of process control functions and the chemical acceptability of the system. At a later stage an assessment was made of the routine operation of the computer system when interest was focused on the time taken to perform individual tasks and the reliability of the hardware components. With the exception of one aspect of peak detection, the data acquisition programs were found to operate in a satisfactory manner, and the accuracy and precision of the computer system was at least as good as that of the routine laboratory methods; these latter involved manual reading and interpretation of recorder charts. The individual data processing programs were validated but when the programs were integrated to form a total software system, considerable delays in processing were encountered. Despite several attempts to reduce the time taken to perform processing routines, it was found impracticable to carry out the data handling activities of the laboratory within an acceptable time scale using the existing hardware configuration. The computer system is currently in use on a seven-day week basis for monitoring analytical equipment and performing the following functions (1) Acquisition of raw data from as many as 19 different determinations on up to 12 AutoAnalyzer channels at one time. (2) Peak detection and validation. (3) Calculation of results after correction for instrumental drift. (4) Output of results identified by cup number. (5) Calculation of mean and standard deviation of patient specimens. The present mode of operation removes the need for manual reading of AutoAnalyzer charts and hence reading errors, but it involves the transcription of results from the computer print-out to manually prepared work sheets, and the further transcription of results from work sheets to patient reports. The benefits derived from the Elliott 903 computer in its present form of operation can be summarised as follows: (1) It has been possible to increase the laboratory throughput without a substantial increase in staff in spite of an increase in the numbers of technical staff attending classes of further education during working hours. This has resulted in an increase in productivity and a decrease in the average cost per determination. (2) There is a decrease in the number of human errors by the elimination of reading of recorder charts. (3) Quality control statistics are available while they are still relevant to the current situation. The extension or modification of the hardware configuration and the additional software required to meet the needs of this laboratory have been investigated. Consideration has been given to the possibility of completely replacing the present computer system and to the feasibility of linking the laboratory system to a remotely situated data processing computer system

Informatic system for a global tissue–fluid biorepository with a graph theory–oriented graphical user interface

The Richard Floor Biorepository supports collaborative studies of extracellular vesicles (EVs) found in human fluids and tissue specimens. The current emphasis is on biomarkers for central nervous system neoplasms but its structure may serve as a template for collaborative EV translational studies in other fields. The informatic system provides specimen inventory tracking with bar codes assigned to specimens and containers and projects, is hosted on globalized cloud computing resources, and embeds a suite of shared documents, calendars, and video-conferencing features. Clinical data are recorded in relation to molecular EV attributes and may be tagged with terms drawn from a network of externally maintained ontologies thus offering expansion of the system as the field matures. We fashioned the graphical user interface (GUI) around a web-based data visualization package. This system is now in an early stage of deployment, mainly focused on specimen tracking and clinical, laboratory, and imaging data capture in support of studies to optimize detection and analysis of brain tumour–specific mutations. It currently includes 4,392 specimens drawn from 611 subjects, the majority with brain tumours. As EV science evolves, we plan biorepository changes which may reflect multi-institutional collaborations, proteomic interfaces, additional biofluids, changes in operating procedures and kits for specimen handling, novel procedures for detection of tumour-specific EVs, and for RNA extraction and changes in the taxonomy of EVs. We have used an ontology-driven data model and web-based architecture with a graph theory–driven GUI to accommodate and stimulate the semantic web of EV science