4 research outputs found

    A deep-learning approach to aid in diagnosing Barrett’s oesophagus related dysplasia

    Get PDF
    Barrett's oesophagus is the only known precursor to oesophagus carcinoma. Histologically, it is defined as a condition of columnar cells replacing the standard squamous lining. Those altered cells are prone to cytological and architectural abnormalities, known as dysplasia. The dysplastic degree varies from low to high grade and can evolve into invasive carcinoma or adenocarcinoma. Thus, detecting high-grade and intramucosal carcinoma during the surveillance of Barrett's oesophagus patients is vital so they can be treated by surgical resection. Unfortunately, the achieved interobserver agreement for grading dysplasia among pathologists is only fair to moderate. Nowadays, grading Barrett's dysplasia is limited to visual examination by pathologists for glass or virtual slides. This work aims to diagnose different grades of dysplasia in Barrett’s oesophagus, particularly high-grade dysplasia, from virtual histopathological slides of oesophagus tissue. In the first approach, virtual slides were analysed at a low magnification to detect regions of interest and predict the grade of dysplasia based on the analysis of the virtual slides at 10X magnification. Transfer learning was employed to partially fine-tune two deep-learning networks using healthy and Barrett’s oesophagus tissue. Then, the two networks were connected. The proposed model achieved 0.57 sensitivity, 0.79 specificity and moderate agreement with a pathologist. On the contrary, the second approach processed the slides at a higher magnification (40X magnification). It adapted novelty detection and local outlier factor alongside transfer learning to solve the multiple instances learning problem. It increased the performance of the diagnosis to 0.84 sensitivity and 0.92 specificity, and the interobserver agreement reached a substantial level. Finally, the last approach mimics the pathologists’ procedure to diagnose dysplasia, relying on both magnifications. Thus, their behaviours during the assessment were analysed. As a result, it was found that employing a multi-scale approach to detect dysplastic tissue using a low magnification level (10X magnification) and grade dysplasia at a higher level (40X magnification). The proposed computer-aided diagnosis system was built using networks from the first two approaches. It scored 0.90 sensitivity, 0.94 specificity and a substantial agreement with the pathologist and a moderate agreement with the other expert

    Better prognostic markers for nonmuscle invasive papillary urothelial carcinomas

    Get PDF
    Bladder cancer is a common type of cancer, especially among men in developed countries. Most cancers in the urinary bladder are papillary urothelial carcinomas. They are characterized by a high recurrence frequency (up to 70 %) after local resection. It is crucial for prognosis to discover these recurrent tumours at an early stage, especially before they become muscle-invasive. Reliable prognostic biomarkers for tumour recurrence and stage progression are lacking. This is why patients diagnosed with a non-muscle invasive bladder cancer follow extensive follow-up regimens with possible serious side effects and with high costs for the healthcare systems. WHO grade and tumour stage are two central biomarkers currently having great impact on both treatment decisions and follow-up regimens. However, there are concerns regarding the reproducibility of WHO grading, and stage classification is challenging in small and fragmented tumour material. In Paper I, we examined the reproducibility and the prognostic value of all the individual microscopic features making up the WHO grading system. Among thirteen extracted features there was considerable variation in both reproducibility and prognostic value. The only feature being both reasonably reproducible and statistically significant prognostic was cell polarity. We concluded that further validation studies are needed on these features, and that future grading systems should be based on well-defined features with true prognostic value. With the implementation of immunotherapy, there is increasing interest in tumour immune response and the tumour microenvironment. In a search for better prognostic biomarkers for tumour recurrence and stage progression, in Paper II, we investigated the prognostic value of tumour infiltrating immune cells (CD4, CD8, CD25 and CD138) and previously investigated cell proliferation markers (Ki-67, PPH3 and MAI). Low Ki 67 and tumour multifocality were associated with increased recurrence risk. Recurrence risk was not affected by the composition of immune cells. For stage progression, the only prognostic immune cell marker was CD25. High values for MAI was also strongly associated with stage progression. However, in a multivariate analysis, the most prognostic feature was a combination of MAI and CD25. BCG-instillations in the bladder are indicated in intermediate and high-risk non-muscle invasive bladder cancer patients. This old-fashion immunotherapy has proved to reduce both recurrence- and progression-risk, although it is frequently followed by unpleasant side-effects. As many as 30-50% of high-risk patients receiving BCG instillations, fail by develop high-grade recurrences. They do not only suffer from unnecessary side-effects, but will also have a delay in further treatment. Together with colleagues at three different Dutch hospitals, in Paper III, we looked at the prognostic and predictive value of T1-substaging. A T1-tumour invades the lamina propria, and we wanted to separate those with micro- from those with extensive invasion. We found that BCG-failure was more common among patients with extensive invasion. Furthermore, T1-substaging was associated with both high-grade recurrence-free and progression-free survival. Finally, in Paper IV, we wanted to investigate the prognostic value of two classical immunohistochemical markers, p53 and CK20, and compare them with previously investigated proliferation markers. p53 is a surrogate marker for mutations in the gene TP53, considered to be a main characteristic for muscle-invasive tumours. CK20 is a surrogate marker for luminal tumours in the molecular classification of bladder cancer, and is frequently used to distinguish reactive urothelial changes from urothelial carcinoma in situ. We found both positivity for p53 and CK20 to be significantly associated with stage progression, although not performing better than WHO grade and stage. The proliferation marker MAI, had the highest prognostic value in our study. Any combination of variables did not perform better in a multivariate analysis than MAI alone
    corecore