Search

Primary sclerosing cholangitis (PSC) is a chronic inflammatory disease of the intra- and extrahepatic bile ducts. Over time, the chronic inflammation may lead to fibrosis and obstruction of the biliary tree, which prevents normal flow of bile and causes cholestasis. Obstructive fibrosis will often lead to liver cirrhosis, which can be treated with liver transplantation surgery. Liver transplantation is one of the only feasible treatment options for this group of patients. Aetiology of PSC remains elusive and therapeutic options are difficult to develop. Moreover, chronic inflammation of biliary epithelium predisposes to biliary neoplasia/ dysplasia and cholangiocarcinoma. The incidence of cholangiocarcinoma in this population is high, the prognosis is poor, and treatment options are sparse. Preemptive liver transplantation, before development of cholangiocarcinoma (CCA) or metastatic disease, may improve overall survival significantly. Liver biopsy is no longer considered a mandatory part of routine work-up to assign the diagnosis of PSC according to the international guidelines for disease management and diagnosis (EASL). It is, however, needed to exclude concomitant autoimmune hepatitis and small duct PSC, not visible in imaging. Additionally, inflammation activity in the liver tissue cannot be evaluated by any other modality. Concerns about applying liver biopsy specimens in evaluation of disease stage are related to the patchiness of the disease. We aimed to investigate the value of liver histology in diagnosis and in measuring disease progression in PSC patients (n=300), diagnosed at Helsinki University Hospital between 1988 and 2018. In addition, we examined whether we could develop automated analysis methods to evaluate liver histology in PSC. We created a non-invasive HelPSCreen measurement tool to screen and diagnose PSC based on only laboratory parameters. With this tool, we were able to reliably screen PSC patients from a larger cohort of patients with inflammatory bowel disease (IBD). Nevertheless, histology did not add value in the primary diagnosis of PSC. On the other hand, we created a novel histological scoring system – the PSC histoscore – a PSC-tailored system to evaluate liver samples of PSC patients. By using this scoring system, the risk for major clinical endpoints can be predicted better. In this study, we showed that inflammation activity, in addition to disease stage, evaluated from histological liver samples, had substantial prognostic value in estimating the course of disease. As clinical endpoints, we applied liver-related deaths, cholangiocarcinomas, and liver transplantation. Additionally, we created an artificial intelligence (AI)-based image analysis tool to quantify objectively and repeatably several histological features from cytokeratin 7 (K7)-stained liver biopsy specimens of patients with PSC. Using this technology, we showed that a single immunohistochemical staining method can provide substantial prognostic information compared with the traditional surrogate endpoint markers. We demonstrated that K7-staining, as a single immunohistochemical staining method, can be applied in evaluation of chronic cholestasis, as it correlates well with clinical indices of cholestasis. Additionally, the K7-load in a liver biopsy specimen of a patient with PSC predicts disease outcome measured by either a pathologist or an automated image analysis tool. In conclusion, we promote the use of liver histology, PSC histoscore, and K7- staining as part of the routine follow-up protocols because they provide prognostic information, even at an early stage of disease. Since newly developed treatment options are becoming available and several drug trials are ongoing, it might be feasible to test the performance of liver biopsy specimens as surrogate endpoint markers and to evaluate treatment response, also because inflammation activity, shown to have prognostic value, cannot be evaluated in any other way. The value of histology can be increased by applying automated objective methods in their evaluation when high quantities of objective numeric data are produced. International collaboration is imperative in order to develop better prognostic markers and treatment options for patients with PSC. As a future objective, we intend to validate our results in larger international cohorts. Primaari sklerosoiva kolangiitti (PSC) on krooninen, tulehduksellinen sappitiesairaus. Edetessään se aiheuttaa arpikudosmuodostusta sappiteiden ympärille, joka ahtauttaa sappiteitä ja estää sapen normaalia eritystä ja kulkua (eng. cholestasis). Lisääntyvä arpikudos voi johtaa maksakirroosiin, johon ainut hoitomuoto on maksan siirto. Lääkehoidon kehittäminen on haasteellista, koska taudin etiologisia tekijöitä ei täysin tunneta. Lisäksi krooninen tulehdus altistaa sappiteiden syövälle – kolangiokarsinoomalle. Kolangiokarsinooman insidenssi PSC-populaatiossa on korkea, ennuste on huono ja hoitomahdollisuudet ovat rajalliset. Oikein ajoitettu ennalta ehkäisevä maksan siirto voi parantaa potilaiden ennustetta huomattavasti. Kansainvälisten hoitosuositusten mukaisesti maksabiopsiaa ei pidetä tarpeellisena taudin diagnosoimiseksi. PSC:n aiheuttamat muutokset maksakudoksessa ovat usein läiskäiset, joten taudin edenneisyyden arvioimista maksabiopsiasta on pidetty epävarmana. Tulehdusaktiviteetin arvioiminen kuitenkin onnistuu ainoastaan biopsiasta. Tavoitteemme oli tutkia Helsingin Yliopistollisen keskussairaalan (HUH) alueella vuosien 1988 ja 2018 välillä PSC diagnoosin saaneiden potilaiden (n=300) maksabiopsioita ja niiden merkitystä taudin toteamisessa ja ennusteen arvioinnissa. Tavoitteena oli selvittää, mitä uutta tietoa näytteistä saadaan tulehdusaktiviteettia arvioimalla, ja voidaanko näitä näytteitä hyödyntämällä rakentaa automatisoitu arviointityökalu. Rakensimme kajoamattoman laboratorioparametreihin perustuvan työkalun nimeltään HelPSCreen, jonka avulla pystyimme seulomaan ja diagnosoimaan PSC potilaat kohortista, joka koostui muita maksasairauksia sairastavista potilaista. Histologia ei kuitenkaan tuonut tähän merkittävää lisäarvoa. Lisäksi loimme histologisen, PSC:lle räätälöidyn luokittelumenetelmän maksabiopsioiden tutkimiseen, (PSC-Histoscore). Tällä menetelmällä pystyimme ennustamaan taudin kulkua biopsiassa esiintyvien histologisten muuttujien avulla. Osoitimme, että tulehdusaktiviteetti sekä sidekudoksen määrä ennustavat merkittävällä tavalla päätetapahtumia. Rakensimme myös tekoälyyn pohjautuvan kuva-analyysityökalun, jolla pystyimme objektiivisesti sekä toistettavasti mittaamaan useita histologisia piirteitä PSC-potilaiden sytokeratiini 7-värjätyistä maksabiopsioista. Tämä yksittäinen värjäysmenetelmä tuotti merkittävästi ennusteen kannalta oleellista tietoa verrattuna perinteisiin ennustemittareihin. Johtopäätöksiimme pohjautuen kannustamme hyödyntämään PSC-potilaiden seurannassa maksabiopsioita, tekemään näistä K7-värjäyksiä, sekä käyttämään histologisessa arvioinnissa PSC-Histoscore-menetelmää.

At present, no sensitive or specific screening test exists for primary sclerosing cholangitis (PSC). PSC screening is mainly based on elevated alkaline phosphatase (ALP) in patients with inflammatory bowel disease (IBD). We aimed to produce a screening score based on laboratory tests to predict the likelihood of PSC. Moreover, we evaluated the additional roles of liver histology and magnetic resonance cholangiopancreatography (MRCP) in the diagnosis of PSC. The data of 385 patients who came for their first endoscopic retrograde cholangiography (ERC) to confirm PSC diagnosis were retrieved from the PSC registry of the Helsinki University Hospital. Overall, 69 patients referred for ERC with suspected PSC, in whom PSC was excluded by ERC or liver biopsy and MRCP, served as controls. We included patients’ demographics and 13 laboratory test results in the analysis. Variables with significant odds ratios were selected for multivariate logistic regression, which was used to create a novel scoring system for PSC. The presence of IBD, serum perinuclear anti-neutrophil cytoplasmic antibodies, and ALP levels demonstrated the highest predictive value for PSC. A score was assigned for each statistically significant predictor. The optimal cut-off point for the score was ≥3, with an AUC of 0.83 (95%CI: 0.78–0.88). The addition of liver histology or MRCP findings to the score did not add a predictive value. In conclusion, we created a novel, simple scoring system to screen the probability of PSC. The HelPSCreen-score may help to assess the disease prevalence and to target further investigations in patients suspected of PSC.

Additional file 1.