Higher need for polycystic liver disease therapy in female patients: Sex-specific association between liver volume and need for therapy.

BACKGROUND AND AIMS: Prognostic tools or biomarkers are urgently needed in polycystic liver disease (PLD) to monitor disease progression and evaluate treatment outcomes. Total liver volume (TLV) is currently used to assess cross-sectional disease severity, and female patients typically have larger livers than males. Therefore, this study explores the sex-specific association between TLV and volume-reducing therapy (VRT). APPROACH AND RESULTS: In this prospective cohort study, we included patients with PLD from European treatment centers. We explored sex-specific differences in the association between baseline TLV and initiation of volume-reducing therapy and determined the cumulative incidence rates of volume-reducing therapy in our cohort.We included 358 patients, of whom 157 (43.9%) received treatment. Treated patients had a higher baseline TLV (median TLV 2.16 vs. 4.34 liter, p < 0.001), were more frequently female (69.7% vs. 89.8%, p < 0.001), and had a higher risk of liver events (HR 4.381, p < 0.001). The cumulative volume-reducing therapy rate at 1 year of follow-up was 21.0% for females compared to 9.1% for males. Baseline TLV was associated with volume-reducing therapy, and there was an interaction with sex (HR females 1.202, p < 0.001; HR males 1.790, p < 0.001; at 1.5 l). CONCLUSION: Baseline TLV is strongly associated with volume-reducing therapy initiation at follow-up in patients with PLD, with sex-specific differences in this association. Disease staging systems should use TLV to predict the need for future volume-reducing therapy in PLD separately for males and females.

Expanding the clinical application of the polycystic liver disease questionnaire: determination of a clinical threshold to select patients for therapy.

BACKGROUND: Polycystic liver disease (PLD) causes symptoms resulting from cystic volume expansion. The PLD-specific questionnaire (PLD-Q) captures symptom burden. This study aims to develop a threshold to identify patients with symptoms requiring further exploration and possibly intervention. METHODS: We recruited PLD patients with completed PLD-Qs during their patient journey. We evaluated baseline PLD-Q scores in (un)treated PLD patients to determine a threshold of clinical importance. We assessed our threshold's discriminative ability with receiver operator characteristic statistics, Youden Index, sensitivity, specificity, positive and negative predictive value parameters. RESULTS: We included 198 patients with a balanced proportion of treated (n=100) and untreated patients (n=98, PLD-Q scores 49 vs 19, p<0.001; median total liver volume 5827 vs 2185 ml, p<0.001). We established the PLD-Q threshold at 32 points. A score of ≥32 differentiates treated from untreated patients with an area under the ROC of 0.856, Youden Index 0.564, sensitivity of 85.0%, specificity of 71.4%, positive predictive value of 75.2%, and negative predictive value of 82.4%. Similar metrics were observed in predefined subgroups and an external cohort. CONCLUSION: We established the PLD-Q threshold at 32 points with high discriminative ability to identify symptomatic patients. Patients with a score ≥32 should be eligible for treatment or inclusion in trials.

Validation of a semi-automatic method to measure total liver volumes in polycystic liver disease on computed tomography - high speed and accuracy.

OBJECTIVES: Polycystic liver disease (PLD) is characterized by growth of hepatic cysts, causing hepatomegaly. Disease severity is determined using total liver volume (TLV), which can be measured from computed tomography (CT). The gold standard is manual segmentation which is time-consuming and requires expert knowledge of the anatomy. This study aims to validate the commercially available semi-automatic MMWP (Multimodality Workplace) Volume tool for CT scans of PLD patients. METHODS: We included adult patients with one (n = 60) or two (n = 46) abdominal CT scans. Semi-automatic contouring was compared with manual segmentation, using comparison of observed volumes (cross-sectional) and growth (longitudinal), correlation coefficients (CC), and Bland-Altman analyses with bias and precision, defined as the mean difference and SD from this difference. Inter- and intra-reader variability were assessed using coefficients of variation (CV) and we assessed the time to perform both procedures. RESULTS: Median TLV was 5292.2 mL (IQR 3141.4-7862.2 mL) at baseline. Cross-sectional analysis showed high correlation and low bias and precision between both methods (CC 0.998, bias 1.62%, precision 2.75%). Absolute volumes were slightly higher for semi-automatic segmentation (manual 5292.2 (3141.4-7862.2) versus semi-automatic 5432.8 (3071.9-7960.2) mL, difference 2.7%, p < 0.001). Longitudinal analysis demonstrated that semi-automatic segmentation accurately measures liver growth (CC 0.908, bias 0.23%, precision 4.04%). Inter- and intra-reader variability were small (2.19% and 0.66%) and comparable to manual segmentation (1.21% and 0.63%) (p = 0.26 and p = 0.37). Semi-automatic segmentation was faster than manual tracing (19 min versus 50 min, p = 0.009). CONCLUSIONS: Semi-automatic liver segmentation is a fast and accurate method to determine TLV and liver growth in PLD patients. KEY POINTS: • Semi-automatic liver segmentation using the commercially available MMWP volume tool accurately determines total liver volume as well as liver growth over time in polycystic liver disease patients. • This method is considerably faster than manual segmentation through the use of Hounsfield unit settings. • We used a real-life CT set for the validation and showed that the semi-automatic tool measures accurately regardless of contrast used for the CT scan or not, presence of polycystic kidneys, liver volume, and previous invasive treatment for polycystic liver disease.

Treatment of Polycystic Liver Disease: Impact on Patient-reported Symptom Severity and Health-related Quality of Life.

Polycystic liver disease (PLD) is a genetic disorder in which patients suffer from progressive development of multiple (>10) hepatic cysts. Most patients remain asymptomatic during the course of their disease. However, a minority of PLD patients suffer from symptoms caused by hepatomegaly leading to serious limitations in daily life. Untreated symptomatic PLD patients score significantly worse on health-related quality of life (HRQoL) compared to age and gender-matched populations. Currently, liver transplantation is the only curative treatment for PLD. The main goal of other available therapies is to strive for symptomatic relief and improvement of HRQoL by suppressing disease progression. In this review, we summarize the effect of PLD treatment on patient-reported outcome measures with a distinction between HRQoL and symptom severity. At present there is heterogeneity in application of questionnaires and no questionnaire is available that measures both HRQoL and PLD symptom severity. Therefore, we recommend the combination of a validated PLD-specific symptom severity questionnaire and a general HRQoL questionnaire to evaluate treatment success as a minimal core set. However, the specific choice of questionnaires depends on treatment choice and/or research question. These questionnaires may serve as a biomarker of treatment response, failure, and adverse events.

Abdominal wall hernia is a frequent complication of polycystic liver disease and associated with hepatomegaly.

BACKGROUND AND AIM: Polycystic liver disease (PLD) is related to hepatomegaly which causes an increased mechanical pressure on the abdominal wall. This may lead to abdominal wall herniation (AWH). We set out to establish the prevalence of AWH in PLD and explore risk factors. METHODS: In this cross-sectional cohort study, we assessed the presence of AWHs from PLD patients with at least 1 abdominal computed tomography or magnetic resonance imaging scan. AWH presence on imaging was independently evaluated by two researchers. Data on potential risk factors were extracted from clinical files. RESULTS: We included 484 patients of which 40.1% (n = 194) had an AWH. We found a clear predominance of umbilical hernias (25.8%, n = 125) while multiple hernias were present in 6.2% (n = 30). Using multivariate analysis, male sex (odds ratio [OR] 2.727 p < .001), abdominal surgery (OR 2.575, p < .001) and disease severity according to the Gigot classification (Type 3 OR 2.853, p < .001) were identified as risk factors. Height-adjusted total liver volume was an independent PLD-specific risk factor in the subgroup of patients with known total liver volume (OR 1.363, p = .001). Patients with multiple hernias were older (62.1 vs. 55.1, p = .001) and more frequently male (22.0% vs. 50.0%, p = .001). CONCLUSION: AWHs occur frequently in PLD with a predominance of umbilical hernias. Hepatomegaly is a clear disease-specific risk factor.

Polycystic liver: automatic segmentation using deep learning on CT is faster and as accurate compared to manual segmentation.

OBJECTIVE: This study aimed to develop and investigate the performance of a deep learning model based on a convolutional neural network (CNN) for the automatic segmentation of polycystic livers at CT imaging. METHOD: This retrospective study used CT images of polycystic livers. To develop the CNN, supervised training and validation phases were performed using 190 CT series. To assess performance, the test phase was performed using 41 CT series. Manual segmentation by an expert radiologist (Rad1a) served as reference for all comparisons. Intra-observer variability was determined by the same reader after 12 weeks (Rad1b), and inter-observer variability by a second reader (Rad2). The Dice similarity coefficient (DSC) evaluated overlap between segmentations. CNN performance was assessed using the concordance correlation coefficient (CCC) and the two-by-two difference between the CCCs; their confidence interval was estimated with bootstrap and Bland-Altman analyses. Liver segmentation time was automatically recorded for each method. RESULTS: A total of 231 series from 129 CT examinations on 88 consecutive patients were collected. For the CNN, the DSC was 0.95 ± 0.03 and volume analyses yielded a CCC of 0.995 compared with reference. No statistical difference was observed in the CCC between CNN automatic segmentation and manual segmentations performed to evaluate inter-observer and intra-observer variability. While manual segmentation required 22.4 ± 10.4 min, central and graphics processing units took an average of 5.0 ± 2.1 s and 2.0 ± 1.4 s, respectively. CONCLUSION: Compared with manual segmentation, automated segmentation of polycystic livers using a deep learning method achieved much faster segmentation with similar performance. KEY POINTS: • Automatic volumetry of polycystic livers using artificial intelligence method allows much faster segmentation than expert manual segmentation with similar performance. • No statistical difference was observed between automatic segmentation, inter-observer variability, or intra-observer variability.

Estrogens in polycystic liver disease: A target for future therapies?

BACKGROUND AND AIMS: Patients suffering from polycystic liver disease (PLD) can develop large liver volumes, leading to physical and psychological complaints, reducing quality of life. There is an unmet need for new therapies in these patients. Estrogen seems to be a promising target for new therapies. In this review, we summarize the available experimental and epidemiological evidence to unravel the role of estrogens and other female hormones in PLD, to answer clinical questions and identify new targets for therapy. METHODS: We identified all experimental and epidemiologial studies concerning estrogens or other female hormones and PLD, to answer pre-defined clinial questions. RESULTS: Female sex is the most important risk factor for the presence and severity of disease; estrogen supplementation enhances liver growth and after menopause, liver growth decreases. Experimental studies show the presence of the estrogen receptors alfa and beta on cystic cholangiocytes, and increased in vitro growth after administration of estrogen. CONCLUSIONS: Based on the available evidence, female PLD patients should be discouraged from taking estrogen-containing contraceptives or hormone replacement therapy. Since liver growth rates decline after menopause, treatment decisions should be based on measured liver growth in postmenopausal women. Finally, blockage of estrogen receptors or estrogen production is a promising target for new therapies.

New insights into targeting hepatic cystogenesis in autosomal dominant polycystic liver and kidney disease.

Introduction: Polycystic liver disease (PLD) is a rare disease defined by the growth of hepatic cysts and occurs either isolated or as an extrarenal manifestation of polycystic kidney disease. While surgery has been the mainstay in treatment of symptomatic PLD, recently discovered regulatory mechanisms affecting hepatic cystogenesis provide potential new therapies to reduce hepatic cyst burden.Areas covered: This review summarizes intracellular pathways and therapeutic targets involved in hepatic cystogenesis. While drugs that target cAMP, mTOR and bile acids were evaluated in clinical trials, investigation in autophagy, Wnt and miRNA signaling pathways are still in the pre-clinical phase. Recent epidemiological data present female hormones as a promising therapeutic target. Additionally, therapeutic advances in renal cystogenesis are reviewed for their potential application in treatment of hepatic cysts.Expert opinion: Further elucidation of the pathophysiology of hepatic cystogenesis is needed to provide additional targets and improve the efficacy of current treatments. The most promising therapeutic target in PLD is the female hormone pathway, given the increased severity in women and the harmful effects of exogenous estrogens. In addition, combining current pharmaceutical and surgical therapies can lead to improved outcomes. Lastly, the rarity of PLD creates the need to share expertise internationally.