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  1. Article ; Online: Reliability as a Precondition for Trust—Segmentation Reliability Analysis of Radiomic Features Improves Survival Prediction

    Gustav Müller-Franzes / Sven Nebelung / Justus Schock / Christoph Haarburger / Firas Khader / Federico Pedersoli / Maximilian Schulze-Hagen / Christiane Kuhl / Daniel Truhn

    Diagnostics, Vol 12, Iss 247, p

    2022  Volume 247

    Abstract: Machine learning results based on radiomic analysis are often not transferrable. A potential reason for this is the variability of radiomic features due to varying human made segmentations. Therefore, the aim of this study was to provide comprehensive ... ...

    Abstract Machine learning results based on radiomic analysis are often not transferrable. A potential reason for this is the variability of radiomic features due to varying human made segmentations. Therefore, the aim of this study was to provide comprehensive inter-reader reliability analysis of radiomic features in five clinical image datasets and to assess the association of inter-reader reliability and survival prediction. In this study, we analyzed 4598 tumor segmentations in both computed tomography and magnetic resonance imaging data. We used a neural network to generate 100 additional segmentation outlines for each tumor and performed a reliability analysis of radiomic features. To prove clinical utility, we predicted patient survival based on all features and on the most reliable features. Survival prediction models for both computed tomography and magnetic resonance imaging datasets demonstrated less statistical spread and superior survival prediction when based on the most reliable features. Mean concordance indices were C mean = 0.58 [most reliable] vs. C mean = 0.56 [all] ( p < 0.001, CT) and C mean = 0.58 vs. C mean = 0.57 ( p = 0.23, MRI). Thus, preceding reliability analyses and selection of the most reliable radiomic features improves the underlying model’s ability to predict patient survival across clinical imaging modalities and tumor entities.
    Keywords radiomic features ; overall survival ; segmentation variability ; inter-rater reliability ; neural network ; robustness ; Medicine (General) ; R5-920
    Subject code 519
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization

    Tianyu Han / Sven Nebelung / Federico Pedersoli / Markus Zimmermann / Maximilian Schulze-Hagen / Michael Ho / Christoph Haarburger / Fabian Kiessling / Christiane Kuhl / Volkmar Schulz / Daniel Truhn

    Nature Communications, Vol 12, Iss 1, Pp 1-

    2021  Volume 11

    Abstract: Unmasking the decision making process of machine learning models is essential for implementing diagnostic support systems in clinical practice. Here, the authors demonstrate that adversarially trained models can significantly enhance the usability of ... ...

    Abstract Unmasking the decision making process of machine learning models is essential for implementing diagnostic support systems in clinical practice. Here, the authors demonstrate that adversarially trained models can significantly enhance the usability of pathology detection as compared to their standard counterparts.
    Keywords Science ; Q
    Language English
    Publishing date 2021-07-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Sarcopenia and Myosteatosis as Prognostic Markers in Patients with Advanced Cholangiocarcinoma Undergoing Palliative Treatment

    Markus S. Jördens / Linda Wittig / Lisa Heinrichs / Verena Keitel / Maximilian Schulze-Hagen / Gerald Antoch / Wolfram T. Knoefel / Georg Fluegen / Tom Luedde / Christina Loberg / Christoph Roderburg / Sven H. Loosen

    Journal of Clinical Medicine, Vol 10, Iss 4340, p

    2021  Volume 4340

    Abstract: Background: Cholangiocarcinoma (CCA) represents the second most common primary liver cancer and is characterized by a very poor outcome, but reliable prognostic markers are largely missing. Sarcopenia, the progressive loss of muscle mass and strength, as ...

    Abstract Background: Cholangiocarcinoma (CCA) represents the second most common primary liver cancer and is characterized by a very poor outcome, but reliable prognostic markers are largely missing. Sarcopenia, the progressive loss of muscle mass and strength, as well as myosteatosis have been associated with an unfavorable outcome in several clinical conditions, including cancer. Here, we evaluated the prognostic relevance of sarcopenia and myosteatosis using routine abdominal CT (computed tomography) scans in advanced stage CCA patients undergoing palliative treatment. Methods: Routine abdominal CT scans were used to assess the skeletal muscle and the psoas muscle index (L3SMI/L3PMI) at the level of the third lumbar vertebra as radiological indices for sarcopenia as well as the mean skeletal muscle attenuation (MMA) as a surrogate for myosteatosis. Results were correlated with clinical data and outcomes. Results: Using a calculated optimal cut-off value of 71.95 mm 2 /cm, CCA patients with an L3SMI value below this cut-off showed a significantly reduced median overall survival (OS) of only 250 days compared to 450 days in patients with a higher L3SMI. Moreover, the median OS of CCA patients with an L3PMI above 6345 mm 2 /cm was 552 days compared to 252 days in patients with a lower L3PMI. Finally, CCA patients with an MMA above 30.51 Hounsfield Units survived significantly longer (median OS: 430 days) compared to patients with an MMA value below this ideal cut-off (median OS: 215 days). The prognostic relevance of L3SMI, L3PMI, and MMA was confirmed in uni- and multivariate Cox regression analyses. Conclusion: Routine abdominal CT scans represent a unique opportunity to evaluate sarcopenia as well as myosteatosis in advanced CCA patients. We identified the L3SMI/L3PMI as well as the MMA as negative prognostic factors in CCA patients undergoing palliative therapy, arguing that the “opportunistic” evaluation of these parameters might yield important clinical information in daily routine.
    Keywords cholangiocellular carcinoma ; CCA ; sarcopenia ; myosteatosis ; MMA ; prognostic marker ; Medicine ; R
    Subject code 610
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: CT-Based Prediction of Liver Function and Post-PVE Hypertrophy Using an Artificial Neural Network

    Daniel Heise / Maximilian Schulze-Hagen / Jan Bednarsch / Roman Eickhoff / Andreas Kroh / Philipp Bruners / Simon B. Eickhoff / Ralph Brecheisen / Florian Ulmer / Ulf Peter Neumann

    Journal of Clinical Medicine, Vol 10, Iss 3079, p

    2021  Volume 3079

    Abstract: Background: This study aimed to evaluate whether hypertrophy after portal vein embolization (PVE) and maximum liver function capacity (LiMAx) are predictable by an artificial neural network (ANN) model based on computed tomography (CT) texture features. ... ...

    Abstract Background: This study aimed to evaluate whether hypertrophy after portal vein embolization (PVE) and maximum liver function capacity (LiMAx) are predictable by an artificial neural network (ANN) model based on computed tomography (CT) texture features. Methods: We report a retrospective analysis on 118 patients undergoing preoperative assessment by CT before and after PVE for subsequent extended liver resection due to a malignant tumor at RWTH Aachen University Hospital. The LiMAx test was carried out in a subgroup of 55 patients prior to PVE. Associations between CT texture features and hypertrophy as well as liver function were assessed by a multilayer perceptron ANN model. Results: Liver volumetry showed a median hypertrophy degree of 33.9% (16.5–60.4%) after PVE. Non-response, defined as a hypertrophy grade lower than 25%, was found in 36.5% (43/118) of the cases. The ANN prediction of the hypertrophy response showed a sensitivity of 95.8%, specificity of 44.4% and overall prediction accuracy of 74.6% ( p < 0.001). The observed median LiMAx was 327 (248–433) μg/kg/h and was strongly correlated with the predicted LiMAx (R 2 = 0.89). Conclusion: Our study shows that an ANN model based on CT texture features is able to predict the maximum liver function capacity and may be useful to assess potential hypertrophy after performing PVE.
    Keywords liver function ; liver volume ; portal vein embolization ; artificial neural network ; computed tomography ; Medicine ; R
    Subject code 610
    Language English
    Publishing date 2021-07-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: A Radiomics Approach to Predict the Emergence of New Hepatocellular Carcinoma in Computed Tomography for High-Risk Patients with Liver Cirrhosis

    Eric Tietz / Daniel Truhn / Gustav Müller-Franzes / Marie-Luise Berres / Karim Hamesch / Sven Arke Lang / Christiane Katharina Kuhl / Philipp Bruners / Maximilian Schulze-Hagen

    Diagnostics, Vol 11, Iss 1650, p

    2021  Volume 1650

    Abstract: Liver cirrhosis poses a major risk for the development of hepatocellular carcinoma (HCC). This retrospective study investigated to what extent radiomic features allow the prediction of emerging HCC in patients with cirrhosis in contrast-enhanced computed ...

    Abstract Liver cirrhosis poses a major risk for the development of hepatocellular carcinoma (HCC). This retrospective study investigated to what extent radiomic features allow the prediction of emerging HCC in patients with cirrhosis in contrast-enhanced computed tomography (CECT). A total of 51 patients with liver cirrhosis and newly detected HCC lesions ( n = 82) during follow-up (FU-CT) after local tumor therapy were included. These lesions were not to have been detected by the radiologist in the chronologically prior CECT (PRE-CT). For training purposes, segmentations of 22 patients with liver cirrhosis but without HCC-recurrence were added. A total of 186 areas (82 HCCs and 104 cirrhotic liver areas without HCC) were analyzed. Using univariate analysis, four independent features were identified, and a multivariate logistic regression model was trained to classify the outlined regions as “HCC probable” or “HCC improbable”. In total, 60/82 (73%) of segmentations with later detected HCC and 84/104 (81%) segmentations without HCC were classified correctly (AUC of 81%, 95% CI 74–87%), yielding a sensitivity of 72% (95% CI 57–83%) and a specificity of 86% (95% CI 76–96%). In conclusion, the model predicted the occurrence of new HCCs within segmented areas with an acceptable sensitivity and specificity in cirrhotic liver tissue in CECT.
    Keywords CT ; liver cirrhosis ; hepatocellular carcinoma ; radiomics ; tumor prediction ; Medicine (General) ; R5-920
    Subject code 610
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Progressive Sarcopenia Correlates with Poor Response and Outcome to Immune Checkpoint Inhibitor Therapy

    Sven H. H. Loosen / Vincent van den Bosch / Joao Gorgulho / Maximilian Schulze-Hagen / Jennis Kandler / Markus S. S. Jördens / Frank Tacke / Christina Loberg / Gerald Antoch / Tim Brümmendorf / Ulf P. Neumann / Christiane Kuhl / Tom Luedde / Christoph Roderburg

    Journal of Clinical Medicine, Vol 10, Iss 1361, p

    2021  Volume 1361

    Abstract: Background : Immune checkpoint inhibitors (ICIs) represent a new therapeutic standard for an increasing number of tumor entities. Nevertheless, individual response and outcome to ICI is very heterogeneous, and the identification of the ideal ICI ... ...

    Abstract Background : Immune checkpoint inhibitors (ICIs) represent a new therapeutic standard for an increasing number of tumor entities. Nevertheless, individual response and outcome to ICI is very heterogeneous, and the identification of the ideal ICI candidate has remained one of the major issues. Sarcopenia and the progressive loss of muscle mass and strength, as well as muscular fat deposition, have been established as negative prognostic factors for a variety of diseases, but their role in the context of ICI therapy is not fully understood. Here, we have evaluated skeletal muscle composition as a novel prognostic marker in patients undergoing ICI therapy for solid malignancies. Methods: We analyzed patients with metastasized cancers receiving ICI therapy according to the recommendation of the specific tumor board . Routine CT scans before treatment initialization and during ICI therapy were used to assess the skeletal muscle index (L3SMI) as well as the mean skeletal muscle attenuation (MMA) in n = 88 patients receiving ICI therapy. Results: While baseline L3SMI and MMA values were unsuitable for predicting the individual response and outcome to ICI therapy, longitudinal changes of the L3SMI and MMA (∆L3SMI, ∆MMA) during ICI therapy turned out to be a relevant marker of therapy response and overall survival. Patients who responded to ICI therapy at three months had a significantly higher ∆L3SMI compared to non-responders (−3.20 mm 2 /cm vs. 1.73 mm 2 /cm, p = 0.002). Moreover, overall survival (OS) was significantly lower in patients who had a strongly decreasing ∆L3SMI (<−6.18 mm 2 /cm) or a strongly decreasing ∆MMA (<−0.4 mm 2 /cm) during the first three month of ICI therapy. Median OS was only 127 days in patients with a ∆L3SMI of below −6.18 mm 2 /cm, compared to 547 days in patients with only mildly decreasing or even increasing ∆L3SMI values ( p < 0.001). Conclusion: Both progressive sarcopenia and an increasing skeletal muscle fat deposition are associated with poor response and outcome to ICI ...
    Keywords sarcopenia ; checkpoint inhibitors ; ICI ; PD-L1 ; PD-1 ; prognosis ; Medicine ; R
    Subject code 610
    Language English
    Publishing date 2021-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: IL-6 and IL-8 Serum Levels Predict Tumor Response and Overall Survival after TACE for Primary and Secondary Hepatic Malignancies

    Sven H. Loosen / Maximilian Schulze-Hagen / Catherine Leyh / Fabian Benz / Mihael Vucur / Christiane Kuhl / Christian Trautwein / Frank Tacke / Philipp Bruners / Christoph Roderburg / Tom Luedde

    International Journal of Molecular Sciences, Vol 19, Iss 6, p

    2018  Volume 1766

    Abstract: While surgical resection represents the standard potentially curative therapy for liver cancer, transarterial chemoembolization (TACE) has evolved as a standard therapy for intermediate-stage hepatocellular carcinoma (HCC) as well as liver metastases. ... ...

    Abstract While surgical resection represents the standard potentially curative therapy for liver cancer, transarterial chemoembolization (TACE) has evolved as a standard therapy for intermediate-stage hepatocellular carcinoma (HCC) as well as liver metastases. However, it is still not fully understood which patients particularly benefit from TACE. Cytokines represent a broad category of signaling molecules that might reflect concomitant inflammation as an adverse prognostic factor. Here, we evaluated the role of interleukin (IL)-6, IL-8, and CC-chemokine ligand (CCL)22 as biomarkers in the context of TACE treatment. Cytokine serum levels were analyzed by multiplex immunoassay in 54 patients (HCC: n = 44, liver metastases: n = 10) undergoing TACE as well as 51 healthy controls. Patients with primary and secondary liver cancer showed significantly elevated levels of IL-6 and IL-8 but not CCL22 compared to healthy controls. Interestingly, low pre-interventional levels of IL-6 and IL-8 were predictors for an objective response after TACE in binary logistic regression. In contrast, patients with high pre-interventional IL-6 and IL-8 serum levels not only poorly responded to TACE but had a significantly impaired overall survival. Serum levels of IL-6 and IL-8 represent promising biomarkers for patients undergoing TACE and might help to pre-interventionally identify patients who particularly benefit from TACE regarding objective treatment response and overall survival.
    Keywords cancer ; TACE ; cytokines ; HCC ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
    Subject code 610
    Language English
    Publishing date 2018-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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