<scp>FDG</scp>‐<scp>PET</scp>/<scp>MRI</scp> imaging for the management of alveolar echinococcosis: initial clinical experience at a reference centre in Austria

Lötsch, Felix; Waneck, Fredrik; Groger, Mirjam; Auer, Herbert; Kaczirek, Klaus; Rausch, Ivo; Wadsak, Wolfgang; Hacker, Marcus; Lagler, Heimo; Ramharter, Michael; Karanikas, Georgios

doi:10.1111/tmi.13228

Cited by 16 publications

(10 citation statements)

References 24 publications

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“…HAE proliferates by the means of budding or infiltration, which could produce new vesicles that infiltrated into the deep tissue. HAE could not only directly infiltrate the adjacent tissue, but also could be moved to the peritoneum and distant organs through lymphatic channels and blood vessels 3 . The diagnosis of HAE mainly depends on epidemiological evidence, clinical characteristics, serology and immunological test, imaging examination, and other factors 4 .…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: The diagnostic nomogram of platelet-based score models for hepatic alveolar echinococcosis and atypical liver cancer

Wang

Guan

et al. 2019

Sci Rep

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Hepatic alveolar echinococcosis (HAE) and liver cancer had similarities in imaging results, clinical characteristics, and so on. And it is difficult for clinicians to distinguish them before operation. The aim of our study was to build a differential diagnosis nomogram based on platelet (PLT) score model and use internal validation to check the model. The predicting model was constructed by the retrospective database that included in 153 patients with HAE (66 cases) or liver cancer (87 cases), and all cases was confirmed by clinicopathology and collected from November 2011 to December 2018. Lasso regression analysis model was used to construct data dimensionality reduction, elements selection, and building prediction model based on the 9 PLT-based scores. A multi-factor regression analysis was performed to construct a simplified prediction model, and we added the selected PLT-based scores and relevant clinicopathologic features into the nomogram. Identification capability, calibration, and clinical serviceability of the simplified model were evaluated by the Harrell’s concordance index (C-index), calibration plot, receiver operating characteristic curve (ROC), and decision curve. An internal validation was also evaluated by the bootstrap resampling. The simplified model, including in 4 selected factors, was significantly associated with differential diagnosis of HAE and liver cancer. Predictors of the simplified diagnosis nomogram consisted of the API index, the FIB-4 index, fibro-quotent (FibroQ), and fibrosis index constructed by King’s College Hospital (King’s score). The model presented a perfect identification capability, with a high C-index of 0.929 (0.919 through internal validation), and good calibration. The area under the curve (AUC) values of this simplified prediction nomogram was 0.929, and the result of ROC indicated that this nomogram had a good predictive value. Decision curve analysis showed that our differential diagnosis nomogram had clinically identification capability. In conclusion, the differential diagnosis nomogram could be feasibly performed to verify the preoperative individualized diagnosis of HAE and liver cancer.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: The diagnostic nomogram of platelet-based score models for hepatic alveolar echinococcosis and atypical liver cancer

Wang

Guan

et al. 2019

Sci Rep

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“…The 18F-FDG PET-CT reflects the metabolism of the lesions through the semiquantitative index (SUV) value to determine biological activity in HAE lesions. Therefore, the 18F-FDG PET-CT shows the active areas of lesions that cannot be detected by traditional imaging examinations [ 30 – 32 ].…”

Section: Discussionmentioning

confidence: 99%

Hepatic Alveolar Echinococcosis: Predictive Biological Activity Based on Radiomics of MRI

Ren

Wang

Miao

et al. 2021

BioMed Research International

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Background. To evaluate the role of radiomics based on magnetic resonance imaging (MRI) in the biological activity of hepatic alveolar echinococcosis (HAE). Methods. In this study, 90 active and 46 inactive cases of HAE patients were analyzed retrospectively. All the subjects underwent MRI and positron emission tomography computed tomography (PET-CT) before surgery. A total of 1409 three-dimensional radiomics features were extracted from the T2-weighted MR images (T2WI). The inactive group in the training cohort was balanced via the synthetic minority oversampling technique (SMOTE) method. The least absolute shrinkage and selection operator (LASSO) regression method was used for feature selection. The machine learning (ML) classifiers were logistic regression (LR), multilayer perceptron (MLP), and support vector machine (SVM). We used a fivefold cross-validation strategy in the training cohorts. The classification performance of the radiomics signature was evaluated using receiver operating characteristic curve (ROC) analysis in the training and test cohorts. Results. The radiomics features were significantly associated with the biological activity, and 10 features were selected to construct the radiomics model. The best performance of the radiomics model for the biological activity prediction was obtained by MLP ( AUC = 0.830 ± 0.053 ; accuracy = 0.817 ; sensitivity = 0.822 ; specificity = 0.811 ). Conclusions. We developed and validated a radiomics model as an adjunct tool to predict the HAE biological activity by combining T2WI images, which achieved results nearly equal to the PET-CT findings.

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“…CT in a combination with PET (positron emission tomography) is considered to be one of the most reliable imaging techniques for early diagnosis of AE and monitoring of the changes and biological activity of the disease [23]. Particularly in children when surgical treatment is not possible and long follow-up is needed PET/MRI could reduce radiation exposure compared to PET/CT [24]. However, limited availability in primary centers, longer scanning time, and costs remain the main drawbacks of PET/CT and PET/MRI techniques [23].…”

Section: Discussionmentioning

confidence: 99%

Alveolar Echinococcosis in Children

Jonaitytė

Judickas

Tamulevičienė

et al. 2020

Case Reports in Pediatrics

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Alveolar echinococcosis (AE) is an infectious zoonotic disease that is caused by Echinococcus multilocularis. The disease is generally identified accidentally because of the long asymptomatic period, has a malignant behaviour, and mainly occurs in the liver. Usually it is diagnosed in adults and is very rare in pediatric patients. We report two cases of AE and 1 differential case between AE and cystic echinococcosis (CE) in children: two of them had lesions in the liver and one had rare extrahepatic presentation of a cyst in the spleen. All our patients received chemotherapy with albendazole because surgical treatment was not recommended. The children were followed-up from 10 to 30 months and no significant improvement was seen. In this report we discuss the difficulties we faced in the treatment and follow-up of these patients. We also review the main clinical manifestations, general diagnostic methods, and treatment options of AE according to the current literature.

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FDG‐PET/MRI imaging for the management of alveolar echinococcosis: initial clinical experience at a reference centre in Austria

Cited by 16 publications

References 24 publications

RETRACTED ARTICLE: The diagnostic nomogram of platelet-based score models for hepatic alveolar echinococcosis and atypical liver cancer

RETRACTED ARTICLE: The diagnostic nomogram of platelet-based score models for hepatic alveolar echinococcosis and atypical liver cancer

Hepatic Alveolar Echinococcosis: Predictive Biological Activity Based on Radiomics of MRI

Alveolar Echinococcosis in Children

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