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  • Springer Science and Business Media LLC  (18)
  • 1
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    Dual-energy CT in early acute pancreatitis: improved detection using iodine quantification
    Springer Science and Business Media LLC ; 2019
    In:  European Radiology Vol. 29, No. 5 ( 2019-5), p. 2226-2232
    Details
    In: European Radiology, Springer Science and Business Media LLC, Vol. 29, No. 5 ( 2019-5), p. 2226-2232
    Type of Medium: Online Resource
    ISSN: 0938-7994 , 1432-1084
    URL: Article
    DOI: 10.1007/s00330-018-5844-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 2
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    Diagnostic accuracy of quantitative dual-energy CT-based volumetric bone mineral density assessment for the prediction of osteoporosis-associated fractures
    Springer Science and Business Media LLC ; 2022
    In:  European Radiology Vol. 32, No. 5 ( 2022-05), p. 3076-3084
    Details
    In: European Radiology, Springer Science and Business Media LLC, Vol. 32, No. 5 ( 2022-05), p. 3076-3084
    Abstract: To evaluate the predictive value of volumetric bone mineral density (BMD) assessment of the lumbar spine derived from phantomless dual-energy CT (DECT)-based volumetric material decomposition as an indicator for the 2-year occurrence risk of osteoporosis-associated fractures. Methods L1 of 92 patients (46 men, 46 women; mean age, 64 years, range, 19–103 years) who had undergone third-generation dual-source DECT between 01/2016 and 12/2018 was retrospectively analyzed. For phantomless BMD assessment, dedicated DECT postprocessing software using material decomposition was applied. Digital files of all patients were sighted for 2 years following DECT to obtain the incidence of osteoporotic fractures. Receiver operating characteristic (ROC) analysis was used to calculate cut-off values and logistic regression models were used to determine associations of BMD, sex, and age with the occurrence of osteoporotic fractures. Results A DECT-derived BMD cut-off of 93.70 mg/cm 3 yielded 85.45% sensitivity and 89.19% specificity for the prediction to sustain one or more osteoporosis-associated fractures within 2 years after BMD measurement. DECT-derived BMD was significantly associated with the occurrence of new fractures (odds ratio of 0.8710, 95% CI, 0.091–0.9375, p   〈  .001), indicating a protective effect of increased DECT-derived BMD values. Overall AUC was 0.9373 (CI, 0.867–0.977, p   〈  .001) for the differentiation of patients who sustained osteoporosis-associated fractures within 2 years of BMD assessment. Conclusions Retrospective DECT-based volumetric BMD assessment can accurately predict the 2-year risk to sustain an osteoporosis-associated fracture in at-risk patients without requiring a calibration phantom. Lower DECT-based BMD values are strongly associated with an increased risk to sustain fragility fractures. Key Points •Dual-energy CT–derived assessment of bone mineral density can identify patients at risk to sustain osteoporosis-associated fractures with a sensitivity of 85.45% and a specificity of 89.19%. •The DECT-derived BMD threshold for identification of at-risk patients lies above the American College of Radiology (ACR) QCT guidelines for the identification of osteoporosis (93.70 mg/cm 3 vs 80 mg/cm 3 ).
    Type of Medium: Online Resource
    ISSN: 1432-1084
    URL: Article
    DOI: 10.1007/s00330-021-08323-9
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 3
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    Radiomics of high-resolution computed tomography for the differentiation between cholesteatoma and middle ear inflammation: effects of post-reconstruction methods in a dual-center study
    Springer Science and Business Media LLC ; 2021
    In:  European Radiology Vol. 31, No. 6 ( 2021-06), p. 4071-4078
    Details
    In: European Radiology, Springer Science and Business Media LLC, Vol. 31, No. 6 ( 2021-06), p. 4071-4078
    Abstract: To evaluate the performance of radiomic features extracted from high-resolution computed tomography (HRCT) for the differentiation between cholesteatoma and middle ear inflammation (MEI), and to investigate the impact of post-reconstruction harmonization and data resampling. Methods One hundred patients were included in this retrospective dual-center study: 48 with histology-proven cholesteatoma (center A: 23; center B: 25) and 52 with MEI (A: 27; B: 25). Radiomic features (co-occurrence and run-length matrix, absolute gradient, autoregressive model, Haar wavelet transform) were extracted from manually defined 2D-ROIs. The ten best features for lesion differentiation were selected using probability of error and average correlation coefficients. A multi-layer perceptron feed-forward artificial neural network (MLP-ANN) was used for radiomics-based classification, with histopathology serving as the reference standard (70% of cases for training, 30% for validation). The analysis was performed five times each on (a) unmodified data and on data that were (b) resampled to the same matrix size, and (c) corrected for acquisition protocol differences using ComBat harmonization. Results Using unmodified data, the MLP-ANN classification yielded an overall median area under the receiver operating characteristic curve (AUC) of 0.78 (0.72–0.84). Using original data from center A and resampled data from center B, an overall median AUC of 0.88 (0.82–0.99) was yielded, while using ComBat harmonized data, an overall median AUC of 0.89 (0.79–0.92) was revealed. Conclusion Radiomic features extracted from HRCT differentiate between cholesteatoma and MEI. When using multi-centric data obtained with differences in CT acquisition parameters, data resampling and ComBat post-reconstruction harmonization clearly improve radiomics-based lesion classification. Key Points • Unenhanced high-resolution CT coupled with radiomics analysis may be useful for the differentiation between cholesteatoma and middle ear inflammation. • Pooling of data extracted from inhomogeneous CT datasets does not appear meaningful without further post-processing. • When using multi-centric CT data obtained with differences in acquisition parameters, post-reconstruction harmonization and data resampling clearly improve radiomics-based soft-tissue differentiation.
    Type of Medium: Online Resource
    ISSN: 0938-7994 , 1432-1084
    URL: Article
    DOI: 10.1007/s00330-020-07564-4
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 4
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    Single- and dual-energy CT pulmonary angiography using second- and third-generation dual-source CT systems: comparison of radiation dose and image quality
    Springer Science and Business Media LLC ; 2019
    In:  European Radiology Vol. 29, No. 9 ( 2019-9), p. 4603-4612
    Details
    In: European Radiology, Springer Science and Business Media LLC, Vol. 29, No. 9 ( 2019-9), p. 4603-4612
    Type of Medium: Online Resource
    ISSN: 0938-7994 , 1432-1084
    URL: Article
    DOI: 10.1007/s00330-018-5982-1
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 5
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    Comparison of radiomics models and dual-energy material decomposition to decipher abdominal lymphoma in contrast-enhanced CT
    Springer Science and Business Media LLC ; 2023
    In:  International Journal of Computer Assisted Radiology and Surgery Vol. 18, No. 10 ( 2023-03-06), p. 1829-1839
    Details
    In: International Journal of Computer Assisted Radiology and Surgery, Springer Science and Business Media LLC, Vol. 18, No. 10 ( 2023-03-06), p. 1829-1839
    Abstract: The radiologists’ workload is increasing, and computational imaging techniques may have the potential to identify visually unequivocal lesions, so that the radiologist can focus on equivocal and critical cases. The purpose of this study was to assess radiomics versus dual-energy CT (DECT) material decomposition to objectively distinguish visually unequivocal abdominal lymphoma and benign lymph nodes. Methods Retrospectively, 72 patients [ m , 47; age, 63.5 (27–87) years] with nodal lymphoma ( n  = 27) or benign abdominal lymph nodes ( n  = 45) who had contrast-enhanced abdominal DECT between 06/2015 and 07/2019 were included. Three lymph nodes per patient were manually segmented to extract radiomics features and DECT material decomposition values. We used intra-class correlation analysis, Pearson correlation and LASSO to stratify a robust and non-redundant feature subset. Independent train and test data were applied on a pool of four machine learning models. Performance and permutation-based feature importance was assessed to increase the interpretability and allow for comparison of the models. Top performing models were compared by the DeLong test. Results About 38% (19/50) and 36% (8/22) of the train and test set patients had abdominal lymphoma. Clearer entity clusters were seen in t-SNE plots using a combination of DECT and radiomics features compared to DECT features only. Top model performances of AUC = 0.763 (CI = 0.435–0.923) were achieved for the DECT cohort and AUC = 1.000 (CI = 1.000–1.000) for the radiomics feature cohort to stratify visually unequivocal lymphomatous lymph nodes. The performance of the radiomics model was significantly ( p  = 0.011, DeLong) superior to the DECT model. Conclusions Radiomics may have the potential to objectively stratify visually unequivocal nodal lymphoma versus benign lymph nodes. Radiomics seems superior to spectral DECT material decomposition in this use case. Therefore, artificial intelligence methodologies may not be restricted to centers with DECT equipment.
    Type of Medium: Online Resource
    ISSN: 1861-6429
    URL: Article
    DOI: 10.1007/s11548-023-02854-w
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 6
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    Comprehensive comparison of dual-energy computed tomography and magnetic resonance imaging for the assessment of bone marrow edema and fracture lines in acute vertebral fractures
    Springer Science and Business Media LLC ; 2022
    In:  European Radiology Vol. 32, No. 1 ( 2022-01), p. 561-571
    Details
    In: European Radiology, Springer Science and Business Media LLC, Vol. 32, No. 1 ( 2022-01), p. 561-571
    Abstract: To compare dual-energy CT (DECT) and MRI for assessing presence and extent of traumatic bone marrow edema (BME) and fracture line depiction in acute vertebral fractures. Methods Eighty-eight consecutive patients who underwent dual-source DECT and 3-T MRI of the spine were retrospectively analyzed. Five radiologists assessed all vertebrae for presence and extent of BME and for identification of acute fracture lines on MRI and, after 12 weeks, on DECT series. Additionally, image quality, image noise, and diagnostic confidence for overall diagnosis of acute vertebral fracture were assessed. Quantitative analysis of CT numbers was performed by a sixth radiologist. Two radiologists analyzed MRI and grayscale DECT series to define the reference standard. Results For assessing BME presence and extent, DECT showed high sensitivity (89% and 84%, respectively) and specificity (98% in both), and similarly high diagnostic confidence compared to MRI (2.30 vs. 2.32; range 0–3) for the detection of BME ( p = .72). For evaluating acute fracture lines, MRI achieved high specificity (95%), moderate sensitivity (76%), and a significantly lower diagnostic confidence compared to DECT (2.42 vs. 2.62, range 0–3) ( p 〈 .001). A cutoff value of − 0.43 HU provided a sensitivity of 89% and a specificity of 90% for diagnosing BME, with an overall AUC of 0.96. Conclusions DECT and MRI provide high diagnostic confidence and image quality for assessing acute vertebral fractures. While DECT achieved high overall diagnostic accuracy in the analysis of BME presence and extent, MRI provided moderate sensitivity and lower confidence for evaluating fracture lines. Key Points • In the setting of spinal trauma, dual-energy CT (DECT) is highly accurate in the evaluation of acute vertebral fractures and bone marrow edema presence and extent. • MRI provides moderate sensitivity and lower diagnostic confidence for the depiction of acute fracture lines, when compared to DECT, which might result in potentially inaccurate and underestimated severity assessment of injuries in certain cases when no fracture lines are visible on MRI. • DECT may represent a valid imaging alternative to MRI in specific settings of acute spinal trauma and in follow-up examinations, especially in elderly or unstable patients and in cases of subtle or complex orientated fracture lines.
    Type of Medium: Online Resource
    ISSN: 0938-7994 , 1432-1084
    URL: Article
    DOI: 10.1007/s00330-021-08081-8
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 7
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    Diagnostic accuracy of color-coded virtual noncalcium reconstructions derived from portal venous phase dual-energy CT in the assessment of lumbar disk herniation
    Springer Science and Business Media LLC ; 2022
    In:  European Radiology Vol. 32, No. 4 ( 2022-04), p. 2168-2177
    Details
    In: European Radiology, Springer Science and Business Media LLC, Vol. 32, No. 4 ( 2022-04), p. 2168-2177
    Abstract: To investigate the diagnostic accuracy of color-coded contrast-enhanced dual-energy CT virtual noncalcium (VNCa) reconstructions for the assessment of lumbar disk herniation compared to unenhanced VNCa imaging. Methods A total of 91 patients were retrospectively evaluated (65 years ± 16; 43 women) who had undergone third-generation dual-source dual-energy CT and 3.0-T MRI within an examination interval up to 3 weeks between November 2019 and December 2020. Eight weeks after assessing unenhanced color-coded VNCa reconstructions for the presence and degree of lumbar disk herniation, corresponding contrast-enhanced portal venous phase color-coded VNCa reconstructions were independently analyzed by the same five radiologists. MRI series were additionally analyzed by one highly experienced musculoskeletal radiologist and served as reference standard. Results MRI depicted 210 herniated lumbar disks in 91 patients. VNCa reconstructions derived from contrast-enhanced CT scans showed similar high overall sensitivity (93% vs 95%), specificity (94% vs 95%), and accuracy (94% vs 95%) for the assessment of lumbar disk herniation compared to unenhanced VNCa images (all p   〉  .05). Interrater agreement in VNCa imaging was excellent for both, unenhanced and contrast-enhanced CT ( κ  = 0.84 vs κ  = 0.86; p   〉  .05). Moreover, ratings for diagnostic confidence, image quality, and noise differed not significantly between unenhanced and contrast-enhanced VNCa series (all p   〉  .05). Conclusions Color-coded VNCa reconstructions derived from contrast-enhanced dual-energy CT yield similar diagnostic accuracy for the depiction of lumbar disk herniation compared to unenhanced VNCa imaging and therefore may improve opportunistic retrospective lumbar disk herniation assessment, particularly in case of staging CT examinations. Key Points • Color-coded dual-source dual-energy CT virtual noncalcium (VNCa) reconstructions derived from portal venous phase yield similar high diagnostic accuracy for the assessment of lumbar disk herniation compared to unenhanced VNCa CT series (94% vs 95%) with MRI serving as a standard of reference. • Diagnostic confidence, image quality, and noise levels differ not significantly between unenhanced and contrast-enhanced portal venous phase VNCa dual-energy CT series. • Dual-source dual-energy CT might have the potential to improve opportunistic retrospective lumbar disk herniation assessment in CT examinations performed for other indications through reconstruction of VNCa images.
    Type of Medium: Online Resource
    ISSN: 0938-7994 , 1432-1084
    URL: Article
    DOI: 10.1007/s00330-021-08354-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 8
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    Potential of high dimensional radiomic features to assess blood components in intraaortic vessels in non-contrast CT scans
    Springer Science and Business Media LLC ; 2021
    In:  BMC Medical Imaging Vol. 21, No. 1 ( 2021-12)
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    In: BMC Medical Imaging, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2021-12)
    Abstract: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans. Methods One hundred patients (median age, 69 years; range, 19–94 years) who received CT scans of the thoracolumbar spine and blood-testing for hemoglobin and hematocrit levels ± 24 h between 08/2018 and 11/2019 were retrospectively included. Intraaortic blood was segmented using a spherical volume of interest of 1 cm diameter with consecutive radiomic analysis applying PyRadiomics software. Feature selection was performed applying analysis of correlation and collinearity. The final feature set was obtained to differentiate moderate-to-severe anemia. Random forest machine learning was applied and predictive performance was assessed. A decision-tree was obtained to propose a cut-off value of CT Hounsfield units (HU). Results High correlation with hemoglobin and hematocrit levels was shown for first-order radiomic features ( p   〈  0.001 to p  = 0.032). The top 3 features showed high correlation to hemoglobin values ( p ) and minimal collinearity (r) to the top ranked feature Median ( p   〈  0.001), Energy ( p  = 0.002, r = 0.387), Minimum ( p  = 0.032, r = 0.437). Median ( p   〈  0.001) and Minimum ( p  = 0.003) differed in moderate-to-severe anemia compared to non-anemic state. Median yielded superiority to the combination of Median and Minimum ( p (AUC) = 0.015, p (precision) = 0.017, p (accuracy) = 0.612) in the predictive performance employing random forest analysis. A Median HU value ≤ 36.5 indicated moderate-to-severe anemia (accuracy = 0.90, precision = 0.80). Conclusions First-order radiomic features correlate with hemoglobin levels and may be feasible for the prediction of moderate-to-severe anemia. High dimensional radiomic features did not aid augmenting the data in our exemplary use case of intraluminal blood component assessment. Trial registration Retrospectively registered.
    Type of Medium: Online Resource
    ISSN: 1471-2342
    URL: Article
    DOI: 10.1186/s12880-021-00654-9
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 9
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    CT-radiomics and clinical risk scores for response and overall survival prognostication in TACE HCC patients
    Springer Science and Business Media LLC ; 2023
    In:  Scientific Reports Vol. 13, No. 1 ( 2023-01-11)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2023-01-11)
    Abstract: We aimed to identify hepatocellular carcinoma (HCC) patients who will respond to repetitive transarterial chemoembolization (TACE) to improve the treatment algorithm. Retrospectively, 61 patients (mean age, 65.3 years ± 10.0 [SD]; 49 men) with 94 HCC mRECIST target-lesions who had three consecutive TACE between 01/2012 and 01/2020 were included. Robust and non-redundant radiomics features were extracted from the 24 h post-embolization CT. Five different clinical TACE-scores were assessed. Seven different feature selection methods and machine learning models were used. Radiomics, clinical and combined models were built to predict response to TACE on a lesion-wise and patient-wise level as well as its impact on overall-survival prognostication. 29 target-lesions of 19 patients were evaluated in the test set. Response rates were 37.9% (11/29) on the lesion-level and 42.1% (8/19) on the patient-level. Radiomics top lesion-wise response prognostications was AUC 0.55–0.67. Clinical scores revealed top AUCs of 0.65–0.69. The best working model combined the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical score mHAP_II_score_group with AUC = 0.70, accuracy = 0.72. We transferred this model on a patient-level to achieve AUC = 0.62, CI = 0.41–0.83. The two radiomics-clinical features revealed overall-survival prognostication of C-index = 0.67. In conclusion, a random forest model using the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical mHAP-II-score-group seems promising for TACE response prognostication.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-023-27714-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2615211-3
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  • 10
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    Radiomics for therapy-specific head and neck squamous cell carcinoma survival prognostication (part I)
    Springer Science and Business Media LLC ; 2023
    In:  BMC Medical Imaging Vol. 23, No. 1 ( 2023-06-02)
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    In: BMC Medical Imaging, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2023-06-02)
    Abstract: Treatment plans for squamous cell carcinoma of the head and neck (SCCHN) are individually decided in tumor board meetings but some treatment decision-steps lack objective prognostic estimates. Our purpose was to explore the potential of radiomics for SCCHN therapy-specific survival prognostication and to increase the models’ interpretability by ranking the features based on their predictive importance. Methods We included 157 SCCHN patients (male, 119; female, 38; mean age, 64.39 ± 10.71 years) with baseline head and neck CT between 09/2014 and 08/2020 in this retrospective study. Patients were stratified according to their treatment. Using independent training and test datasets with cross-validation and 100 iterations, we identified, ranked and inter-correlated prognostic signatures using elastic net (EN) and random survival forest (RSF). We benchmarked the models against clinical parameters. Inter-reader variation was analyzed using intraclass-correlation coefficients (ICC). Results EN and RSF achieved top prognostication performances of AUC = 0.795 (95% CI 0.767–0.822) and AUC = 0.811 (95% CI 0.782–0.839). RSF prognostication slightly outperformed the EN for the complete (ΔAUC 0.035, p  = 0.002) and radiochemotherapy (ΔAUC 0.092, p   〈  0.001) cohort. RSF was superior to most clinical benchmarking ( p  ≤ 0.006). The inter-reader correlation was moderate or high for all features classes (ICC ≥ 0.77 (± 0.19)). Shape features had the highest prognostic importance, followed by texture features. Conclusions EN and RSF built on radiomics features may be used for survival prognostication. The prognostically leading features may vary between treatment subgroups. This warrants further validation to potentially aid clinical treatment decision making in the future.
    Type of Medium: Online Resource
    ISSN: 1471-2342
    URL: Article
    DOI: 10.1186/s12880-023-01034-1
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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