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Book ; Thesis: Vergleich der organspezifischen Strahlendosen von zwei dynamischen Volumenperfusions CT Protokollen mit einem triphasischen Routineprotokoll des Abdomens

Gawlitza, Joshua Felix Michael / Henzler, Thomas

2018

Institution	Universität Heidelberg
Author's details	vorgelegt von Joshua Felix Michael Gawlitza
Language	German
Size	63 Blätter, Illustrationen, Diagramme, 30 cm
Publishing place	Heidelberg
Publishing country	Germany
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Dissertation, Ruprecht-Karls-Universität zu Heidelberg, 2018
HBZ-ID	HT020128203
Database	Catalogue ZB MED Medicine, Health

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Article ; Online: Evaluating Treatment Response in GEJ Adenocarcinoma: The Role of Pretherapeutic and Posttherapeutic Iodine Mapping.

Graf, Markus / Gawlitza, Joshua / Makowski, Marcus / Meurer, Felix / Huber, Thomas / Ziegelmayer, Sebastian

Investigative radiology

2024

Abstract: Background: Neoadjuvant therapy regimens have significantly improved the prognosis of GEJ (gastroesophageal junction) cancer; however, there are a significant percentage of patients who benefit from earlier resection or adapted therapy regimens, and the ...

Abstract	Background: Neoadjuvant therapy regimens have significantly improved the prognosis of GEJ (gastroesophageal junction) cancer; however, there are a significant percentage of patients who benefit from earlier resection or adapted therapy regimens, and the true response rate can only be determined histopathologically. Methods that allow preoperative assessment of response are lacking. Purpose: The purpose of this retrospective study is to assess the potential of pretherapeutic and posttherapeutic spectral CT iodine density (IoD) in predicting histopathological response to neoadjuvant chemotherapy in patients diagnosed with adenocarcinoma of the GEJ. Methods: In this retrospective cohort study, a total of 62 patients with GEJ carcinoma were studied. Patients received a multiphasic CT scan at diagnosis and preoperatively. Iodine-density maps were generated based on spectral CT data. All tumors were histopathologically analyzed, and the tumor regression grade (TRG) according to Becker et al ( Cancer . 2003;98:1521-1530) was determined. Two experienced radiologists blindly placed 5 defined ROIs in the tumor region of highest density, and the maximum value was used for further analysis. Iodine density was normalized to the aortic iodine uptake. In addition, tumor response was assessed according to standard RECIST measurement. After assessing interrater reliability, the correlation of IoD values with treatment response and with histopathologic TRG was evaluated. Results: The normalized ΔIoD (IoD at diagnosis - IoD after neoadjuvant treatment) and the normalized IoD after neoadjuvant treatment correlated significantly with the TRG. For the detection of responders and nonresponders, the receiver operating characteristic (ROC) curve for normalized ΔIoD yielded the highest area under the curve of 0.95 and achieved a sensitivity and specificity of 92.3% and 92.1%, respectively. Iodine density after neoadjuvant treatment achieved an area under the curve of 0.88 and a sensitivity and specificity of 86.8% and 84.6%, respectively (cutoff, 0.266). Iodine density at diagnosis and RECIST did not provide information to distinguish responders from nonresponders. Using the cutoff value for IoD after neoadjuvant treatment, a reliable classification of responders and nonresponders was achieved for both readers in a test set of 11 patients. Intraclass correlation coefficient revealed excellent interrater reliability (intraclass correlation coefficient, >0.9). Lastly, using the cutoff value for normalized ΔIoD as a definition for treatment response, a significantly longer survival of responders was shown. Conclusions: Changes in IoD after neoadjuvant treatment of GEJ cancer may be a potential surrogate for therapy response.
Language	English
Publishing date	2024-01-30
Publishing country	United States
Document type	Journal Article
ZDB-ID	80345-5
ISSN	1536-0210 ; 0020-9996
ISSN (online)	1536-0210
ISSN	0020-9996
DOI	10.1097/RLI.0000000000001064
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Article: Cost-Effectiveness of Artificial Intelligence Support in Computed Tomography-Based Lung Cancer Screening.

Ziegelmayer, Sebastian / Graf, Markus / Makowski, Marcus / Gawlitza, Joshua / Gassert, Felix

Cancers

2022 Volume 14, Issue 7

Abstract: Background: Lung cancer screening is already implemented in the USA and strongly recommended by European Radiological and Thoracic societies as well. Upon implementation, the total number of thoracic computed tomographies (CT) is likely to rise ... ...

Abstract	Background: Lung cancer screening is already implemented in the USA and strongly recommended by European Radiological and Thoracic societies as well. Upon implementation, the total number of thoracic computed tomographies (CT) is likely to rise significantly. As shown in previous studies, modern artificial intelligence-based algorithms are on-par or even exceed radiologist's performance in lung nodule detection and classification. Therefore, the aim of this study was to evaluate the cost-effectiveness of an AI-based system in the context of baseline lung cancer screening. Methods: In this retrospective study, a decision model based on Markov simulation was developed to estimate the quality-adjusted life-years (QALYs) and lifetime costs of the diagnostic modalities. Literature research was performed to determine model input parameters. Model uncertainty and possible costs of the AI-system were assessed using deterministic and probabilistic sensitivity analysis. Results: In the base case scenario CT + AI resulted in a negative incremental cost-effectiveness ratio (ICER) as compared to CT only, showing lower costs and higher effectiveness. Threshold analysis showed that the ICER remained negative up to a threshold of USD 68 for the AI support. The willingness-to-pay of USD 100,000 was crossed at a value of USD 1240. Deterministic and probabilistic sensitivity analysis showed model robustness for varying input parameters. Conclusion: Based on our results, the use of an AI-based system in the initial low-dose CT scan of lung cancer screening is a feasible diagnostic strategy from a cost-effectiveness perspective.
Language	English
Publishing date	2022-03-29
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers14071729
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Article: Comparison of Virtual Non-Contrast and True Non-Contrast CT Images Obtained by Dual-Layer Spectral CT in COPD Patients.

Steinhardt, Manuel / Marka, Alexander W / Ziegelmayer, Sebastian / Makowski, Marcus / Braren, Rickmer / Graf, Markus / Gawlitza, Joshua

Bioengineering (Basel, Switzerland)

2024 Volume 11, Issue 4

Abstract: Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death. Recent studies have underlined the importance of non-contrast-enhanced chest CT scans not only for emphysema progression quantification, but for correlation with clinical ...

Abstract	Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death. Recent studies have underlined the importance of non-contrast-enhanced chest CT scans not only for emphysema progression quantification, but for correlation with clinical outcomes as well. As about 40 percent of the 300 million CT scans per year are contrast-enhanced, no proper emphysema quantification is available in a one-stop-shop approach for patients with known or newly diagnosed COPD. Since the introduction of spectral imaging (e.g., dual-energy CT scanners), it has been possible to create virtual non-contrast-enhanced images (VNC) from contrast-enhanced images, making it theoretically possible to offer proper COPD imaging despite contrast enhancing. This study is aimed towards investigating whether these VNC images are comparable to true non-contrast-enhanced images (TNC), thereby reducing the radiation exposure of patients and usage of resources in hospitals. In total, 100 COPD patients with two scans, one with (VNC) and one without contrast media (TNC), within 8 weeks or less obtained by a spectral CT using dual-layer technology, were included in this retrospective study. TNC and VNC were compared according to their voxel-density histograms. While the comparison showed significant differences in the low attenuated volumes (LAVs) of TNC and VNC regarding the emphysema threshold of -950 Houndsfield Units (HU), the 15th and 10th percentiles of the LAVs used as a proxy for pre-emphysema were comparable. Upon further investigation, the threshold-based LAVs (-950 HU) of TNC and VNC were comparable in patients with a water equivalent diameter (DW) below 270 mm. The study concludes that VNC imaging may be a viable option for assessing emphysema progression in COPD patients, particularly those with a normal body mass index (BMI). Further, pre-emphysema was generally comparable between TNC and VNC. This approach could potentially reduce radiation exposure and hospital resources by making additional TNC scans obsolete.
Language	English
Publishing date	2024-03-22
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2746191-9
ISSN	2306-5354
ISSN	2306-5354
DOI	10.3390/bioengineering11040301
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Article ; Online: Immunohistochemistry Reveals TRPC Channels in the Human Hearing Organ-A Novel CT-Guided Approach to the Cochlea.

Englisch, Colya N / Steinhäuser, Jakob / Wemmert, Silke / Jung, Martin / Gawlitza, Joshua / Wenzel, Gentiana / Schick, Bernhard / Tschernig, Thomas

International journal of molecular sciences

2023 Volume 24, Issue 11

Abstract: TRPC channels are critical players in cochlear hair cells and sensory neurons, as demonstrated in animal experiments. However, evidence for TRPC expression in the human cochlea is still lacking. This reflects the logistic and practical difficulties in ... ...

Abstract	TRPC channels are critical players in cochlear hair cells and sensory neurons, as demonstrated in animal experiments. However, evidence for TRPC expression in the human cochlea is still lacking. This reflects the logistic and practical difficulties in obtaining human cochleae. The purpose of this study was to detect TRPC6, TRPC5 and TRPC3 in the human cochlea. Temporal bone pairs were excised from ten body donors, and the inner ear was first assessed based on computed tomography scans. Decalcification was then performed using 20% EDTA solutions. Immunohistochemistry with knockout-tested antibodies followed. The organ of Corti, the stria vascularis, the spiral lamina, spiral ganglion neurons and cochlear nerves were specifically stained. This unique report of TRPC channels in the human cochlea supports the hypothesis of the potentially critical role of TRPC channels in human cochlear health and disease which has been suggested in previous rodent experiments.
MeSH term(s)	Animals ; Humans ; Immunohistochemistry ; Cochlea/metabolism ; Ear, Inner/metabolism ; Stria Vascularis/metabolism ; Hearing
Language	English
Publishing date	2023-05-26
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2019364-6
ISSN	1422-0067 ; 1422-0067 ; 1661-6596
ISSN (online)	1422-0067
ISSN	1422-0067 ; 1661-6596
DOI	10.3390/ijms24119290
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Article ; Online: Machine learning assisted feature identification and prediction of hemodynamic endpoints using computed tomography in patients with CTEPH.

Gawlitza, Joshua / Endres, Sophie / Fries, Peter / Graf, Markus / Wilkens, Heinrike / Stroeder, Jonas / Buecker, Arno / Massmann, Alexander / Ziegelmayer, Sebastian

The international journal of cardiovascular imaging

2023 Volume 40, Issue 3, Page(s) 569–577

Abstract: Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare but potentially curable cause of pulmonary hypertension (PH). Currently PH is diagnosed by right heart catheterisation. Computed tomography (CT) is used for ruling out other causes and ... ...

Abstract	Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare but potentially curable cause of pulmonary hypertension (PH). Currently PH is diagnosed by right heart catheterisation. Computed tomography (CT) is used for ruling out other causes and operative planning. This study aims to evaluate importance of different quantitative/qualitative imaging features and develop a supervised machine learning (ML) model to predict hemodynamic risk groups. 127 Patients with diagnosed CTEPH who received preoperative right heart catheterization and thoracic CTA examinations (39 ECG-gated; 88 non-ECG gated) were included. 19 qualitative/quantitative imaging features and 3 hemodynamic parameters [mean pulmonary artery pressure, right atrial pressure (RAP), pulmonary artery oxygen saturation (PA SaO2)] were gathered. Diameter-based CT features were measured in axial and adjusted multiplane reconstructions (MPR). Univariate analysis was performed for qualitative and quantitative features. A random forest algorithm was trained on imaging features to predict hemodynamic risk groups. Feature importance was calculated for all models. Qualitative and quantitative parameters showed no significant differences between ECG and non-ECG gated CTs. Depending on reconstruction plane, five quantitative features were significantly different, but mean absolute difference between parameters (MPR vs. axial) was 0.3 mm with no difference in correlation with hemodynamic parameters. Univariate analysis showed moderate to strong correlation for multiple imaging features with hemodynamic parameters. The model achieved an AUC score of 0.82 for the mPAP based risk stratification and 0.74 for the PA SaO2 risk stratification. Contrast agent retention in hepatic vein, mosaic attenuation pattern and the ratio right atrium/left ventricle were the most important features among other parameters. Quantitative and qualitative imaging features of reconstructions correlate with hemodynamic parameters in preoperative CTEPH patients-regardless of MPR adaption. Machine learning based analysis of preoperative imaging features can be used for non-invasive risk stratification. Qualitative features seem to be more important than previously anticipated.
MeSH term(s)	Humans ; Hypertension, Pulmonary ; Pulmonary Embolism/complications ; Pulmonary Embolism/diagnostic imaging ; Predictive Value of Tests ; Tomography, X-Ray Computed/methods ; Hemodynamics ; Machine Learning ; Chronic Disease
Language	English
Publishing date	2023-12-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	2055311-0
ISSN	1875-8312 ; 1573-0743 ; 1569-5794 ; 0167-9899
ISSN (online)	1875-8312 ; 1573-0743
ISSN	1569-5794 ; 0167-9899
DOI	10.1007/s10554-023-03026-2
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Article ; Online: Time is bone - Quantitative comparison of decalcification solvents in human femur samples using dual-X-ray-absorptiometry and computed tomography.

Gawlitza, Joshua / Steinhäuser, Jakob / Bücker, Arno / Krasteva-Christ, Gabriela / Tschernig, Thomas

Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft

2021 Volume 235, Page(s) 151696

Abstract: Introduction: Bone decalcification is a necessary preprocessing step in histological and anatomical studies. Several solutions for decalcification with different claimed times for full decalcification are commercially available. Current literature lacks ...

Abstract	Introduction: Bone decalcification is a necessary preprocessing step in histological and anatomical studies. Several solutions for decalcification with different claimed times for full decalcification are commercially available. Current literature lacks direct, quantitative measurement of calcium hydrocyapatite degradation during decalcification to compare different solutions. Therefore, the aim of this study was to test the performance of three different decalcification solutions in human bone by direct measurement of calcium hydroxyapatite using dual-X-ray-absorptiometry (DEXA) and volumetric computed tomography (CT). Methods: Four femur slices were acquired from the proximal femur of a 76-year-old body donor. The slices were submerged in formaldehyde (control), EDTA, Osteosoft (Merck, Darmstadt, Germany) and "Rapid Bone Decalcifier" (RBD) (American MasterTech Scientific, Lodi, USA). Consecutive DEXA and CT scans were performed at 2 h, 4 h, 8 h, 11 h, 20 h, 44 h and 77 h after solutions were added. Besides the calcium hydroxyapatite concentration, the bone volume was measured each time. Results: Fastest decline in volume was seen in the RBD probe. Further, RBD was the only solution, being able to fully decalcify the bone slice after 77 h. Although a steady decline in volume and hydroxyapatite concentration was seen for EDTA and Osteosoft as well, both were not able to decalcify the slices. Conclusion: Overall, the purely qualititve acquired literature data on bone decalcifiers was verified by our quantitative data for human, cortical-rich bones. Hydrochloric-acid based solutions seem to be preferable in order to rapidly dissolve the calcium hydroxyapatite.
MeSH term(s)	Absorptiometry, Photon ; Aged ; Bone Density ; Bone and Bones ; Femur/diagnostic imaging ; Humans ; Solvents ; Tomography, X-Ray Computed ; X-Rays
Chemical Substances	Solvents
Language	English
Publishing date	2021-02-08
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1106738-x
ISSN	1618-0402 ; 0940-9602
ISSN (online)	1618-0402
ISSN	0940-9602
DOI	10.1016/j.aanat.2021.151696
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Article ; Online: Feature Robustness and Diagnostic Capabilities of Convolutional Neural Networks Against Radiomics Features in Computed Tomography Imaging.

Ziegelmayer, Sebastian / Reischl, Stefan / Harder, Felix / Makowski, Marcus / Braren, Rickmer / Gawlitza, Joshua

Investigative radiology

2021 Volume 57, Issue 3, Page(s) 171–177

Abstract: Materials and methods: Imaging phantoms were scanned twice on 3 computed tomography scanners from 2 different manufactures with varying tube voltages and currents. Phantoms were segmented, and features were extracted using PyRadiomics and a pretrained ... ...

Abstract	Materials and methods: Imaging phantoms were scanned twice on 3 computed tomography scanners from 2 different manufactures with varying tube voltages and currents. Phantoms were segmented, and features were extracted using PyRadiomics and a pretrained CNN. After standardization the concordance correlation coefficient (CCC), mean feature variance, feature range, and the coefficient of variant were calculated to assess feature robustness. In addition, the cosine similarity was calculated for the vectorized activation maps for an exemplary phantom. For the in vivo comparison, the radiomics and CNN features of 30 patients with hepatocellular carcinoma (HCC) and 30 patients with hepatic colon carcinoma metastasis were compared. Results: In total, 851 radiomics features and 256 CNN features were extracted for each phantom. For all phantoms, the global CCC of the CNN features was above 98%, whereas the highest CCC for the radiomics features was 36%. The mean feature variance and feature range was significantly lower for the CNN features. Using a coefficient of variant ≤0.2 as a threshold to define robust features and averaging across all phantoms 346 of 851 (41%) radiomics features and 196 of 256 (77%) CNN features were found to be robust. The cosine similarity was greater than 0.98 for all scanner and parameter variations. In the retrospective analysis, 122 of the 256 CNN (49%) features showed significant differences between HCC and hepatic colon metastasis. Discussion: Convolutional neural network features were more stable compared with radiomics features against technical variations. Moreover, the possibility of tumor entity differentiation based on CNN features was shown. Combined with visualization methods, CNN features are expected to increase reproducibility of quantitative image representations. Further studies are warranted to investigate the impact of feature stability on radiological image-based prediction of clinical outcomes.
MeSH term(s)	Carcinoma, Hepatocellular/diagnostic imaging ; Humans ; Liver Neoplasms/diagnostic imaging ; Neural Networks, Computer ; Phantoms, Imaging ; Reproducibility of Results ; Retrospective Studies ; Tomography, X-Ray Computed/methods
Language	English
Publishing date	2021-09-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	80345-5
ISSN	1536-0210 ; 0020-9996
ISSN (online)	1536-0210
ISSN	0020-9996
DOI	10.1097/RLI.0000000000000827
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Zs.A 734: Show issues

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Article ; Online: Beyond the d-dimer - Machine-learning assisted pre-test probability evaluation in patients with suspected pulmonary embolism and elevated d-dimers.

Gawlitza, Joshua / Ziegelmayer, Sebastian / Wilkens, Heinrike / Jagoda, Philippe / Raczeck, Paul / Buecker, Arno / Stroeder, Jonas

Thrombosis research

2021 Volume 205, Page(s) 11–16

Abstract: Introduction: Acute pulmonary embolism (PE) is a leading cardiovascular cause of death, resembling a common indication for emergency computed tomography (CT). Nonetheless, in clinical routine most CTs performed for suspicion of PE excluded the suspected ...

Abstract	Introduction: Acute pulmonary embolism (PE) is a leading cardiovascular cause of death, resembling a common indication for emergency computed tomography (CT). Nonetheless, in clinical routine most CTs performed for suspicion of PE excluded the suspected diagnosis. As patients with low to intermediate risk for PE are triaged according to the d-dimer, its relatively low specifity and widespread elevation among elderly might be an underlying issue. Aim of this study was to find potential predictors based on initial emergency blood tests in patients with elevated d-dimers and suspected PE to further increase pre-test probability. Methods: In this retrospective study all patients at the local university hospital's emergency room from 2009 to 2019 with suspected PE, emergency blood testing and CT were included. Cluster analysis was performed to separate groups with distinct laboratory parameter profiles and PE frequencies were compared. Machine learning algorithms were trained on the groups to predict individual PE probability based on emergency laboratory parameters. Results: Overall, PE frequency among the 2045 analyzed patients was 41%. Three clusters with significant differences (p ≤ 0.05) in PE frequency were identified: C1 showed a PE frequency of 43%, C2 40% and C3 33%. Laboratory parameter profiles (e.g. creatinine) differed significantly between clusters (p ≤ 0.0001). Both logistic regression and support-vector machines were able to predict clusters with an accuracy of over 90%. Discussion: Initial blood parameters seem to enable further differentiation of patients with suspected PE and elevated d-dimers to raise pre-test probability of PE. Machine-learning-based prediction models might help to further narrow down CT indications in the future.
MeSH term(s)	Aged ; Fibrin Fibrinogen Degradation Products ; Humans ; Machine Learning ; Probability ; Pulmonary Embolism/diagnosis ; Retrospective Studies
Chemical Substances	Fibrin Fibrinogen Degradation Products ; fibrin fragment D
Language	English
Publishing date	2021-07-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	121852-9
ISSN	1879-2472 ; 0049-3848
ISSN (online)	1879-2472
ISSN	0049-3848
DOI	10.1016/j.thromres.2021.07.001
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Article: CT Attenuation of Hepatic Pancreatic Cancer Metastases Correlates with Prognostically Detrimental Metastatic Necrosis.

Reischl, Stefan / Ziegelmayer, Sebastian / Graf, Markus / Gawlitza, Joshua / Sauter, Andreas Philipp / Steinhardt, Manuel / Weber, Marie-Christin / Neumann, Philipp-Alexander / Makowski, Marcus Richard / Lohöfer, Fabian Karl / Mogler, Carolin / Braren, Rickmer Früdd

Journal of clinical medicine

2023 Volume 12, Issue 23

Abstract: Percutaneous CT-guided biopsy is a frequently performed procedure for the confirmation and molecular workup of hepatic metastases of pancreatic ductal adenocarcinoma (PDAC). Tumor necrosis of primary PDAC has shown a negative prognostic impact in recent ... ...

Abstract	Percutaneous CT-guided biopsy is a frequently performed procedure for the confirmation and molecular workup of hepatic metastases of pancreatic ductal adenocarcinoma (PDAC). Tumor necrosis of primary PDAC has shown a negative prognostic impact in recent studies. This study aims to examine predictability in CT scans and the prognostic impact of necrosis in hepatic metastases of PDAC. In this tertiary-center retrospective cohort study, we included 36 patients with hepatic metastases of PDAC who underwent CT-guided hepatic biopsies. Normalized attenuation of the biopsied metastasis was determined in venous phase contrast-enhanced planning scans obtained prior to biopsy by automatic, threshold-based 3D segmentation and manual, blinded 2D segmentation. A board-certified pathologist specialized in hepatic pathology histologically quantified the tumor necrosis and cellularity of the biopsy cylinders. We found a significant inverse-linear correlation between normalized attenuation and the fraction of necrosis (Pearson's r = 0.51,
Language	English
Publishing date	2023-11-26
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662592-1
ISSN	2077-0383
ISSN	2077-0383
DOI	10.3390/jcm12237319
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