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Institute
- Institut für diagnostische und interventionelle Radiologie (Institut für Röntgendiagnostik) (29) (remove)
Es wurden Perfusionsmessungen mittels MRT an Infarktpatienten im Akutstadium und im Langzeitverlauf durchgeführt und quantitativ mittels einem Sektormodell ausgewertet. Hierbei zeigte sich, dass sich die Perfusionswerte im Infarktareal und gesunden Myokard nicht signifikant unterschieden und dass sich diese auch im Jahresverlauf nicht signifikant änderten. Es ergab sich auch keine signifikante Korrelation zwischen der Größe des Infarkareales und den gemessenen Perfusionswerten.
In der vorliegenden Arbeit wurde untersucht, ob die farbige DSA-Darstellungsweise besser als die monochromatische dazu geeignet ist, eine Entscheidung über eine mögliche Stentimplantation bei pAVK zu treffen.
Hierfür wurden DSA-Daten des Universitätsklinikums Würzburg im Zeitraum 04/2014 - 10/2015 retrospektiv ausgewertet. Drei Ärzte bewerteten die Bilder in zwei getrennten Durchgängen bezüglich ihrer Entscheidung zur Stentimplantation. Diese Entscheidungen wurden mit einem Konsensus aus 2 Ärzten verglichen. Anhand von ROC-Analysen konnte so die Treffsicherheit der Entscheidungen evaluiert werden.
In der Studie stellte sich die farbkodierte Darstellung im Vergleich zur monochromatischen Darstellung nicht als überlegen heraus.
Purpose
Artificial neural networks show promising performance in automatic segmentation of cardiac MRI. However, training requires large amounts of annotated data and generalization to different vendors, field strengths, sequence parameters, and pathologies is limited. Transfer learning addresses this challenge, but specific recommendations regarding type and amount of data required is lacking. In this study, we assess data requirements for transfer learning to experimental cardiac MRI at 7T where the segmentation task can be challenging. In addition, we provide guidelines, tools, and annotated data to enable transfer learning approaches by other researchers and clinicians.
Methods
A publicly available segmentation model was used to annotate a publicly available data set. This labeled data set was subsequently used to train a neural network for segmentation of left ventricle and myocardium in cardiac cine MRI. The network is used as starting point for transfer learning to 7T cine data of healthy volunteers (n = 22; 7873 images) by updating the pre-trained weights. Structured and random data subsets of different sizes were used to systematically assess data requirements for successful transfer learning.
Results
Inconsistencies in the publically available data set were corrected, labels created, and a neural network trained. On 7T cardiac cine images the model pre-trained on public imaging data, acquired at 1.5T and 3T, achieved DICE\(_{LV}\) = 0.835 and DICE\(_{MY}\) = 0.670. Transfer learning using 7T cine data and ImageNet weight initialization improved model performance to DICE\(_{LV}\) = 0.900 and DICE\(_{MY}\) = 0.791. Using only end-systolic and end-diastolic images reduced training data by 90%, with no negative impact on segmentation performance (DICE\(_{LV}\) = 0.908, DICE\(_{MY}\) = 0.805).
Conclusions
This work demonstrates and quantifies the benefits of transfer learning for cardiac cine image segmentation. We provide practical guidelines for researchers planning transfer learning projects in cardiac MRI and make data, models, and code publicly available.
Morbidität und Mortalität der Lebererkrankung im Rahmen der Cystischen Fiborse (Cystic fibrosis liver disease, CFLD) sind vornehmlich von Ausmaß und Progredienz der Leberfibrose abhängig. Aufgrund der fehlenden Genauigkeit der bisherigen diagnostischen Verfahren werden viele der an CF erkrankten Menschen erst in fortgeschrittenen Stadien diagnostiziert. Schwere Komplikationen einer Leberzirrhose treten häufig bereits im Kindesalter auf. Die Quantitative Sonoelastographie, hier die Acoustic Radiation Force Impulse (ARFI)-Elastographie, ist ein vielversprechendes, nicht-invasives und strahlenfreies Verfahren zur Messung der Gewebesteifigkeit.
Anhand dieser retrospektiven, monozentrischen Studie soll die ARFI-Elastographie im Hinblick auf den klinischen Einsatz bei der CFLD-Diagnostik untersucht werden. Es wurde eruiert, ob sich mittels ARFI-Elastographie Rückschlüsse auf eine CFLD und deren Schweregrade ziehen lassen.
Hierfür wurden die ARFI-Messungen verschiedener Lebersegmente von 62 an CF erkrankten und 19 lebergesunden Kindern und Jugendlichen verglichen. Zudem erfolgte die Korrelation der Ergebnisse mit zwei etablierten klinischen Leberfibrose-Scores (APRI, Williams-Score).
Im Patientenkollektiv konnten tendenziell erhöhte Scherwellengeschwindigkeiten, entsprechend einer fibrotischen Aktivität, gemessen werden. Die transkostale Messposition in Segment VII/VIII (TC VII/VIII) erwies sich als zuverlässigste Position zur Differenzierung zwischen einer CF-Hepatopathie und einem gesunden Leberparenchym. Hingegen war das Errechnen von Cut-off Werten zur Graduierung von Fibrosestadien nicht möglich. Auch war keine Korrelation zu Leberfiborsescores feststellbar.
Insgesamt zeigt sich, dass die Diagnosestellung einer CFLD aktuell nur in Kombination mit bisherigen Messmethoden wie der klinischen Untersuchung, der Laboranalytik und der Sonographie möglich ist. Die Interpretation der ARFI-cut-off Werte bleibt aufgrund mangelnder Sensitivität und Spezifität und vor dem Hintergrund der CF-typischen heterogenen Leberpathologie erschwert. Die ARFI-Elastographie kann als zusätzlicher Baustein in der Diagnostik der CFLD, bei unklaren Befundkonstellationen oder zum Therapie-Monitoring herangezogen werden. Um einen klaren klinischen Einsatz in der Routinediagnostik zu definieren bedarf es weiterer großer, multizentrischer und prospektiver Studien.
Es wurde die diagnostische Genauigkeit fünf verschiedener Rekonstruktionsalgorithmen der DE-CTA der Becken-Bein-Gefäße von Patienten mit pAVK an einem Dual-Source CT mit dem diagnostischen Goldstandard der DSA verglichen. Die DE-CTA zeigte eine exzellente Sensitivität an Becken- und Beingefäßen hinsichtlich einer korrekten Stenosegraduierung, unabhängig von der Rekonstruktion. Die Standard MPR zeigte insgesamt die besten Ergebnisse und ist deshalb vor allem in nicht eindeutigen Fällen die Methode der Wahl. Die Auswertung von DE-CS MPRs, DE-CS MIPs, gekrümmten MPRs oder die semi-automatische quantitative Stenosegradauswertung bringt keinen Zugewinn an diagnostischer Performance im Vergleich zur visuellen Auswertung der Standard MPR. Das Ausmaß der Gefäßwandverkalkungen und die intraluminale Kontrastierung hatten keinen signifikanten Effekt auf die Sensitivität zur Erkennung signifikanter Stenosen an den Becken- und Beingefäßen. Jedoch verschlechterten sich die Spezifität und die Genauigkeit der Rekonstruktionen, welche auf der DE-Knochen- und DE-Plaqueentfernung basieren, signifikant in stark verkalkten oder nur schwach kontrastierten Gefäßsegmenten. Beim Auswerten von DE-CS Rekonstruktionen ist infolgedessen vor allem in schlecht kontrastierten oder stark verkalkten Gefäßen eine weitere Verifizierung des Befundes nötig, um unnötige invasive DSAs als Folge von falsch positiven CTA-Befunden zu reduzieren.
Das Ziel dieser Arbeit war herauszufinden, ob der iFlow-Algorithmus als zusätzlicher Parameter zu Evaluierung des technischen Erfolgs einer Revaskularisation einer Nierenarterienstenose eingesetzt werden kann. Hierfür haben wir die „mean time to peak“ in Sekunden in den farbcodierten Bildern gemessen, um den Effekt einer Stentimplantation auf den Blutfluss zu eruieren. Im Verlauf haben wir dann getestet, ob unsere Ergebnisse den klinischen Verlauf unserer Patienten wiederspiegeln, um feststellen zu können, ob die syngo iFlow-Software den Erfolg der endovaskulären Therapie voraussagen kann.
Purpose
To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy.
Methods
In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework (“nnU-net”) was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels.
Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the Sørensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson’s r correlation and Bland-Altman analysis.
Results
The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC: 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network.
Conclusion
The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.
Objectives
Trauma evaluation of extremities can be challenging in conventional radiography. A multi-use x-ray system with cone-beam CT (CBCT) option facilitates ancillary 3-D imaging without repositioning. We assessed the clinical value of CBCT scans by analyzing the influence of additional findings on therapy.
Methods
Ninety-two patients underwent radiography and subsequent CBCT imaging with the twin robotic scanner (76 wrist/hand/finger and 16 ankle/foot/toe trauma scans). Reports by on-call radiologists before and after CBCT were compared regarding fracture detection, joint affliction, comminuted injuries, and diagnostic confidence. An orthopedic surgeon recommended therapy based on reported findings. Surgical reports (N = 52) and clinical follow-up (N = 85) were used as reference standard.
Results
CBCT detected more fractures (83/64 of 85), joint involvements (69/53 of 71), and multi-fragment situations (68/50 of 70) than radiography (all p < 0.001). Six fractures suspected in radiographs were ruled out by CBCT. Treatment changes based on additional information from CBCT were recommended in 29 patients (31.5%). While agreement between advised therapy before CBCT and actual treatment was moderate (κ = 0.41 [95% confidence interval 0.35–0.47]; p < 0.001), agreement after CBCT was almost perfect (κ = 0.88 [0.83–0.93]; p < 0.001). Diagnostic confidence increased considerably for CBCT studies (p < 0.001). Median effective dose for CBCT was 4.3 μSv [3.3–5.3 μSv] compared to 0.2 μSv [0.1–0.2 μSv] for radiography.
Conclusions
CBCT provides advantages for the evaluation of acute small bone and joint trauma by detecting and excluding extremity fractures and fracture-related findings more reliably than radiographs. Additional findings induced therapy change in one third of patients, suggesting substantial clinical impact.
Parathyroid carcinoma (PC) is an orphan malignancy accounting for only ~1% of all cases with primary hyperparathyroidism. The localization of recurrent PC is of critical importance and can be exceedingly difficult to diagnose and sometimes futile when common sites of recurrence in the neck and chest cannot be confirmed. Here, we present the diagnostic workup, molecular analysis and multimodal therapy of a 46-year old woman with the extraordinary manifestation of abdominal lymph node metastases 12 years after primary diagnosis of PC. The patient was referred to our endocrine tumor center in 2016 with the aim to localize the tumor causative of symptomatic biochemical recurrence. In view of the extensive previous workup we decided to perform [18F]FDG-PET-CT. A pathological lymph node in the liver hilus showed slightly increased FDG-uptake and hence was suspected as site of recurrence. Selective venous sampling confirmed increased parathyroid hormone concentration in liver veins. Abdominal lymph node metastasis was resected and histopathological examination confirmed PC. Within four months, the patient experienced biochemical recurrence and based on high tumor mutational burden detected in the surgical specimen by whole exome sequencing the patient received immunotherapy with pembrolizumab that led to a biochemical response. Subsequent to disease progression repeated abdominal lymph node resection was performed in 10/2018, 01/2019 and in 01/2020. Up to now (12/2020) the patient is biochemically free of disease. In conclusion, a multimodal diagnostic approach and therapy in an interdisciplinary setting is needed for patients with rare endocrine tumors. Molecular analyses may inform additional treatment options including checkpoint inhibitors such as pembrolizumab.
Purpose
Repeat surgery in patients with primary hyperparathyroidism (pHPT) is associated with an increased risk of complications and failure. This stresses the need for optimized strategies to accurately localize a parathyroid adenoma before repeat surgery is performed. However, evidence on the extent of required diagnostics for a structured approach is sparse.
Methods
A retrospective single-center evaluation of 28 patients with an indication for surgery due to pHPT and previous thyroid or parathyroid surgery was performed. Diagnostic workup, surgical approach, and outcome in terms of complications and successful removement of parathyroid adenoma with biochemical cure were evaluated.
Results
Neck ultrasound, sestamibi scintigraphy, C11-methionine PET-CT, and selective parathyroid hormone venous sampling, but not MRI imaging, effectively detected the presence of a parathyroid adenoma with high positive predictive values. Biochemical cure was revealed by normalization of calcium and parathormone levels 24-48h after surgery and was achieved in 26/28 patients (92.9%) with an overall low rate of complications. Concordant localization by at least two diagnostic modalities enabled focused surgery with success rates of 100%, whereas inconclusive localization significantly increased the rate of bilateral explorations and significantly reduced the rate of biochemical cure to 80%.
Conclusion
These findings suggest that two concordant diagnostic modalities are sufficient to accurately localize parathyroid adenoma before repeat surgery for pHPT. In cases of poor localization, extended diagnostic procedures are warranted to enhance surgical success rates. We suggest an algorithm for better orientation when repeat surgery is intended in patients with pHPT.