Refine
Year of publication
Document Type
- Article (236)
- Conference Proceeding (11)
- Part of a Book (2)
Keywords
Institute
- Medizinische Fakultät (248)
- Universitätsklinikum (246)
- Lehrstuhl für Diagnostische und Interventionelle Radiologie (243)
- Lehrstuhl für Allgemeine und Spezielle Pathologie (13)
- Lehrstuhl für Innere Medizin mit Schwerpunkt Hämatologie und Onkologie (11)
- Professur für personalisierte Tumormedizin und molekulare Onkologie (9)
- Lehrstuhl für Kinder- und Jugendmedizin (8)
- Nachhaltigkeitsziele (8)
- Zentrum für Advanced Analytics and Predictive Sciences (CAAPS) (8)
- Ziel 3 - Gesundheit und Wohlergehen (8)
Objectives
The UK Biobank (UKBB) and German National Cohort (NAKO) are among the largest cohort studies, capturing a wide range of health-related data from the general population, including comprehensive magnetic resonance imaging (MRI) examinations. The purpose of this study was to demonstrate how MRI data from these large-scale studies can be jointly analyzed and to derive comprehensive quantitative image-based phenotypes across the general adult population.
Materials and Methods
Image-derived features of abdominal organs (volumes of liver, spleen, kidneys, and pancreas; volumes of kidney hilum adipose tissue; and fat fractions of liver and pancreas) were extracted from T1-weighted Dixon MRI data of 17,996 participants of UKBB and NAKO based on quality-controlled deep learning generated organ segmentations. To enable valid cross-study analysis, we first analyzed the data generating process using methods of causal discovery. We subsequently harmonized data from UKBB and NAKO using the ComBat approach for batch effect correction. We finally performed quantile regression on harmonized data across studies providing quantitative models for the variation of image-derived features stratified for sex and dependent on age, height, and weight.
Results
Data from 8791 UKBB participants (49.9% female; age, 63 ± 7.5 years) and 9205 NAKO participants (49.1% female, age: 51.8 ± 11.4 years) were analyzed. Analysis of the data generating process revealed direct effects of age, sex, height, weight, and the data source (UKBB vs NAKO) on image-derived features. Correction of data source-related effects resulted in markedly improved alignment of image-derived features between UKBB and NAKO. Cross-study analysis on harmonized data revealed comprehensive quantitative models for the phenotypic variation of abdominal organs across the general adult population.
Conclusions
Cross-study analysis of MRI data from UKBB and NAKO as proposed in this work can be helpful for future joint data analyses across cohorts linking genetic, environmental, and behavioral risk factors to MRI-derived phenotypes and provide reference values for clinical diagnostics.
Value of dual-phase multislice CT prior to minimally invasive therapy of iatrogenic renal injuries
(2005)
Whole-body MR imaging in the German National Cohort: rationale, design, and technical background
(2015)
Objectives
Liquid biopsy (LBx) provides diagnostic, prognostic and predictive insights for malignant diseases and offers promising applications regarding tumor burden, tumor heterogeneity and clonal evolution.
Methods
ALPS is a prospective trial for patients with metastatic cancer that comprises sequential collection of LBx samples, tumor tissue, radiological imaging data, clinical information and patient-reported outcomes. Peripheral blood plasma is collected based on the individual patient’s staging intervals and LBx-derived ctDNA analyses are performed using CAncer Personalized Profiling sequencing (CAPP-seq).
Results
From April 2021 to October 2023, 419 patients have been enrolled. A total of 1,293 LBx samples were collected, 419 samples (100 %) at the beginning of the study and an average of 3 (range 1–12) during the 30-month follow-up period of the current interim analysis. 380 tissue biopsy (TBx) samples (90.7 %) were available at baseline and 39.6 % had ≥1 TBx samples at follow-up. Lung cancer patients are most prevalent in ALPS (n=147), followed by colorectal (n=38), prostate (n=31) and gastroesophageal cancer (n=28). On average, 12.0 ng/mL plasma cell-free DNA (cfDNA) could be isolated. First CAPP-seq analyses in 60 patients comprised 110 samples and demonstrated a detection sensitivity of 0.1 %.
Conclusions
The first interim analysis of ALPS confirms feasibility for comprehensive longitudinal evaluation of LBx and demonstrates suitability for ctDNA evaluation.
In magnetic resonance imaging (MRI), the perception of substandard image quality may prompt repetition of the respective image acquisition protocol. Subsequently selecting the preferred high-quality image data from a series of acquisitions can be challenging. An automated workflow may facilitate and improve this selection. We therefore aimed to investigate the applicability of an automated image quality assessment for the prediction of the subjectively preferred image acquisition. Our analysis included data from 11,347 participants with whole-body MRI examinations performed as part of the ongoing prospective multi-center German National Cohort (NAKO) study. Trained radiologic technologists repeated any of the twelve examination protocols due to induced setup errors and/or subjectively unsatisfactory image quality and chose a preferred acquisition from the resultant series. Up to 11 quantitative image quality parameters were automatically derived from all acquisitions. Regularized regression and standard estimates of diagnostic accuracy were calculated. Controlling for setup variations in 2342 series of two or more acquisitions, technologists preferred the repetition over the initial acquisition in 1116 of 1396 series in which the initial setup was retained (79.9%, range across protocols: 73–100%). Image quality parameters then commonly showed statistically significant differences between chosen and discarded acquisitions. In regularized regression across all protocols, ‘structured noise maximum’ was the strongest predictor for the technologists’ choice, followed by ‘N/2 ghosting average’. Combinations of the automatically derived parameters provided an area under the ROC curve between 0.51 and 0.74 for the prediction of the technologists’ choice. It is concluded that automated image quality assessment can, despite considerable performance differences between protocols and anatomical regions, contribute substantially to identifying the subjective preference in a series of MRI acquisitions and thus provide effective decision support to readers.
Neurofibromatosis type 1 (NF1) is a phenotypically heterogenous multisystem cancer predisposition syndrome manifesting in childhood and adolescents. Central nervous system (CNS) manifestations include structural, neurodevelopmental, and neoplastic disease. We aimed to (1) characterize the spectrum of CNS manifestations of NF1 in a paediatric population, (2) explore radiological features in the CNS by image analyses, and (3) correlate genotype with phenotypic expression for those with a genetic diagnosis. We performed a database search in the hospital information system covering the period between January 2017 and December 2020. We evaluated the phenotype by retrospective chart review and imaging analysis. 59 patients were diagnosed with NF1 [median age 10.6 years (range, 1.1–22.6); 31 female] at last follow-up, pathogenic NF1 variants were identified in 26/29. 49/59 patients presented with neurological manifestations including 28 with structural and neurodevelopmental findings, 16 with neurodevelopmental, and 5 with structural findings only. Focal areas of signal intensity (FASI) were identified in 29/39, cerebrovascular anomalies in 4/39. Neurodevelopmental delay was reported in 27/59 patients, learning difficulties in 19/59. Optic pathway gliomas (OPG) were diagnosed in 18/59 patients, 13/59 had low-grade gliomas outside the visual pathways. 12 patients received chemotherapy. Beside the established NF1 microdeletion, neither genotype nor FASI were associated with the neurological phenotype. NF1 was associated with a spectrum of CNS manifestations in at least 83.0% of patients. Regular neuropsychological assessment complementing frequent clinical and ophthalmologic testing for OPG is necessary in the care of each child with NF1.
