Publications by authors named "Stefan Klein"

165 Publications

[Potential of ultrasound in allogeneic stem cell transplantation and transplant-related complications].

Z Gastroenterol 2021 Feb 25. Epub 2021 Feb 25.

Interdisziplinäres Ultraschallzentrum, UKGM Marburg.

Allogeneic hematopoietic stem cell transplantation (HCT) is a complex therapeutic procedure causing significant morbidity and mortality, including the gastrointestinal tract. Early diagnosis and treatment of HCT-associated complications are, therefore, of utmost importance to improve overall HCT outcome. Sonography can be a powerful diagnostic tool and is easily accessible at the bedside of HCT patients. In the hands of a sonography-experienced physician, it allows for instant diagnosis and can also rule out several important transplant-associated complications. Here we review available evidence on the diagnostic and clinical value of ultrasound prior, during and after HCT.
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http://dx.doi.org/10.1055/a-1374-4192DOI Listing
February 2021

APIR4EMC: Autocalibrated parallel imaging reconstruction for extended multi-contrast imaging.

Magn Reson Imaging 2021 Feb 14;78:80-89. Epub 2021 Feb 14.

Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.

Purpose: To improve image quality of multi-contrast imaging with the proposed Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging (APIR4EMC).

Methods: APIR4EMC reconstructs multi-contrast images in an autocalibrated parallel imaging reconstruction framework by adding contrasts as virtual coils. Compensation of signal evolution along the echo train of different contrasts is performed to improve signal prediction for missing samples. As a proof of concept, we performed prospectively accelerated phantom and in-vivo brain acquisitions with T1, T1-fat saturated (Fatsat), T2, PD, and FLAIR contrasts. The k-space sampling patterns of these acquisitions were jointly optimized. Images were jointly reconstructed with the proposed APIR4EMC method as well as individually with GRAPPA. Root mean square error (RMSE) to fully sampled reference images and g-factor maps were computed for both methods in the phantom experiment. Visual evaluation was performed in the in-vivo experiment.

Results: Compared to GRAPPA, APIR4EMC reduced artifacts and improved SNR of the reconstructed images in the phantom acquisitions. Quantitatively, APIR4EMC substantially reduced noise amplification (g-factor) as well as RMSE compared to GRAPPA. Signal evolution compensation reduced artifacts. In the in-vivo experiments, 1 mm isotropic 3D images with contrasts of T1, T1-Fatsat, T2, PD, and FLAIR were acquired in as little as 7.5 min with the acceleration factor of 9. Reconstruction quality was consistent with the phantom results.

Conclusion: Compared to single contrast reconstruction with GRAPPA, APIR4EMC reduces artifacts and noise amplification in accelerated multi-contrast imaging.
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http://dx.doi.org/10.1016/j.mri.2021.02.002DOI Listing
February 2021

The Human Leukocyte Antigen-DPB1 Degree of Compatibility Is Determined by Its Expression Level and Mismatch Permissiveness: A German Multicenter Analysis.

Front Immunol 2020 25;11:614976. Epub 2021 Jan 25.

Institute of Clinical Transfusion Medicine and Immunogenetics Ulm, German Red Cross Blood Transfusion Service, Baden Wuerttemberg-Hessen, and University Hospital Ulm, Ulm, Germany.

T-cell epitope matching according to the TCE3 algorithm classifies HLA-DPB1 mismatches in permissive and non-permissive. This classification has been shown to be predictive for mortality and acute GvHD (aGvHD) events in large international cohorts. We retrospectively genotyped HLA-DPB1 in 3523 patients transplanted in Germany between 2000 and 2014 and in their unrelated donors using an Illumina amplicon-NGS based assay. Aim of the study was to evaluate DP-compatibility beyond the established TCE3 algorithm by assessing the combined effect of several DP-mismatch parameters on post-transplant outcome. We implemented an extended DP-mismatch assessment model where TCE3, DP allotype expression with respect to rs9277534, mismatch vector and number of mismatches were conjointly taken into consideration. In this model, non-permissive HLA-DPB1 mismatches showed significantly increased aGvHD risk if they were accompanied by two HLA-DPB1 mismatches in GvH direction (HR: 1.46) or one mismatched highly expressed patient allotype (HR: 1.53). As previously reported, non-permissive HLA-DPB1 mismatches associated with a significantly higher risk of aGvHD and non-relapse mortality (HR 1.36 and 1.21, respectively), which in turn translated into worse GvHD and relapse free survival (HR 1.13). Effects on GvL and GvHD appeared strongest in GvH-directed non-permissive mismatches. Our study results support the consideration of additional HLA-DPB1 mismatch parameters along with the established TCE3 matching algorithm for refinement of future donor selection. In particular, our findings suggest that DP non-permissiveness associated with two HLA-DPB1 mismatches or at least on highly expressed mismatched patient allotype should be avoided.
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http://dx.doi.org/10.3389/fimmu.2020.614976DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7868530PMC
January 2021

Efficacy of UVC-treated, pathogen-reduced platelets versus untreated platelets: a randomized controlled non-inferiority trial.

Haematologica 2021 Feb 4. Epub 2021 Feb 4.

German Red Cross Blood Service NSTOB, Springe, Germany; Bavarian Red Cross Blood Service, Nuremberg.

Pathogen reduction (PR) technologies for blood components have been established to reduce the residual risk of known and emerging infectious agents. THERAFLEX UVPlatelets, a novel UVC light-based PR technology for platelet concentrates, works without photoactive substances. This randomized, controlled, double-blind, multicenter, noninferiority trial was designed to compare the efficacy and safety of UVC-treated platelets to that of untreated platelets in thrombocytopenic patients with hematologic-oncologic diseases. Primary objective was to determine non-inferiority of UVC-treated platelets, assessed by the 1-hour corrected count increment (CCI) in up to eight per-protocol platelet transfusion episodes. Analysis of the 171 eligible patients showed that the defined non-inferiority margin of 30% of UVC-treated platelets was narrowly missed as the mean differences in 1-hour CCI between standard platelets versus UVC-treated platelets for intention-to-treat and perprotocol analyses were 18.2% (95% confidence interval [CI]: 6.4%; 30.1) and 18.7% (95% CI: 6.3%; 31.1%), respectively. In comparison to the control, the UVC group had a 19.2% lower mean 24-hour CCI and was treated with an about 25% higher number of platelet units, but the average number of days to next platelet transfusion did not differ significantly between both treatment groups. The frequency of low-grade adverse events was slightly higher in the UVC group and the frequencies of refractoriness to platelet transfusion, platelet alloimmunization, severe bleeding events, and red blood cell transfusions were comparable between groups. Our study suggests that transfusion of pathogen-reduced platelets produced with the UVC technology is safe but non-inferiority was not demonstrated. (The German Clinical Trials Register number: DRKS00011156).
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http://dx.doi.org/10.3324/haematol.2020.260430DOI Listing
February 2021

Modelling the cascade of biomarker changes in -related frontotemporal dementia.

J Neurol Neurosurg Psychiatry 2021 Jan 15. Epub 2021 Jan 15.

Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.

Objective: Progranulin-related frontotemporal dementia (FTD-) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-, in a data-driven way.

Methods: We included 56 presymptomatic and 35 symptomatic mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD- and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.

Results: Language functioning and NfL were the earliest abnormal biomarkers in FTD-. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.

Conclusion: Degeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic mutation carriers at risk of conversion to the clinical stage.
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http://dx.doi.org/10.1136/jnnp-2020-323541DOI Listing
January 2021

The sequence of structural, functional and cognitive changes in multiple sclerosis.

Neuroimage Clin 2021 24;29:102550. Epub 2020 Dec 24.

Amsterdam UMC, Location VUmc, Departments of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands. Electronic address:

Background: As disease progression remains poorly understood in multiple sclerosis (MS), we aim to investigate the sequence in which different disease milestones occur using a novel data-driven approach.

Methods: We analysed a cohort of 295 relapse-onset MS patients and 96 healthy controls, and considered 28 features, capturing information on T2-lesion load, regional brain and spinal cord volumes, resting-state functional centrality ("hubness"), microstructural tissue integrity of major white matter (WM) tracts and performance on multiple cognitive tests. We used a discriminative event-based model to estimate the sequence of biomarker abnormality in MS progression in general, as well as specific models for worsening physical disability and cognitive impairment.

Results: We demonstrated that grey matter (GM) atrophy of the cerebellum, thalamus, and changes in corticospinal tracts are early events in MS pathology, whereas other WM tracts as well as the cognitive domains of working memory, attention, and executive function are consistently late events. The models for disability and cognition show early functional changes of the default-mode network and earlier changes in spinal cord volume compared to the general MS population. Overall, GM atrophy seems crucial due to its early involvement in the disease course, whereas WM tract integrity appears to be affected relatively late despite the early onset of WM lesions.

Conclusion: Data-driven modelling revealed the relative occurrence of both imaging and non-imaging events as MS progresses, providing insights into disease propagation mechanisms, and allowing fine-grained staging of patients for monitoring purposes.
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http://dx.doi.org/10.1016/j.nicl.2020.102550DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804841PMC
December 2020

Analyzing the effect of APOE on Alzheimer's disease progression using an event-based model for stratified populations.

Neuroimage 2021 02 16;227:117646. Epub 2020 Dec 16.

Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, the Netherlands.

Alzheimer's disease (AD) is the most common form of dementia and is phenotypically heterogeneous. APOE is a triallelic gene which correlates with phenotypic heterogeneity in AD. In this work, we determined the effect of APOE alleles on the disease progression timeline of AD using a discriminative event-based model (DEBM). Since DEBM is a data-driven model, stratification into smaller disease subgroups would lead to more inaccurate models as compared to fitting the model on the entire dataset. Hence our secondary aim is to propose and evaluate novel approaches in which we split the different steps of DEBM into group-aspecific and group-specific parts, where the entire dataset is used to train the group-aspecific parts and only the data from a specific group is used to train the group-specific parts of the DEBM. We performed simulation experiments to benchmark the accuracy of the proposed approaches and to select the optimal approach. Subsequently, the chosen approach was applied to the baseline data of 417 cognitively normal, 235 mild cognitively impaired who convert to AD within 3 years, and 342 AD patients from the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset to gain new insights into the effect of APOE carriership on the disease progression timeline of AD. In the ε4 carrier group, the model predicted with high confidence that CSF Amyloidβ and the cognitive score of Alzheimer's Disease Assessment Scale (ADAS) are early biomarkers. Hippocampus was the earliest volumetric biomarker to become abnormal, closely followed by the CSF Phosphorylated Tau (PTAU) biomarker. In the homozygous ε3 carrier group, the model predicted a similar ordering among CSF biomarkers. However, the volume of the fusiform gyrus was identified as one of the earliest volumetric biomarker. While the findings in the ε4 carrier and the homozygous ε3 carrier groups fit the current understanding of progression of AD, the finding in the ε2 carrier group did not. The model predicted, with relatively low confidence, CSF Neurogranin as one of the earliest biomarkers along with cognitive score of Mini-Mental State Examination (MMSE). Amyloid β was found to become abnormal after PTAU. The presented models could aid understanding of the disease, and in selecting homogeneous group of presymptomatic subjects at-risk of developing symptoms for clinical trials.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117646DOI Listing
February 2021

Allogeneic HCT for adults with B-cell precursor acute lymphoblastic leukemia harboring IKZF1 gene mutations. A study by the Acute Leukemia Working Party of the EBMT.

Bone Marrow Transplant 2020 Nov 25. Epub 2020 Nov 25.

Department of Hematology, Hospital Saint Antoine, Paris, France.

The presence of IKZF1 gene mutations is associated with poor prognosis of B-cell precursor acute lymphoblastic leukemia (BCP-ALL). The goal of this retrospective study was to evaluate outcome of allogeneic hematopoietic cell transplantation (allo-HCT) in this population. Ninety-five patients transplanted in first (n = 75) or second (n = 20) complete remission (CR) from either HLA-matched sibling (n = 32), unrelated (n = 47) or haploidentical (n = 16) donor were included in the analysis. The probabilities of the overall survival (OS) and leukemia-free survival (LFS) at 2 years were 55% and 47%, respectively. Relapse incidence (RI) was 32% while non-relapse mortality (NRM), 21%. The incidence of grade II-IV acute graft-versus-host disease (GVHD) and chronic GVHD was 34% and 30%, respectively. The probability of GVHD and relapse-free survival (GRFS) was 35%. In a multivariate analysis positive minimal residual disease (MRD) status was associated with decreased chance of LFS (HR = 3.15, p = 0.004) and OS (HR = 2.37, p = 0.049) as well as increased risk of relapse (HR = 5.87, p = 0.003). Disease stage (CR2 vs. CR1) affected all, LFS, OS, GRFS, RI, and NRM. Results of allo-HCT for patients with BCP-ALL and IKZF1 mutations are generally improving, however, individuals with detectable MRD have poor prognosis and require additional intervention prior to transplantation.
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http://dx.doi.org/10.1038/s41409-020-01139-zDOI Listing
November 2020

OCTA Multilayer and Multisector Peripapillary Microvascular Modeling for Diagnosing and Staging of Glaucoma.

Transl Vis Sci Technol 2020 11 5;9(2):58. Epub 2020 Nov 5.

Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.

Purpose: To develop and assess an automatic procedure for classifying and staging glaucomatous vascular damage based on optical coherence tomography angiography (OCTA) imaging.

Methods: OCTA scans (Zeiss Cirrus 5000 HD-OCT) from a random eye of 39 healthy subjects and 82 glaucoma patients were used to develop a new classification algorithm based on multilayer and multisector information. The averaged circumpapillary retinal nerve fiber layer (RNFL) thickness was also collected. Three models, support vector machine (SVM), random forest (RF), and gradient boosting (xGB), were developed and optimized for classifying between healthy and glaucoma patients, primary open-angle glaucoma (POAG) and normal-tension glaucoma (NTG), and glaucoma severity groups.

Results: All the models, the SVM (area under the receiver operating characteristic [AUROC] 0.89 ± 0.06), the RF (AUROC 0.86 ± 0.06), and the xGB (AUROC 0.85 ± 0.07), with 26, 22, and 29 vascular features obtained after feature selection, respectively, presented a similar performance to the RNFL thickness (AUROC 0.85 0.06) in classifying healthy and glaucoma patients. The superficial vascular plexus was the most informative layer with the infero temporal sector as the most discriminative region of interest. No significant differentiation was obtained in discriminating the POAG from the NTG group. The xGB model, after feature selection, presented the best performance in classifying the severity groups (AUROC 0.76 0.06), outperforming the RNFL (AUROC 0.67 0.06).

Conclusions: OCTA multilayer and multisector information has similar performance to RNFL for glaucoma diagnosis, but it has an added value for glaucoma severity classification, showing promising results for staging glaucoma progression.

Translational Relevance: OCTA, in its current stage, has the potential to be used in clinical practice as a complementary imaging technique in glaucoma management.
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http://dx.doi.org/10.1167/tvst.9.2.58DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674004PMC
November 2020

Treatment of myeloid malignancies relapsing after allogeneic hematopoietic stem cell transplantation with venetoclax and hypomethylating agents-a retrospective multicenter analysis on behalf of the German Cooperative Transplant Study Group.

Ann Hematol 2020 Nov 16. Epub 2020 Nov 16.

Department of Hematology, Oncology and Clinical Immunology, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University, Moorenstr. 5, 40225, Düsseldorf, Germany.

Treatment of relapse after allogeneic hematopoietic stem cell transplantation (alloHSCT) remains a great challenge. Aiming to evaluate the combination of venetoclax and hypomethylating agents (HMAClax) for the treatment of relapse of myeloid malignancies after alloHSCT, we retrospectively collected data from 32 patients treated at 11 German centers. Venetoclax was applied with azacitidine (n = 13) or decitabine (n = 19); 11 patients received DLI in addition. HMAClax was the first salvage therapy in 8 patients. The median number of cycles per patient was 2 (1-19). All but 1 patient had grade 3/4 neutropenia. Hospital admission for grade 3/4 infections was necessary in 23 patients (72%); 5 of these were fatal. In 30 evaluable patients, overall response rate (ORR) was 47% (14/30, 3 CR MRD, 5 CR, 2 CRi, 1 MLFS, 3 PR). ORR was 86% in first salvage patients versus 35% in later salvage patients (p = 0.03). In 6 patients with molecular relapse (MR), ORR was 67% versus 42% in patients with hematological relapse (HR) (n = 24, p = n.s.). After a median follow-up of 8.4 months, 25 patients (78%) had died and 7 were alive. Estimated median overall survival was 3.7 months. Median survival of patients with HMAClax for first versus later salvage therapy was 5.7 and 3.4 months (p = n.s.) and for patients with MR (not reached) compared to HR (3.4 months, p = 0.024). This retrospective case series shows that venetoclax is utilized in various different combinations, schedules, and doses. Toxicity is substantial and patients who receive venetoclax/HMA combinations for MR or as first salvage therapy derive the greatest benefit.
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http://dx.doi.org/10.1007/s00277-020-04321-xDOI Listing
November 2020

Erratum: The Value of Quantitative Musculoskeletal Imaging.

Semin Musculoskelet Radiol 2020 Aug 21;24(4):e1. Epub 2020 Oct 21.

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

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http://dx.doi.org/10.1055/s-0040-1719097DOI Listing
August 2020

A multicenter prospective, randomized, placebo-controlled phase II/III trial for preemptive acute graft-versus-host disease therapy.

Leukemia 2020 Oct 20. Epub 2020 Oct 20.

Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany.

Acute graft-versus-host disease (aGvHD) contributes to about 50% of transplant-related mortality (non-relapse mortality) after allogeneic hematopoietic stem cell transplantation (HSCT). Here the predictive value of a urinary proteomic profile (aGvHD_MS17) was tested together with preemptive prednisolone therapy. Two-hundred and fifty-nine of 267 patients were eligible for analysis. Ninety-two patients were randomized upon aGvHD_MS17 classification factor above 0.1 to receive either prednisolone (2-2.5 mg/kg, N = 44) or placebo (N = 47; N = 1 randomization failure) for 5 days followed by tapering. The remaining 167 patients formed the observation group. The primary endpoint of the randomized trial was incidence of aGvHD grade II between randomization and day +100 post HSCT. Analysis of the short-term preemptive prednisolone therapy in the randomized patients showed no significant difference in incidence or severity of acute GvHD (HR: 1.69, 95% CI: 0.66-4.32, P = 0.27). Prednisolone as preemptive treatment did not lead to an increase in relapse (20.2% in the placebo and 14.0% in the prednisolone group (P = 0.46)). The frequency of adverse events was slightly higher in the placebo group (64.4% versus 50%, respectively). Taken together, the results of the Pre-GvHD trial demonstrated the feasibility and safety of preemptive prednisolone treatment in the randomized patients.
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http://dx.doi.org/10.1038/s41375-020-01059-3DOI Listing
October 2020

Topical Treatment of Acyclovir-Resistant Herpes Simplex Virus Stomatitis after Allogeneic Hematopoietic Cell Transplantation.

Oncol Res Treat 2020 16;43(12):672-678. Epub 2020 Oct 16.

Department of Hematology and Oncology, University Hospital Mannheim, Heidelberg University, Mannheim, Germany,

Introduction: We report on patients who developed severe acyclovir-resistant (ACVr) herpes simplex virus 1 (HSV-1) stomatitis after allogeneic hematopoietic cell transplantation (HCT).

Patients: HCT patients suffering from HSV-1 stomatitis without response after 1 week of high-dose acyclovir (ACV) were tested for ACV resistance. Patients with proven ACV resistance were treated either topically with cidofovir solution and gel or with topical foscavir cream or with intravenous foscavir.

Results: Among 214 consecutive HCT patients, 6 developed severe ACVr HSV-1 stomatitis (WHO grade III n = 1, WHO grade IV n = 5). All 6 patients suffered from relapse of acute myeloid leukemia (AML) after HCT. ACVr stomatitis was treated topically with first-line (n = 4) or second-line (n = 2) cidofovir. Topical foscavir cream was applied as first-line (n = 1) or second-line (n = 1) therapy. Intravenous foscavir was used in 3 patients (first-line therapy, n = 1; second-line therapy, n = 2). Complete remission was reached by topical cidofovir (n = 3), topical foscavir (n = 1), and intravenous foscavir (n = 1), respectively. Five of the 6 patients died due to progression of leukemia. Only 1 patient survived.

Conclusions: ACVr HSV-1 stomatitis is a severe complication in AML patients relapsing after HCT. It reflects the seriously impaired general condition of these patients. This analysis shows that topical treatment with cidofovir or foscavir might be a sufficient first-line therapy approach in ACVr HSV-1 stomatitis. It might serve as a less toxic alternative to intravenous foscavir.
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http://dx.doi.org/10.1159/000510988DOI Listing
October 2020

The Value of Quantitative Musculoskeletal Imaging.

Semin Musculoskelet Radiol 2020 Aug 29;24(4):460-474. Epub 2020 Sep 29.

Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Musculoskeletal imaging is mainly based on the subjective and qualitative analysis of imaging examinations. However, integration of quantitative assessment of imaging data could increase the value of imaging in both research and clinical practice. Some imaging modalities, such as perfusion magnetic resonance imaging (MRI), diffusion MRI, or T2 mapping, are intrinsically quantitative. But conventional morphological imaging can also be analyzed through the quantification of various parameters. The quantitative data retrieved from imaging examinations can serve as biomarkers and be used to support diagnosis, determine patient prognosis, or monitor therapy.We focus on the value, or clinical utility, of quantitative imaging in the musculoskeletal field. There is currently a trend to move from volume- to value-based payments. This review contains definitions and examines the role that quantitative imaging may play in the implementation of value-based health care. The influence of artificial intelligence on the value of quantitative musculoskeletal imaging is also discussed.
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http://dx.doi.org/10.1055/s-0040-1710356DOI Listing
August 2020

Association between meniscal volume and development of knee osteoarthritis.

Rheumatology (Oxford) 2020 Sep 25. Epub 2020 Sep 25.

Department of General Practice, Erasmus MC University Medical Center Rotterdam, The Netherlands.

Objective: To assess the association between meniscal volume, its change over time and the development of knee OA after 30 months in overweight/obese women.

Methods: Data from the PRevention of knee Osteoarthritis in Overweight Females study were used. This cohort included 407 women with a BMI ≥ 27 kg/m2, free of OA-related symptoms. The primary outcome measure was incident OA after 30 months, defined by one out of the following criteria: medial or lateral joint space narrowing (JSN)  ≥ 1.0 mm, incident radiographic OA [Kellgren and Lawrence (K&L)  ≥ 2], or incident clinical OA. The secondary outcomes were either of these items separately. Menisci at both baseline and follow-up were automatically segmented to obtain meniscal volume and delta-volumes. Generalized estimating equations were used to evaluate associations between the volume measures and the outcomes.

Results: Medial and lateral baseline and delta-volumes were not significantly associated to the primary outcome. Lateral meniscal baseline volume was significantly associated to lateral JSN [odds ratio (OR) = 0.87; 95% CI: 0.75, 0.99], while other measures were not. Medial and lateral baseline volume were positively associated to K&L incidence (OR = 1.32 and 1.22; 95% CI: 1.15, 1.50 and 1.03, 1.45, respectively), while medial and lateral delta-volume were negatively associated to K&L incidence (OR = 0.998 and 0.997; 95% CI: 0.997, 1.000 and 0.996, 0.999, respectively). None of the meniscal measures were significantly associated to incident clinical OA.

Conclusion: Larger baseline meniscal volume and the decrease of meniscal volume over time were associated to the development of structural OA after 30 months in overweight and obese women.
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http://dx.doi.org/10.1093/rheumatology/keaa522DOI Listing
September 2020

Differential diagnosis and mutation stratification of desmoid-type fibromatosis on MRI using radiomics.

Eur J Radiol 2020 Oct 8;131:109266. Epub 2020 Sep 8.

Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands. Electronic address:

Purpose: Diagnosing desmoid-type fibromatosis (DTF) requires an invasive tissue biopsy with β-catenin staining and CTNNB1 mutational analysis, and is challenging due to its rarity. The aim of this study was to evaluate radiomics for distinguishing DTF from soft tissue sarcomas (STS), and in DTF, for predicting the CTNNB1 mutation types.

Methods: Patients with histologically confirmed extremity STS (non-DTF) or DTF and at least a pretreatment T1-weighted (T1w) MRI scan were retrospectively included. Tumors were semi-automatically annotated on the T1w scans, from which 411 features were extracted. Prediction models were created using a combination of various machine learning approaches. Evaluation was performed through a 100x random-split cross-validation. The model for DTF vs. non-DTF was compared to classification by two radiologists on a location matched subset.

Results: The data included 203 patients (72 DTF, 131 STS). The T1w radiomics model showed a mean AUC of 0.79 on the full dataset. Addition of T2w or T1w post-contrast scans did not improve the performance. On the location matched cohort, the T1w model had a mean AUC of 0.88 while the radiologists had an AUC of 0.80 and 0.88, respectively. For the prediction of the CTNNB1 mutation types (S45 F, T41A and wild-type), the T1w model showed an AUC of 0.61, 0.56, and 0.74.

Conclusions: Our radiomics model was able to distinguish DTF from STS with high accuracy similar to two radiologists, but was not able to predict the CTNNB1 mutation status.
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http://dx.doi.org/10.1016/j.ejrad.2020.109266DOI Listing
October 2020

Salvage autologous transplant and lenalidomide maintenance vs. lenalidomide/dexamethasone for relapsed multiple myeloma: the randomized GMMG phase III trial ReLApsE.

Leukemia 2020 Jul 21. Epub 2020 Jul 21.

Department of Oncology, Hematology and Bone Marrow Transplantation with Section of Pneumology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

The role of salvage high-dose chemotherapy and autologous stem cell transplantation (sHDCT/ASCT) for relapsed and/or refractory multiple myeloma (RRMM) in the era of continuous novel agent treatment has not been defined. This randomized, open-label, phase III, multicenter trial randomized patients with 1st-3rd relapse of multiple myeloma (MM) to a transplant arm (n = 139) consisting of 3 Rd (lenalidomide 25 mg, day 1-21; dexamethasone 40 mg, day 1, 8, 15, and 22; 4-week cycles) reinduction cycles, sHDCT (melphalan 200 mg/m), ASCT, and lenalidomide maintenance (10 mg/day) or to a control arm (n = 138) of continuous Rd. Median PFS was 20.7 months in the transplant and 18.8 months in the control arm (HR 0.87; 95% CI 0.65-1.16; p = 0.34). Median OS was not reached in the transplant and 62.7 months in the control arm (HR 0.81; 95% CI 0.52-1.28; p = 0.37). Forty-one patients (29%) did not receive the assigned sHDCT/ASCT mainly due to early disease progression, adverse events, and withdrawal of consent. Multivariate landmark analyses from the time of sHDCT showed superior PFS and OS (p = 0.0087/0.0057) in patients who received sHDCT/ASCT. Incorporation of sHDCT/ASCT into relapse treatment with Rd was feasible in 71% of patients and did not significantly prolong PFS and OS on ITT analysis while patients who received sHDCT/ASCT may have benefitted.
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http://dx.doi.org/10.1038/s41375-020-0948-0DOI Listing
July 2020

DeepDicomSort: An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data.

Neuroinformatics 2021 01;19(1):159-184

Biomedical Imaging Group Rotterdam, Departments of Radiology and Nuclear Medicine and Medical Informatics, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands.

With the increasing size of datasets used in medical imaging research, the need for automated data curation is arising. One important data curation task is the structured organization of a dataset for preserving integrity and ensuring reusability. Therefore, we investigated whether this data organization step can be automated. To this end, we designed a convolutional neural network (CNN) that automatically recognizes eight different brain magnetic resonance imaging (MRI) scan types based on visual appearance. Thus, our method is unaffected by inconsistent or missing scan metadata. It can recognize pre-contrast T1-weighted (T1w),post-contrast T1-weighted (T1wC), T2-weighted (T2w), proton density-weighted (PDw) and derived maps (e.g. apparent diffusion coefficient and cerebral blood flow). In a first experiment,we used scans of subjects with brain tumors: 11065 scans of 719 subjects for training, and 2369 scans of 192 subjects for testing. The CNN achieved an overall accuracy of 98.7%. In a second experiment, we trained the CNN on all 13434 scans from the first experiment and tested it on 7227 scans of 1318 Alzheimer's subjects. Here, the CNN achieved an overall accuracy of 98.5%. In conclusion, our method can accurately predict scan type, and can quickly and automatically sort a brain MRI dataset virtually without the need for manual verification. In this way, our method can assist with properly organizing a dataset, which maximizes the shareability and integrity of the data.
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http://dx.doi.org/10.1007/s12021-020-09475-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7782469PMC
January 2021

TADPOLE Challenge: Accurate Alzheimer's disease prediction through crowdsourced forecasting of future data.

Predict Intell Med 2019 10 10;11843:1-10. Epub 2019 Oct 10.

Centre for Medical Image Computing, University College London, UK.

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge compares the performance of algorithms at predicting the future evolution of individuals at risk of Alzheimer's disease. TADPOLE Challenge participants train their models and algorithms on historical data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Participants are then required to make forecasts of three key outcomes for ADNI-3 rollover participants: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog 13), and total volume of the ventricles - which are then compared with future measurements. Strong points of the challenge are that the test data did not exist at the time of forecasting (it was acquired afterwards), and that it focuses on the challenging problem of cohort selection for clinical trials by identifying fast progressors. The submission phase of TADPOLE was open until 15 November 2017; since then data has been acquired until April 2019 from 219 subjects with 223 clinical visits and 150 Magnetic Resonance Imaging (MRI) scans, which was used for the evaluation of the participants' predictions. Thirty-three teams participated with a total of 92 submissions. No single submission was best at predicting all three outcomes. For diagnosis prediction, the best forecast (team Frog), which was based on gradient boosting, obtained a multiclass area under the receiver-operating curve (MAUC) of 0.931, while for ventricle prediction the best forecast (team ), which was based on disease progression modelling and spline regression, obtained mean absolute error of 0.41% of total intracranial volume (ICV). For ADAS-Cog 13, no forecast was considerably better than the benchmark mixed effects model ( ), provided to participants before the submission deadline. Further analysis can help understand which input features and algorithms are most suitable for Alzheimer's disease prediction and for aiding patient stratification in clinical trials. The submission system remains open via the website: https://tadpole.grand-challenge.org/.
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http://dx.doi.org/10.1007/978-3-030-32281-6_1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315046PMC
October 2019

FAIR-compliant clinical, radiomics and DICOM metadata of RIDER, interobserver, Lung1 and head-Neck1 TCIA collections.

Med Phys 2020 Nov 27;47(11):5931-5940. Epub 2020 Jun 27.

Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, 6229 ET, The Netherlands.

Purpose: One of the most frequently cited radiomics investigations showed that features automatically extracted from routine clinical images could be used in prognostic modeling. These images have been made publicly accessible via The Cancer Imaging Archive (TCIA). There have been numerous requests for additional explanatory metadata on the following datasets - RIDER, Interobserver, Lung1, and Head-Neck1. To support repeatability, reproducibility, generalizability, and transparency in radiomics research, we publish the subjects' clinical data, extracted radiomics features, and digital imaging and communications in medicine (DICOM) headers of these four datasets with descriptive metadata, in order to be more compliant with findable, accessible, interoperable, and reusable (FAIR) data management principles.

Acquisition And Validation Methods: Overall survival time intervals were updated using a national citizens registry after internal ethics board approval. Spatial offsets of the primary gross tumor volume (GTV) regions of interest (ROIs) associated with the Lung1 CT series were improved on the TCIA. GTV radiomics features were extracted using the open-source Ontology-Guided Radiomics Analysis Workflow (O-RAW). We reshaped the output of O-RAW to map features and extraction settings to the latest version of Radiomics Ontology, so as to be consistent with the Image Biomarker Standardization Initiative (IBSI). Digital imaging and communications in medicine metadata was extracted using a research version of Semantic DICOM (SOHARD, GmbH, Fuerth; Germany). Subjects' clinical data were described with metadata using the Radiation Oncology Ontology. All of the above were published in Resource Descriptor Format (RDF), that is, triples. Example SPARQL queries are shared with the reader to use on the online triples archive, which are intended to illustrate how to exploit this data submission.

Data Format: The accumulated RDF data are publicly accessible through a SPARQL endpoint where the triples are archived. The endpoint is remotely queried through a graph database web application at http://sparql.cancerdata.org. SPARQL queries are intrinsically federated, such that we can efficiently cross-reference clinical, DICOM, and radiomics data within a single query, while being agnostic to the original data format and coding system. The federated queries work in the same way even if the RDF data were partitioned across multiple servers and dispersed physical locations.

Potential Applications: The public availability of these data resources is intended to support radiomics features replication, repeatability, and reproducibility studies by the academic community. The example SPARQL queries may be freely used and modified by readers depending on their research question. Data interoperability and reusability are supported by referencing existing public ontologies. The RDF data are readily findable and accessible through the aforementioned link. Scripts used to create the RDF are made available at a code repository linked to this submission: https://gitlab.com/UM-CDS/FAIR-compliant_clinical_radiomics_and_DICOM_metadata.
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http://dx.doi.org/10.1002/mp.14322DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754296PMC
November 2020

Topographical Mapping of 436 Newly Diagnosed IDH Wildtype Glioblastoma With vs. Without MGMT Promoter Methylation.

Front Oncol 2020 12;10:596. Epub 2020 May 12.

Department of Radiology and Nuclear Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, Netherlands.

Omethylguanine-methyltransferase (MGMT) promoter methylation and isocitrate dehydrogenase (IDH) mutation status are important prognostic factors for patients with glioblastoma. There are conflicting reports about a differential topographical distribution of glioblastoma with vs. without MGMT promoter methylation, possibly caused by molecular heterogeneity in glioblastoma populations. We initiated this study to re-evaluate the topographical distribution of glioblastoma with vs. without MGMT promoter methylation in light of the updated WHO 2016 classification. Preoperative T2-weighted/FLAIR and postcontrast T1-weighted MRI scans of patients aged 18 year or older with IDH wildtype glioblastoma were collected. Tumors were semi-automatically segmented, and the topographical distribution between glioblastoma with vs. without MGMT promoter methylation was visualized using frequency heatmaps. Then, voxel-wise differences were analyzed using permutation testing with Threshold Free Cluster Enhancement. Four hundred thirty-six IDH wildtype glioblastoma patients were included; 211 with and 225 without MGMT promoter methylation. Visual examination suggested that when compared with MGMT unmethylated glioblastoma, MGMT methylated glioblastoma were more frequently located near bifrontal and left occipital periventricular area and less frequently near the right occipital periventricular area. Statistical analyses, however, showed no significant difference in topographical distribution between MGMT methylated vs. MGMT unmethylated glioblastoma. This study re-evaluated the topographical distribution of MGMT promoter methylation in 436 newly diagnosed IDH wildtype glioblastoma, which is the largest homogenous IDH wildtype glioblastoma population to date. There was no statistically significant difference in anatomical localization between MGMT methylated vs. unmethylated IDH wildtype glioblastoma.
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http://dx.doi.org/10.3389/fonc.2020.00596DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235346PMC
May 2020

The Effects of Weak and Strong CYP3A Induction by Rifampicin on the Pharmacokinetics of Five Progestins and Ethinylestradiol Compared to Midazolam.

Clin Pharmacol Ther 2020 Oct 11;108(4):798-807. Epub 2020 May 11.

Bayer AG, Berlin, Germany.

It is known that co-administration of CYP3A inducers may decrease the effectiveness of oral contraceptives containing progestins as mono-preparations or combined with ethinylestradiol. In a randomized clinical drug-drug interaction study, we investigated the effects of CYP3A induction on the pharmacokinetics of commonly used progestins and ethinylestradiol. Rifampicin was used to induce CYP3A. The progestins chosen as victim drugs were levonorgestrel, norethindrone, desogestrel, and dienogest as mono-products, and drospirenone combined with ethinylestradiol. Postmenopausal women (n = 12-14 per treatment group) received, in fixed sequence, a single dose of the victim drug plus midazolam without rifampicin, with rifampicin 10 mg/day (weak induction), and with rifampicin 600 mg/day (strong induction). The effects on progestin exposure were compared with the effects on midazolam exposure (as a benchmark). Unbound concentrations were evaluated for drugs binding to sex hormone binding globulin. Weak CYP3A induction, as confirmed by a mean decrease in midazolam exposure by 46%, resulted in minor changes in progestin exposure (mean decreases: 15-37%). Strong CYP3A induction, in contrast, resulted in mean decreases by 57-90% (mean decrease in midazolam exposure: 86%). Namely, the magnitude of the observed induction effects varied from weak to strong. Our data might provide an impetus to revisit the currently applied clinical recommendations for oral contraceptives, especially for levonorgestrel and norethindrone-containing products, and they might give an indication as to which progestin could be used, if requested, by women taking weak CYP3A inducers-although it is acknowledged that the exact exposure-response relationship for contraceptive efficacy is currently unclear for most progestins.
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http://dx.doi.org/10.1002/cpt.1848DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7540325PMC
October 2020

Microvascular damage assessed by optical coherence tomography angiography for glaucoma diagnosis: a systematic review of the most discriminative regions.

Acta Ophthalmol 2020 Sep 16;98(6):537-558. Epub 2020 Mar 16.

Research Group Ophthalmology, Department of Neurosciences, KU Leuven, Leuven, Belgium.

A growing number of studies have reported a link between vascular damage and glaucoma based on optical coherence tomography angiography (OCTA) imaging. This multitude of studies focused on different regions of interest (ROIs) which offers the possibility to draw conclusions on the most discriminative locations to diagnose glaucoma. The objective of this work was to review and analyse the discriminative capacity of vascular density, retrieved from different ROIs, on differentiating healthy subjects from glaucoma patients. PubMed was used to perform a systematic review on the analysis of glaucomatous vascular damage using OCTA. All studies up to 21 April 2019 were considered. The ROIs were analysed by region (macula, optic disc and peripapillary region), layer (superficial and deep capillary plexus, avascular, whole retina, choriocapillaris and choroid) and sector (according to the Garway-Heath map). The area under receiver operator characteristic curve (AUROC) and the statistical difference (p-value) were used to report the importance of each ROI for diagnosing glaucoma. From 96 screened studies, 43 were eligible for this review. Overall, the peripapillary region showed to be the most discriminative region with the highest mean AUROC (0.80 ± 0.09). An improvement of the AUROC from this region is observed when a sectorial analysis is performed, with the highest AUROCs obtained at the inferior and superior sectors of the superficial capillary plexus in the peripapillary region (0.86 ± 0.03 and 0.87 ± 0.10, respectively). The presented work shows that glaucomatous vascular damage can be assessed using OCTA, and its added value as a complementary feature for glaucoma diagnosis depends on the region of interest. A sectorial analysis of the superficial layer at the peripapillary region is preferable for assessing glaucomatous vascular damage.
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http://dx.doi.org/10.1111/aos.14392DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497179PMC
September 2020

Influence of the Insertion Site on Central Venous Catheter-Related Complications in Patients Undergoing Allogeneic Hematopoietic Cell Transplantation.

Biol Blood Marrow Transplant 2020 06 18;26(6):1189-1194. Epub 2020 Feb 18.

Department of Hematology and Oncology, University Hospital Mannheim, Mannheim, Germany. Electronic address:

Central venous catheters (CVCs) are extensively used in patients undergoing allogeneic hematopoietic cell transplantation (HCT). In these patients CVC are placed routinely either via the internal jugular vein (IJV) or the subclavian vein (SCV). Purpose of this study was to systematically analyze complications of CVC at different insertion sites in HCT recipients. In this retrospective analysis, all consecutive patients (n = 56) who received a CVC (n = 101) due to allogeneic HCT at our institution between January 2011 and June 2013 were included. Three-lumen standard, nontunneled CVCs were placed via either the IJV (n = 60; 59%) or the SCV (n = 41; 41%). Study endpoints were time to local inflammation at the insertion site, time to fever, time to a combined endpoint of inflammation and fever, central line-associated bloodstream infection (CLABSI), duration of catheterization, catheter lumen obstruction, deep-vein thrombosis, pneumothorax, and catheter-related death. The median duration of catheterization per CVC was almost identical for the IJV and SCV sites (18 days versus 17 days; P not significant). There were no differences in the frequency of CLABSI, deep-vein thrombosis, pneumothorax, and catheter lumen obstruction between IJV and SCV CVC insertion sites. None of the patients died due to a CVC-related cause. Local inflammation occurred less frequently (48% versus 71%; P = .025) and later (median time to local inflammation, 25 days versus 12 days; P = .01) in IJV CVCs versus SCV CVCs. There was a trend toward a median longer time to the occurrence of fever for IJV CVCs compared with SCV CVCs (20 days versus 13 days; P = .07). In the multivariate analysis, diagnosis of acute leukemia (hazard ratio [HR], 1.696; P = .036), SCV CVC (HR, 1.617; P  = .039), and neutropenic CVC-days (HR, 2.477; P = .01) were identified as risk factors for the occurrence of local inflammation or fever. In contrast to earlier studies in patients without hematologic malignancies, these data demonstrate that CVCs placed in the SCV are not superior over IJV CVCs. Moreover, local inflammation occurred earlier and more frequently in patients with an SCV CVC.
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http://dx.doi.org/10.1016/j.bbmt.2020.02.007DOI Listing
June 2020

Predicting Global Cognitive Decline in the General Population Using the Disease State Index.

Front Aging Neurosci 2019 23;11:379. Epub 2020 Jan 23.

Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.

Background: Identifying persons at risk for cognitive decline may aid in early detection of persons at risk of dementia and to select those that would benefit most from therapeutic or preventive measures for dementia.

Objective: In this study we aimed to validate whether cognitive decline in the general population can be predicted with multivariate data using a previously proposed supervised classification method: Disease State Index (DSI).

Methods: We included 2,542 participants, non-demented and without mild cognitive impairment at baseline, from the population-based Rotterdam Study (mean age 60.9 ± 9.1 years). Participants with significant global cognitive decline were defined as the 5% of participants with the largest cognitive decline per year. We trained DSI to predict occurrence of significant global cognitive decline using a large variety of baseline features, including magnetic resonance imaging (MRI) features, cardiovascular risk factors, APOE-ε4 allele carriership, gait features, education, and baseline cognitive function as predictors. The prediction performance was assessed as area under the receiver operating characteristic curve (AUC), using 500 repetitions of 2-fold cross-validation experiments, in which (a randomly selected) half of the data was used for training and the other half for testing.

Results: A mean AUC (95% confidence interval) for DSI prediction was 0.78 (0.77-0.79) using only age as input feature. When using all available features, a mean AUC of 0.77 (0.75-0.78) was obtained. Without age, and with age-corrected features and feature selection on MRI features, a mean AUC of 0.70 (0.63-0.76) was obtained, showing the potential of other features besides age.

Conclusion: The best performance in the prediction of global cognitive decline in the general population by DSI was obtained using only age as input feature. Other features showed potential, but did not improve prediction. Future studies should evaluate whether the performance could be improved by new features, e.g., longitudinal features, and other prediction methods.
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http://dx.doi.org/10.3389/fnagi.2019.00379DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989484PMC
January 2020

External validation of models for KIR2DS1/KIR3DL1-informed selection of hematopoietic cell donors fails.

Blood 2020 04;135(16):1386-1395

Department of Internal Medicine I, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.

Several studies suggest that harnessing natural killer (NK) cell reactivity mediated through killer cell immunoglobulin-like receptors (KIRs) could reduce the risk of relapse after allogeneic hematopoietic cell transplantation. Based on one promising model, information on KIR2DS1 and KIR3DL1 and their cognate ligands can be used to classify donors as KIR-advantageous or KIR-disadvantageous. This study was aimed at externally validating this model in unrelated donor hematopoietic cell transplantation. The impact of the predictor on overall survival (OS) and relapse incidence was tested in a Cox regression model adjusted for patient age, a modified disease risk index, Karnofsky performance status, donor age, HLA match, sex match, cytomegalovirus match, conditioning intensity, type of T-cell depletion, and graft type. Data from 2222 patients with acute myeloid leukemia or myelodysplastic syndrome were analyzed. KIR genes were typed by using high-resolution amplicon-based next-generation sequencing. In univariable analyses and subgroup analyses, OS and the cumulative incidence of relapse of patients with a KIR-advantageous donor were comparable to patients with a KIR-disadvantageous donor. The adjusted hazard ratio from the multivariable Cox regression model was 0.99 (Wald test, P = .93) for OS and 1.04 (Wald test, P = .78) for relapse incidence. We also tested the impact of activating donor KIR2DS1 and inhibition by KIR3DL1 separately but found no significant impact on OS and the risk of relapse. Thus, our study shows that the proposed model does not universally predict NK-mediated disease control. Deeper knowledge of NK-mediated alloreactivity is necessary to predict its contribution to graft-versus-leukemia reactions and to eventually use KIR genotype information for donor selection.
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http://dx.doi.org/10.1182/blood.2019002887DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162689PMC
April 2020

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data.

Sci Rep 2019 12 27;9(1):20038. Epub 2019 Dec 27.

Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.

Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and current treatment options are limited to symptomatic relief. Prediction of OA progression is a very challenging and timely issue, and it could, if resolved, accelerate the disease modifying drug development and ultimately help to prevent millions of total joint replacement surgeries performed annually. Here, we present a multi-modal machine learning-based OA progression prediction model that utilises raw radiographic data, clinical examination results and previous medical history of the patient. We validated this approach on an independent test set of 3,918 knee images from 2,129 subjects. Our method yielded area under the ROC curve (AUC) of 0.79 (0.78-0.81) and Average Precision (AP) of 0.68 (0.66-0.70). In contrast, a reference approach, based on logistic regression, yielded AUC of 0.75 (0.74-0.77) and AP of 0.62 (0.60-0.64). The proposed method could significantly improve the subject selection process for OA drug-development trials and help the development of personalised therapeutic plans.
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http://dx.doi.org/10.1038/s41598-019-56527-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934728PMC
December 2019

Standardized monitoring of cytomegalovirus-specific immunity can improve risk stratification of recurrent cytomegalovirus reactivation after hematopoietic stem cell transplantation.

Haematologica 2021 Feb 1;106(2):363-374. Epub 2021 Feb 1.

Dpt of Internal Medicine III, Hematology and Oncology, University Medical Center Regensburg, Germany.

Recurrence of cytomegalovirus reactivation remains a major cause of morbidity and mortality following allogeneic hematopoietic stem cell transplantation. Monitoring cytomegalovirus-specific cellular immunity using a standardized assay might improve the risk stratification of patients. A prospective multicenter study was conducted in 175 intermediate- and high-risk allogeneic hematopoietic stem cell transplant recipients under preemptive antiviral therapy. Cytomegalovirus-specific cellular immunity was measured using a standardized IFN-γ ELISpot assay (T-Track® CMV). Primary aim was to evaluate the suitability of measuring cytomegalovirus-specific immunity after end of treatment for a first cytomegalovirus reactivation to predict recurrent reactivation. 40/101 (39.6%) patients with a first cytomegalovirus reactivation experienced recurrent reactivations, mainly in the high-risk group (cytomegalovirus-seronegative donor/cytomegalovirus-seropositive recipient). The positive predictive value of T-Track® CMV (patients with a negative test after the first reactivation experienced at least one recurrent reactivation) was 84.2% in high-risk patients. Kaplan-Meier analysis revealed a higher probability of recurrent cytomegalovirus reactivation in high-risk patients with a negative test after the first reactivation (hazard ratio 2.73; p=0.007). Interestingly, a post-hoc analysis considering T-Track® CMV measurements at day 100 post-transplantation, a time point highly relevant for outpatient care, showed a positive predictive value of 90.0% in high-risk patients. Our results indicate that standardized cytomegalovirus-specific cellular immunity monitoring may allow improved risk stratification and management of recurrent cytomegalovirus reactivation after hematopoietic stem cell transplantation. This study was registered at www.clinicaltrials.gov as #NCT02156479.
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http://dx.doi.org/10.3324/haematol.2019.229252DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849569PMC
February 2021

An Efficient Method for Multi-Parameter Mapping in Quantitative MRI Using B-Spline Interpolation.

IEEE Trans Med Imaging 2020 05 21;39(5):1681-1689. Epub 2019 Nov 21.

Quantitative MRI methods that estimate multiple physical parameters simultaneously often require the fitting of a computational complex signal model defined through the Bloch equations. Repeated Bloch simulations can be avoided by matching the measured signal with a precomputed signal dictionary on a discrete parameter grid (i.e. lookup table) as used in MR Fingerprinting. However, accurate estimation requires discretizing each parameter with a high resolution and consequently high computational and memory costs for dictionary generation, storage, and matching. Here, we reduce the required parameter resolution by approximating the signal between grid points through B-spline interpolation. The interpolant and its gradient are evaluated efficiently which enables a least-squares fitting method for parameter mapping. The resolution of each parameter was minimized while obtaining a user-specified interpolation accuracy. The method was evaluated by phantom and in-vivo experiments using fully-sampled and undersampled unbalanced (FISP) MR fingerprinting acquisitions. Bloch simulations incorporated relaxation effects (T,T) , proton density (PD ) , receiver phase ( φ ), transmit field inhomogeneity ( B ), and slice profile. Parameter maps were compared with those obtained from dictionary matching, where the parameter resolution was chosen to obtain similar signal (interpolation) accuracy. For both the phantom and the in-vivo acquisition, the proposed method approximated the parameter maps obtained through dictionary matching while reducing the parameter resolution in each dimension ( T,T,B ) by - on average - an order of magnitude. In effect, the applied dictionary was reduced from 1.47GB to 464KB . Furthermore, the proposed method was equally robust against undersampling artifacts as dictionary matching. Dictionary fitting with B-spline interpolation reduces the computational and memory costs of dictionary-based methods and is therefore a promising method for multi-parametric mapping.
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http://dx.doi.org/10.1109/TMI.2019.2954751DOI Listing
May 2020

Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm.

Clin Cancer Res 2019 12 23;25(24):7455-7462. Epub 2019 Sep 23.

Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, the Netherlands.

Purpose: Patients with 1p/19q codeleted low-grade glioma (LGG) have longer overall survival and better treatment response than patients with 1p/19q intact tumors. Therefore, it is relevant to know the 1p/19q status. To investigate whether the 1p/19q status can be assessed prior to tumor resection, we developed a machine learning algorithm to predict the 1p/19q status of presumed LGG based on preoperative MRI.

Experimental Design: Preoperative brain MR images from 284 patients who had undergone biopsy or resection of presumed LGG were used to train a support vector machine algorithm. The algorithm was trained on the basis of features extracted from post-contrast T1-weighted and T2-weighted MR images and on patients' age and sex. The performance of the algorithm compared with tissue diagnosis was assessed on an external validation dataset of MR images from 129 patients with LGG from The Cancer Imaging Archive (TCIA). Four clinical experts also predicted the 1p/19q status of the TCIA MR images.

Results: The algorithm achieved an AUC of 0.72 in the external validation dataset. The algorithm had a higher predictive performance than the average of the neurosurgeons (AUC 0.52) but lower than that of the neuroradiologists (AUC of 0.81). There was a wide variability between clinical experts (AUC 0.45-0.83).

Conclusions: Our results suggest that our algorithm can noninvasively predict the 1p/19q status of presumed LGG with a performance that on average outperformed the oncological neurosurgeons. Evaluation on an independent dataset indicates that our algorithm is robust and generalizable.
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http://dx.doi.org/10.1158/1078-0432.CCR-19-1127DOI Listing
December 2019