Matthias Boschheidgen

Matthias Boschheidgen

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 June 2021 in Diagnostics
Verified
Journal Article
Open access
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KRKarl Ludger Radke
Karl Ludger Radke
LWLena Wilms
Lena Wilms
Sven NebelungSven Nebelung
Sven Nebelung
DADaniel Abrar
Daniel Abrar
CSChristoph Schleich
Christoph Schleich
AMAnja Müller-Lutz
Anja Müller-Lutz
While morphologic magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of ligamentous wrist injuries, it is merely static and incapable of diagnosing dynamic wrist instability. Based on real-time MRI and algorithm-based image post-processing in terms of convolutional neural networks (CNNs), this study aims to develop and validate an automatic technique to quantify wrist movement. A total of 56 bilateral wrists (28 healthy volunteers) were imaged during continuous and alternating maximum ulnar and radial abduction. Following CNN-based automatic segmentations of carpal bone contours, scapholunate and lunotriquetral gap widths were quantified based on dedicated algorithms and as a function of wrist position. Automatic segmentations were in excellent agreement with manual reference segmentations performed by two radiologists as indicated by Dice similarity coefficients of 0.96 ± 0.02 and consistent and unskewed Bland–Altman plots. Clinical applicability of the framework was assessed in a patient with diagnosed scapholunate ligament injury. Considerable increases in scapholunate gap widths across the range-of-motion were found. In conclusion, the combination of real-time wrist MRI and the present framework provides a powerful diagnostic tool for dynamic assessment of wrist function and, if confirmed in clinical trials, dynamic carpal instability that may elude static assessment using clinical-standard imaging modalities.

1 November 2021 in European Journal of Radiology
Verified
Journal Article
Closed access
MBMatthias Boschheidgen
Matthias Boschheidgen
TUT. Ullrich
T. Ullrich
DBD. Blondin
D. Blondin
FZFarid Ziayee
Farid Ziayee
LKL. Kasprowski
L. Kasprowski
LSLars Schimmöller
Lars Schimmöller

23 October 2020 in British Journal of Radiology
Verified
Journal Article
Closed access
ASAndrea Steuwe
Andrea Steuwe
MWMarie Weber
Marie Weber
OBOliver Thomas Bethge
Oliver Thomas Bethge
CRChristin Rademacher
Christin Rademacher
MBMatthias Boschheidgen
Matthias Boschheidgen
JAJoel Aissa
Joel Aissa
Objectives: Modern reconstruction and post-processing software aims at reducing image noise in CT images, potentially allowing for a reduction of the employed radiation exposure. This study aimed at assessing the influence of a novel deep-learning based software on the subjective and objective image quality compared to two traditional methods [filtered back-projection (FBP), iterative reconstruction (IR)]. Methods: In this institutional review board-approved retrospective study, abdominal low-dose CT images of 27 patients (mean age 38 ± 12 years, volumetric CT dose index 2.9 ± 1.8 mGy) were reconstructed with IR, FBP and, furthermore, post-processed using a novel software. For the three reconstructions, qualitative and quantitative image quality was evaluated by means of CT numbers, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in six different ROIs. Additionally, the reconstructions were compared using SNR, peak SNR, root mean square error and mean absolute error to assess structural differences. Results: On average, CT numbers varied within 1 Hounsfield unit (HU) for the three assessed methods in the assessed ROIs. In soft tissue, image noise was up to 42% lower compared to FBP and up to 27% lower to IR when applying the novel software. Consequently, SNR and CNR were highest with the novel software. For both IR and the novel software, subjective image quality was equal but higher than the image quality of FBP-images. Conclusion: The assessed software reduces image noise while maintaining image information, even in comparison to IR, allowing for a potential dose reduction of approximately 20% in abdominal CT imaging. Advances in knowledge: The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information. The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.

2 June 2025 in European Urology
Verified
Journal Article
Open access
RARouvier Al-Monajjed
Rouvier Al-Monajjed
MBMatthias Boschheidgen
Matthias Boschheidgen
JLJale Lakes
Jale Lakes
AKAgne Krilaviciute
Agne Krilaviciute
JRJan-Philipp Radtke
Jan-Philipp Radtke
PAPeter Albers
Peter Albers
The optimal approach for prostate cancer (PC) screening, including the ideal starting age and most effective diagnostic method, remains under investigation. We evaluated the diagnostic performance of magnetic resonance imaging (MRI)-targeted biopsy (TBx) and systematic biopsy (SBx) in detecting clinically significant PC (csPC) in men aged 45-50 yr in PROBASE, a prospective, randomized trial of a risk-adapted screening strategy. A total of 525 participants with elevated prostate-specific antigen (≥3 ng/ml) underwent MRI followed by biopsy. Of the 209 PC cases detected, 148 (71%) were csPC. SBx identified 94% of csPC cases, while TBx detected 74% (p ≤ 0.05). SBx also diagnosed significantly more low-grade PCs than TBx (p < 0.001). These findings suggest that relying solely on MRI-TBx may lead to underdiagnosis of csPC. Combining SBx with TBx remains the most effective strategy for early detection of PC in young men undergoing screening. Future research should explore optimization strategies to reduce unnecessary biopsies while maintaining high detection rates for csPC. This trial is registered on the ISRCTN registry as ISRCTN37591328 (https://www.isrctn.com/ISRCTN37591328). The study protocol can be accessed at https://doi.org/10.1016/j.eururo.2013.05.022.

14 December 2023 in Clinical Radiology
Verified
Journal Article
Closed access
FZFarid Ziayee
Farid Ziayee
LSLars Schimmöller
Lars Schimmöller
MBMatthias Boschheidgen
Matthias Boschheidgen
LKL. Kasprowski
L. Kasprowski
RAR. Al-Monajjed
R. Al-Monajjed
TUT. Ullrich
T. Ullrich

22 March 2024 in European Journal of Radiology
Verified
Journal Article
Open access
MQM. Quentin
M. Quentin
MBMatthias Boschheidgen
Matthias Boschheidgen
JRJ.P. Radtke
J.P. Radtke
FSF. Spohn
F. Spohn
TUTim Ullrich
Tim Ullrich
LSLars Schimmöller
Lars Schimmöller
Purpose: Patients with suspicion of clinically significant prostate cancer (csPC) on multiparametric prostate MRI (mpMRI) but negative or inconclusive MRI/US fusion-guided biopsy (FB) can be challenging in clinical practice. To assess the utility of MRI in -bore biopsy (IB) in patients with discordant imaging and histopathological findings after FB. Methods: Consecutive patients with Prostate Imaging Reporting and Data System (PI-RADS) category 4 or 5 on mpMRI at 3T after FB without histologically confirmed csPC who underwent IB between 01/2014 and 05/2022, were retrospectively included. The primary objective was to assess the detection rate of csPC. Secondary objectives were to analyze clinical parameters, MRI parameters, and lesion localization. Results: In the final cohort of 51 patients, the IB resulted in an overall detection rate of 71% for PC and 47% for csPC. Furthermore, in 55% of cases with initial low-grade PC, the Gleason score was upgraded after IB. CsPC was often detected apical and/or anterior. The detection rate for PC was 58% in PI-RADS category 4 and 94% in PIRADS category 5 (csPC 39% and 61%, respectively). Patients with csPC had statistically significant smaller prostate volumes, a higher PI-RADS category, a higher prostate-specific antigen density (PSAD), and were older. Conclusions: For a relevant proportion of patients with PI-RADS category 4 or 5 and negative or inconclusive findings on previous FB, but with persistent suspicion of csPC, a subsequent IB verified the presence of csPC. Therefore, IB can be a backup in cases of uncertainty.