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Theranostics 2023; 13(5):1594-1606. doi:10.7150/thno.81938 This issue Cite

Research Paper

Multiparametric magnetic resonance imaging for radiation therapy response monitoring in soft tissue sarcomas: a histology and MRI co-registration algorithm

Matthias Jung^1,2*✉, Balazs Bogner^1*, Thierno D. Diallo¹, Suam Kim¹, Philipp Arnold¹, Hannah Füllgraf³, Konrad Kurowski³, Peter Bronsert^3,4,5, Pia M. Jungmann¹, Jurij Kiefer⁶, Daniel Kraus⁶, Philipp Rovedo⁷, Marco Reisert^7,8, Steffen U. Eisenhardt⁶, Fabian Bamberg¹, Matthias Benndorf^1*, Alexander Runkel^2,6*

1. Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Germany
2. Berta-Ottenstein-Programme, University of Freiburg, Faculty of Medicine, Freiburg, Germany
3. Institute of Surgical Pathology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Germany
4. Tumorbank Comprehensive Cancer Center Freiburg, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Germany
5. Core Facility for Histopathology and Digital Pathology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Germany
6. Department of Plastic and Hand Surgery, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Germany
7. Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Germany
8. Department of Stereotactic and Functional Neurosurgery, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Germany
*Contributed equally

✉ Corresponding author: Matthias Jung, MD, Department of Diagnostic and Interventional Radiology, University of Freiburg, Hugstetter Strasse 55, 79106 Freiburg, Germany. Phone: +49 761 270-38190; matthias.jungde

Abstract

Rationale: To establish a spatially exact co-registration procedure between in vivo multiparametric magnetic resonance imaging (mpMRI) and (immuno)histopathology of soft tissue sarcomas (STS) to identify imaging parameters that reflect radiation therapy response of STS.

Methods: The mpMRI-Protocol included diffusion-weighted (DWI), intravoxel-incoherent motion (IVIM), and dynamic contrast-enhancing (DCE) imaging. The resection specimen was embedded in 6.5% agarose after initial fixation in formalin. To ensure identical alignment of histopathological sectioning and in vivo imaging, an ex vivo MRI scan of the specimen was rigidly co-registered with the in vivo mpMRI. The deviating angulation of the specimen to the in vivo location of the tumor was determined. The agarose block was trimmed accordingly. A second ex vivo MRI in a dedicated localizer with a 4 mm grid was performed, which was matched to a custom-built sectioning machine. Microtomy sections were stained with hematoxylin and eosin. Immunohistochemical staining was performed with anti-ALDH1A1 antibodies as a radioresistance and anti-MIB1 antibodies as a proliferation marker. Fusion of the digitized microtomy sections with the in vivo mpMRI was accomplished through nonrigid co-registration to the in vivo mpMRI. Co-registration accuracy was qualitatively assessed by visual assessment and quantitatively evaluated by computing target registration errors (TRE).

Results: The study sample comprised nine tumor sections from three STS patients. Visual assessment after nonrigid co-registration showed a strong morphological correlation of the histopathological specimens with ex vivo MRI and in vivo mpMRI after neoadjuvant radiation therapy. Quantitative assessment of the co-registration procedure using TRE analysis of different pairs of pathology and MRI sections revealed highly accurate structural alignment, with a total median TRE of 2.25 mm (histology - ex vivo MRI), 2.22 mm (histology - in vivo mpMRI), and 2.02 mm (ex vivo MRI - in vivo mpMRI). There was no significant difference between TREs of the different pairs of sections or caudal, middle, and cranial tumor parts, respectively.

Conclusion: Our initial results show a promising approach to obtaining accurate co-registration between histopathology and in vivo MRI for STS. In a larger cohort of patients, the method established here will enable the prospective identification and validation of in vivo imaging biomarkers for radiation therapy response prediction and monitoring in STS patients via precise molecular and cellular correlation.

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