Literature DB >> 15747142

Improved correlation of histological data with DCE MRI parameter maps by 3D reconstruction, reslicing and parameterization of the histological images.

Fabian Kiessling1, Martin Le-Huu, Tobias Kunert, Matthias Thorn, Silvia Vosseler, Kerstin Schmidt, Johannes Hoffend, Hans-Peter Meinzer, Norbert E Fusenig, Wolfhard Semmler.   

Abstract

Due to poor correlation of slice thickness and orientation, verification of radiological methods with histology is difficult. Thus, a procedure for three-dimensional reconstruction, reslicing and parameterization of histological data was developed, enabling a proper correlation with radiological data. Two different subcutaneous tumors were examined by MR microangiography and DCE-MRI, the latter being post-processed using a pharmacokinetic two-compartment model. Subsequently, tumors were serially sectioned and vessels stained with immunofluorescence markers. A ray-tracing algorithm performed three-dimensional visualization of the histological data, allowing virtually reslicing to thicker sections analogous to MRI slice geometry. Thick slices were processed as parameter maps color coding the marker density in the depth of the slice. Histological 3D reconstructions displayed the diffuse angioarchitecture of malignant tumors. Resliced histological images enabled specification of high enhancing areas seen on MR microangiography as large single vessels or vessel assemblies. In orthogonally reconstructed histological slices, single vessels were delineated. ROI analysis showed significant correlation between histological parameter maps of vessel density and MR parameter maps (r=0.83, P=0.05). The 3D approach to histology improves correlation of histological and radiological data due to proper matching of slice geometry. This method can be used with any histological stain, thus enabling a multivariable correlation of non-invasive data and histology.

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Year:  2005        PMID: 15747142     DOI: 10.1007/s00330-005-2701-5

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


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