Dataset Information

The dataset on the clipped cerebral aneurysm and their radiological findings in three-dimensional computed tomography, time-of-flight magnetic resonance angiography (TOF-MRA), and Pointwise Encoding Time Reduction with Radial Acquisition (PETRA)-MRA.

ABSTRACT: These data present the 141 intracranial arterial branches' visibilities near the 72 cerebral aneurysms in postoperative 58 patients treated with titanium or cobalt-chromium-nickel-molybdenum (CCNM) alloy clips. The visibilities were evaluated using time-of-flight magnetic resonance angiography (TOF-MRA), pointwise encoding time reduction with radial acquisition (PETRA)-MRA, which uses MRA with ultrashort echo time (UTE-MRA) and subtraction technique between saturated and non-saturated images, and three-dimensional computed tomography angiography (3DCTA). We retrospectively acquired the data from the medical records of Suwa Red Cross Hospital. Each method's appearance was compared, and associations between visibility on PETRA-MRA, arterial diameter, clip numbers, clip shapes, clip materials, and amounts of hematoma were summarized. Our article on PETRA-MRA's usefulness for proximal and branched arteries evaluation after cerebral aneurysm clipping [1] was based on these data. This dataset would be useful for reference value for other neurosurgeons or radiologists for further analysis on PETRA-MRA and another UTE-MRA like SILENT-MRA after cerebral aneurysm clipping.

SUBMITTER: Nishikawa A

PROVIDER: S-EPMC7907704 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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The dataset on the clipped cerebral aneurysm and their radiological findings in three-dimensional computed tomography, time-of-flight magnetic resonance angiography (TOF-MRA), and Pointwise Encoding Time Reduction with Radial Acquisition (PETRA)-MRA.

Nishikawa Akihiro A Katsuki Masahito M Kakizawa Yukinari Y Wada Naomichi N Yamamoto Yasunaga Y Uchiyama Toshiya T

Data in brief 20210213

These data present the 141 intracranial arterial branches' visibilities near the 72 cerebral aneurysms in postoperative 58 patients treated with titanium or cobalt-chromium-nickel-molybdenum (CCNM) alloy clips. The visibilities were evaluated using time-of-flight magnetic resonance angiography (TOF-MRA), pointwise encoding time reduction with radial acquisition (PETRA)-MRA, which uses MRA with ultrashort echo time (UTE-MRA) and subtraction technique between saturated and non-saturated images, an ...[more]

PMID: 33665265

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Project description:PurposeTo improve the quantitative accuracy and diagnostic confidence of PET images reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image enhancement (DL-ToF).MethodsA total of 273 [18F]-FDG PET scans were used, including data from 6 centres equipped with GE Discovery MI ToF scanners. PET data were reconstructed using the block-sequential-regularised-expectation-maximisation (BSREM) algorithm with and without ToF. The images were then split into training (n = 208), validation (n = 15), and testing (n = 50) sets. Three DL-ToF models were trained to transform non-ToF BSREM images to their target ToF images with different levels of DL-ToF strength (low, medium, high). The models were objectively evaluated using the testing set based on standardised uptake value (SUV) in 139 identified lesions, and in normal regions of liver and lungs. Three radiologists subjectively rated the models using testing sets based on lesion detectability, diagnostic confidence, and image noise/quality.ResultsThe non-ToF, DL-ToF low, medium, and high methods resulted in - 28 ± 18, - 28 ± 19, - 8 ± 22, and 1.7 ± 24% differences (mean; SD) in the SUVmax for the lesions in testing set, compared to ToF-BSREM image. In background lung VOIs, the SUVmean differences were 7 ± 15, 0.6 ± 12, 1 ± 13, and 1 ± 11% respectively. In normal liver, SUVmean differences were 4 ± 5, 0.7 ± 4, 0.8 ± 4, and 0.1 ± 4%. Visual inspection showed that our DL-ToF improved feature sharpness and convergence towards ToF reconstruction. Blinded clinical readings of testing sets for diagnostic confidence (scale 0-5) showed that non-ToF, DL-ToF low, medium, and high, and ToF images scored 3.0, 3.0, 4.1, 3.8, and 3.5 respectively. For this set of images, DL-ToF medium therefore scored highest for diagnostic confidence.ConclusionDeep learning-based image enhancement models may provide converged ToF-equivalent image quality without ToF reconstruction. In clinical scoring DL-ToF-enhanced non-ToF images (medium and high) on average scored as high as, or higher than, ToF images. The model is generalisable and hence, could be applied to non-ToF images from BGO-based PET/CT scanners.

Dataset Information

The dataset on the clipped cerebral aneurysm and their radiological findings in three-dimensional computed tomography, time-of-flight magnetic resonance angiography (TOF-MRA), and Pointwise Encoding Time Reduction with Radial Acquisition (PETRA)-MRA.

Publications

The dataset on the clipped cerebral aneurysm and their radiological findings in three-dimensional computed tomography, time-of-flight magnetic resonance angiography (TOF-MRA), and Pointwise Encoding Time Reduction with Radial Acquisition (PETRA)-MRA.

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