Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results

Sagiyama, Koji; Watanabe, Yuji; Kamei, Ryotaro; Hong, Su Jin; Kawanami, Satoshi; Matsumoto, Yoshihiro; Honda, Hiroshi

doi:10.1007/s00330-017-4912-y

Cited by 22 publications

(10 citation statements)

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“…All patients were scanned using PET/MRI within 30 min after the PET/CT exam using the Ingenuity TF PET/MRI system (Philips Healthcare). After the scout image was taken and a 3D-T1-weighted image was acquired to correct attenuation [10], patients underwent PET imaging with 3D-ordered subset expectation maximisation (3D-OSEM) and time-of-flight. The field-of-view for the PET imaging was 576 × 576 mm 2 (recon.…”

Section: Pet/mri Systemmentioning

confidence: 99%

“…This may be an ideal imaging tool for EZ detection because it can evaluate both anatomical and functional information simultaneously. Hybrid PET/MRI systems have already been applied in cancer research, such as in brain, head and neck, lung, musculoskeletal, and pancreatic cancers [10]. To the best of our knowledge, there are no data directly comparing the diagnostic accuracy of FDG-PET/CT and FDG-PET/MRI in patients with histopathologically confirmed epilepsy as a reference standard.…”

Section: Introductionmentioning

confidence: 99%

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Diagnostic accuracy for the epileptogenic zone detection in focal epilepsy could be higher in FDG-PET/MRI than in FDG-PET/CT

et al. 2020

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Objectives To examine the utility of FDG-PET/MRI in patients with epilepsy by comparing the diagnostic accuracy of PET/MRI and PET/CT in epileptogenic zone (EZ) detection. Methods This prospective study included 31 patients (17 males, 14 females) who underwent surgical resection for EZ. All patients were first scanned using FDG-PET/CT followed immediately with FDG-PET/MRI. Two series of PET plus standalone MR images were interpreted independently by five board-certified radiologists. A 4-point visual score was used to assess image quality. Sensitivities and visual scores from both PETs and standalone MRI were compared using the McNemar test with Bonferroni correction and Dunn’s multiple comparisons test. Results The EZs were confirmed histopathologically via resection as hippocampal sclerosis (n = 11, 35.5%), gliosis (n = 8, 25.8%), focal cortical dysplasia (n = 6, 19.4%), and brain tumours (n = 6, 19.4%) including cavernous haemangioma (n = 3), dysembryoplastic neuroepithelial tumour (n = 1), ganglioglioma (n = 1), and polymorphous low-grade neuroepithelial tumour of the young (n = 1). The sensitivity of FDG-PET/MRI was significantly higher than that of FDG-PET/CT and standalone MRI (FDG-PET/MRI vs. FDG-PET/CT vs. standalone MRI; 77.4–90.3% vs. 58.1–64.5% vs. 45.2–80.6%, p < 0.0001, respectively). The visual scores derived from FDG-PET/MRI were significantly higher than those of FDG-PET/CT, as well as standalone MRI (2.8 ± 1.2 vs. 2.0 ± 1.1 vs. 2.1 ± 1.2, p < 0.0001, respectively). Compared to FDG-PET/CT, FDG-PET/MRI increased the visual score (51.9%, increased visual scores of 2 and 3). Conclusions The diagnostic accuracy for the EZ detection in focal epilepsy could be higher in FDG-PET/MRI than in FDG-PET/CT. Key Points • Sensitivity of FDG-PET/MRI was significantly higher than that of FDG-PET/CT and standalone MRI (FDG-PET/MRI vs. FDG-PET/CT vs. standalone MRI; 77.4–90.3% vs. 58.1–64.5% vs. 45.2–80.6%, p < 0.0001, respectively). • Visual scores derived from FDG-PET/MRI were significantly higher than those of FDG-PET/CT and standalone MRI (2.8 ± 1.2 vs. 2.0 ± 1.1 vs. 2.1 ± 1.2, p < 0.0001, respectively). • Compared to FDG-PET/CT, FDG-PET/MRI increased the visual score (51.9%, increased visual scores of 2 and 3).

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Section: Pet/mri Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Diagnostic accuracy for the epileptogenic zone detection in focal epilepsy could be higher in FDG-PET/MRI than in FDG-PET/CT

et al. 2020

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“…Diese Methode könnte nützlich sein, um diese Tumorgruppen voneinander trennen zu können. Dennoch muss diese Fragestellung in weiteren "Voxel-by-Voxel"-Analysen erforscht werden [22].…”

Section: "Machine Learning" Durch Die Fdg-pet/ Ct Bei Bronchialkarzinunclassified

“…Dies ist ein wichtiger Aspekt für zukünftige Forschungsfelder [10]. Des Weiteren konnte schon die prognostische Wertigkeit der Texturanalyse der Diffusions-und multiplanaren MRT gezeigt werden [14,22,25].…”

Section: "Machine Learning" Durch Die Fdg-pet/ Ct Bei Bronchialkarzinunclassified

Die Wichtigkeit des „Machine Learning“ und der Texturanalyse in der Onkologie anhand der Fusionsbildgebung

2019

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ZusammenfassungDas Gebiet der Onkologie hat sich in den letzten Jahrzehnten deutlich weiterentwickelt. Klassische Chemotherapien werden aktuell zunehmend durch neue, zielgerichtete „State-of-the-Art“-Therapien ersetzt. Diese zielgerichteten Therapien basieren auf einer Zusammenführung von Informationen aus der molekularen Pathologie, spezifischen Tumormarkern und fortgeschrittener Bildgebungstechnik. PET/CT und PET/MRT bieten aufseiten der Bildgebung hierbei die einzigartige Möglichkeit funktionelle und anatomische Informationen in einer Untersuchung zu vereinen. Bis vor Kurzem wurden PET- und CT/MRT-Bilder meistens binär (Tumor ja/nein) analysiert ohne wesentliche Informationen über die räumliche Verteilung von relevanten Bildparametern innerhalb einer Tumorläsion zu erheben. Mit der Entwicklung und dem Voranschreiten von Texturanalyse-Softwares der nächsten Generation ist es jetzt möglich eine Tumorläsion auch bez. ihrer Heterogenität und Expression spezifischer Zielstrukturen auf den Tumorzellen zu charakterisieren. Jedoch gibt es bei diesem Vorgehen mehrere Herausforderungen, wobei die wichtigste ist, die durch die Texturanalysen generierten großen Datenmengen zu interpretieren. Der Erfolg des „Machine Learning“/des maschinellen Lernens in anderen Gebieten der Wissenschaft, welche mit ähnlich großen Datenmengen umgehen müssen, hat ein neues Kapitel in der zielgerichteten Onkologie mit radioaktiv-markierten Proben eröffnet. In unserem Review-Artikel haben wir das primäre Ziel, aktuelle Literatur und zukünftige Trends der Integration von „Machine Learning“ in der Onkologie durch die Nutzung der Fusionsbildgebung mittels PET/CT oder PET/MRT zusammengefasst.

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“…Sagiyama et al [134] performed a prospective study of 35 patients with soft tissue tumors who underwent the PET/MRI system to evaluate the usefulness of voxel-based PET and MRI parameters for differentiating high-grade from lowgrade and intermediate-grade sarcomas. Using the SUV on PET and the apparent diffusion coefficient (ADC) on MRI for every voxel of tumor lesions, the authors calculated the correlation coefficients between SUV and ADC and heterogeneity, defined as the elliptical 95% area of bivariate normal distribution of SUV and ADC, for each patient, in addition to tumor volume, maximum SUV, and minimum ADC.…”

Section: Sarcomamentioning

confidence: 99%

Radiomics in Oncological PET/CT: Clinical Applications

Lee

2017

Nucl Med Mol Imaging

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F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is widely used for staging, evaluating treatment response, and predicting prognosis in malignant diseases. FDG uptake and volumetric PET parameters such as metabolic tumor volume have been used and are still used as conventional PET parameters to assess biological characteristics of tumors. However, in recent years, additional features derived from PET images by computational processing have been found to reflect intratumoral heterogeneity, which is related to biological tumor features, and to provide additional predictive and prognostic information, which leads to the concept of radiomics. In this review, we focus on recent clinical studies of malignant diseases that investigated intratumoral heterogeneity on PET/CT, and we discuss its clinical role in various cancers.

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Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results

Cited by 22 publications

References 30 publications

Diagnostic accuracy for the epileptogenic zone detection in focal epilepsy could be higher in FDG-PET/MRI than in FDG-PET/CT

Diagnostic accuracy for the epileptogenic zone detection in focal epilepsy could be higher in FDG-PET/MRI than in FDG-PET/CT

Die Wichtigkeit des „Machine Learning“ und der Texturanalyse in der Onkologie anhand der Fusionsbildgebung

Radiomics in Oncological PET/CT: Clinical Applications

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