Improving PET spatial resolution and detectability for prostate cancer imaging
| Autor: | C. Pettinato, Peter L. Choyke, Christian Michel, Stefano Fanti, Lars Eriksson, Maurizio Conti, Stephen Adler, Harshali Bal, Michael E. Casey, Guerin Laura |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Male
Computer science Image processing Article Prostate cancer Limit of Detection Biopsy medicine Image Processing Computer-Assisted Humans Radiology Nuclear Medicine and imaging Image resolution Radiological and Ultrasound Technology medicine.diagnostic_test Pixel business.industry Resolution (electron density) Cancer Prostatic Neoplasms medicine.disease Positron emission tomography Positron-Emission Tomography Tomography Noise (video) Nuclear medicine business Emission computed tomography |
| Zdroj: | Phys Med Biol |
| Popis: | Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%. |
| Databáze: | OpenAIRE |
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