Index of content:
Volume 40, Issue 6, June 2013
Prostate cancer ranks as one of the most common malignancies and currently represents the second leading cancer-specific cause of death in men. The current use of single modality transrectal ultrasound (TRUS) for biopsy guidance has a limited sensitivity and specificity for accurately identifying cancerous lesions within the prostate. This study introduces a novel prostate cancer imaging method that combines TRUS with electrical impedance tomography (EIT) and reports on initial clinical findings based onin vivo measurements.Methods:
The ultrasound system provides anatomic information, which guides EIT image reconstruction. EIT reconstructions are correlated with semiquantitative pathological findings. Thin plate spline warping transformations are employed to overlay electrical impedance images and pathological maps describing the spatial distribution of prostate cancer, with the latter used as reference for data analysis. Clinical data were recorded from a total of 50 men prior to them undergoing radical prostatectomy for prostate cancer treatment. Student'st-tests were employed to statistically examine the electrical property difference between cancerous tissue and benign tissue as defined through histological assessment of the excised gland.Results:
Example EIT reconstructions are presented along with a statistical analysis comparing EIT and pathology. An average transformation error of 1.67% is found when 381 spatially coregistered pathological images are compared with their target EIT reconstructed counterparts. At EIT signal frequencies of 0.4, 3.2, and 25.6 kHz, paired-testing demonstrated that the conductivity of cancerous regions is significantly greater than that of benign regions ( p < 0.0304).Conclusions:
These preliminary clinical findings suggest the potential benefits electrical impedance measurements might have for prostate cancer detection.
- REVIEW ARTICLE (Online only)
40(2013); http://dx.doi.org/10.1118/1.4800806View Description Hide Description
In this paper, the authors review the field of resolution modeling in positron emission tomography (PET) image reconstruction, also referred to as point-spread-function modeling. The review includes theoretical analysis of the resolution modeling framework as well as an overview of various approaches in the literature. It also discusses potential advantages gained via this approach, as discussed with reference to various metrics and tasks, including lesion detection observer studies. Furthermore, attention is paid to issues arising from this approach including the pervasive problem of edge artifacts, as well as explanation and potential remedies for this phenomenon. Furthermore, the authors emphasize limitations encountered in the context of quantitative PET imaging, wherein increased intervoxel correlations due to resolution modeling can lead to significant loss of precision (reproducibility) for small regions of interest, which can be a considerable pitfall depending on the task of interest.