No abstract

The aim of this study was to evaluate the efficacy of helical CT using a combination of CT-attenuation values and visual assessment of stone density as well as discriminant linear analysis to predict the chemical composition of urinary calculi. One hundred human urinary calculi were obtained from a stone-analysis laboratory and placed in 20 excised pig kidneys. They were scanned at 80, 120 and 140 kV with 3-mm collimation. Average, highest and lowest CT-attenuation values and CT variability were recorded. The internal calculus structure was assessed using a wide window setting, and visual assessment of stone density was recorded. A stepwise discriminant linear analysis was performed. The following three variables were discriminant: highest CT-attenuation value, visual density, and highest CT-attenuation value/area ratio, all at 80 kV. The probability of correctly classifying stone composition with these three variables was 0.64, ranging from 0.54 for mixed calculi to 0.69 for pure calculi. The probabilities of correctly classifying calculus composition were: 0.91 for calcium oxalate monohydrate and brushite, 0.89 for cystine, 0.85 for uric acid, 0.11 for calcium oxalate dihydrate, 0.10 for hydroxyapatite, and 0.07 for struvite calculi. When the first two ranks of highest probability for the accurate classification of each calculus type were taken into account, 81% of the calculi were correctly classified. Assessment at 80 kV of the highest CT-attenuation value, visual density and the highest CT-attenuation value/area ratio accurately predicts the chemical composition of 64-81% of urinary calculi. When the first two ranks of highest probability for the accurate classification of each calculus type were taken into account, all cystine, calcium oxalate monohydrate and brushite calculi were correctly classified.

PI-RADS provided the site-specific stratified risk of cancer-positive cores in biopsy-naive men with normal DRE results and elevated PSA levels. There was no significant difference between summed PI-RADS scores of 9 or greater and Likert scale scores of 3 or greater in the detection of cancer in the peripheral zone.

Accuracy of multiparametric MRI has greatly improved the ability of localizing tumor foci of prostate cancer. This property can be used to perform a TRUS-MR image registration, new technological advance, which allows for an overlay of an MRI onto a TRUS image to target a prostate biopsy toward a suspicious area Three types of registration have been developed: cognitive-based, sensor-based, and organ-based registration. Cognitive registration consists of aiming a suspicious area during biopsy with the knowledge of the lesion location identified on multiparametric MRI. Sensor-based registration consists of tracking in real time the TRUS probe with a magnetic device, achieving a global positioning system which overlays in real-time prostate image on both modalities. Its main limitation is that it does not take into account prostate and patient motion during biopsy. Two systems (Artemis and Uronav) have been developed to partially circumvent this drawback. Organ-based registration (Koelis) does not aim to track the TRUS probe, but the prostate itself to compute in a 3D acquisition the TRUS prostate shape, allowing for a registration with the corresponding 3D MRI shape. This system is not limited by prostate/patient motion and allows for a deformation of the organ during registration. Pros and cons of each technique and the rationale for a targeted biopsy only policy are discussed.