DIAGNOSTIC ACCURACY OF IXIP INDEX AND PROSTATE MRI IN THE DIAGNOSIS OF PROSTATE CANCER: PRELIMINARY RESULTS ON A COMBINED APPROACH

The purpose of this study was to assess whether Immune CompleX Predictive Index (iXip) improves diagnostic accuracy of multiparametric prostate MRI (mpMRI) for clinically significant prostate cancer. This study included 72 patients (mean age: 68±8 years) with suspicion of prostate cancer and available iXip score. mpMRI images were evaluated by two radiologists according to the PI-RADS v2.1. Reference standard was based on fusion biopsy and standard transperineal 12-point biopsy. Diagnostic accuracy of iXip, mpMRI and their combination were calculated. Optimal cutoff of iXip with sensitivity and specificity was identified using the Youden index. Patients with clinically significant prostate cancers had significantly higher iXip values compared to patients without clinically significant prostate cancers (median 0.411 vs 0.273; p=0.026). The AUROC for iXip was 0.795 (95% CI 0.579-1.000, p=0.026). Sensitivity and specificity were 75% and 100% respectively for mpMRI alone, and 100% and 80% respectively for mpMRI combined with iXip > 0.375. The combination of mpMRI with a cutoff value of iXip > 0.375 has a very high sensitivity for the diagnosis of prostate cancer and a moderately high specificity

Radiomics and prostate MRI: Current role and future applications

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine learning and deep learning) applied to the field of prostate cancer

Intravenous contrast agent in abdominal CT: Is it really needed to identify the cause of bowel obstruction? Proof of concept

Background. To compare sensitivity of unenhanced computed tomography (CT) and contrast-enhanced CT for the identification of the etiology of bowel obstruction. Materials and Methods. We retrospectively evaluated abdominal CT scans of patients operated for bowel obstruction from March 2013 to October 2017. Two radiologists evaluated CT scans before and after contrast agent in two reading sessions. Then, we calculated sensitivity of CT in the diagnosis of bowel obstruction and determined in which cases the etiology of bowel obstruction was detected on both unenhanced and enhanced CT or on enhanced CT only. The reference standard was defined as the final diagnosis obtained after surgery. Results. Eighteen patients (mean age 72±15 years, age range 37-88 years) were included in the study. Sensitivity of unenhanced CT and enhanced CT was not significantly different in either small bowel obstruction (64%, 7/11 patients vs. 73%, 8/11 patients; P=0.6547) or large bowel obstruction (71%, 5/7 patients vs. 100%, 7/7 patients; P=0.1410). Adhesions were identified on unenhanced CT as the etiology of small bowel obstruction in 80% (4/5) of patients. Tumors were identified on unenhanced CT as the etiology of large bowel obstruction in 67% (4/6) of patients. Conclusion. In the diagnosis of small bowel obstruction due to adhesions with normal bowel wall thickening and when a neoplasm is identified as the etiology of large bowel obstruction on unenhanced CT, an intravenous contrast agent may be avoided for the identification of the etiology. In remaining cases, contrast agent is still recommended

Use of biochar as filler for biocomposite blown films: Structure-processing-properties relationships

In this work, biocomposite blown films based on poly(butylene adipate-co-terephthalate) (PBAT) as biopolymeric matrix and biochar (BC) as filler were successfully fabricated. The materials were subjected to a film-blowing process after being compounded in a twin-screw extruder. The preliminary investigations conducted on melt-mixed PBAT/BC composites allowed PBAT/BC 5% and PBAT/BC 10% to be identified as the most appropriate formulations to be processed via film blowing. The blown films exhibited mechanical performances adequate for possible application as film for packaging, agricultural, and compost bags. The addition of BC led to an improvement of the elastic modulus, still maintaining high values of deformation. Water contact angle measurements revealed an increase in the hydrophobic behavior of the biocomposite films compared to PBAT. Additionally, accelerated degradative tests monitored by tensile tests and spectroscopic analysis revealed that the filler induced a photo-oxidative resistance on PBAT by delaying the degradation phenomena

Malignancy course of pituitary adenoma in MEN1 syndrome: Clinical-Neuroradiological signs

Pituitary carcinomas (PCa) are extremely rare, indistinguishable from pituitary adenomas on histopathological grounds and have a poor prognosis. Most PCa start as PRL or ACTH secreting tumors in males, with relapsing invasive behaviour, refractoriness to medical and radiotherapy and increasing hormonal levels. The presence of distant metastases is still required for the diagnosis of PCa. The association with genetic endocrine diseases must be taken into account, since it adds further risk of evolution towards malignancy. Intradural spinal metastases have also been reported, so a complete craniospinal MR evaluation is recommended, when clinically indicated. We report a case of PCa, associated with MEN1 syndrome, with evidence of meningeal spread to the tentorium cerebelli, clival dura and spinal drop metastases mimicking spinal nerves schwannomas

Deep learning-based methods for prostate segmentation in magnetic resonance imaging

Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardware availability while still achieving accurate segmentation. We apply these models to a limited set of 85 manual prostate segmentations using the k-fold validation strategy and the Tversky loss function and we compare their results. We find that ENet and UNet are more accurate than ERFNet, with ENet much faster than UNet. Specifically, ENet obtains a dice similarity coefficient of 90.89% and a segmentation time of about 6 s using central processing unit (CPU) hardware to simulate real clinical conditions where graphics processing unit (GPU) is not always available. In conclusion, ENet could be efficiently applied for prostate delineation even in small image training datasets with potential benefit for patient management personalization

Megacollect 2004: Hyperspectral Collection Experiment of Terrestrial Targets and Backgrounds of the RIT Megascene and Surrounding Area (Rochester, NY)

This paper describes a collaborative collection campaign to spectrally image and measure a well characterized scene for hyperspectral algorithm development and validation/verification of scene simulation models (DIRSIG). The RIT Megascene, located in the northeast corner of Monroe County near Rochester, New York, has been modeled and characterized under the DIRSIG environment and has been simulated for various hyperspectral and multispectral systems (e.g., HYDICE, LANDSAT, etc.). Until recently, most of the electro-optical imagery of this area has been limited to very high altitude airborne or orbital platforms with low spatial resolutions. Megacollect 2004 addresses this shortcoming by bringing together, in June of 2004, a suite of airborne sensors to image this area in the VNIR, SWIR, MWIR, and LWIR regions. These include the COMPASS (hyperspectral VNIR,SWIR), SEBASS (hyperspectral LWIR), WASP (broadband VIS, SWIR, MWIR, LWIR) and MISI (hyperspectral VNIR, broadband SWIR, MWIR, LWIR). In conjunction with the airborne collections, an extensive ground truth measurement campaign was conducted to characterize atmospheric parameters, select targets, and backgrounds in the field. Laboratory measurements were also made on samples to confirm the field measurements. These spectral measurements spanned the visible and thermal region from 0.4 to 20 microns. These measurements will help identify imaging factors that affect algorithm robustness and areas of improvement in the physical modeling of scene/sensor phenomena. Reflectance panels have also been deployed as control targets to both quantify sensor characteristics and atmospheric effects. A subset of these targets have also been deployed as an independent test suite for target detection algorithms. Details of the planning, coordination, protocols, and execution of the campaign will be discussed with particular emphasis on the ground measurements. The system used to collect the metadata of ground truth measurements and disseminate this data will be described. Lastly, lessons learned in the field will be underscored to highlight additional measurements and changes in protocol to improve future collections of this area