Hepatic acute graft-versus-host disease (aGVHD) is a serious complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT) and is one of the leading causes of early non-recurrent death. The current diagnosis is based mainly based on clinical diagnosis, and there is a lack of non-invasive quantitative diagnosis methods. We propose a multiparametric ultrasound (MPUS) imaging method and explore its effectiveness in evaluating hepatic aGVHD.
In this study, 48 female Wistar rats were used as receptors and 12 male Fischer 344 rats were used as donors for allo-HSCT to establish aGVHD models. After transplantation, 8 rats were randomly selected for ultrasonic examination weekly, including color Doppler ultrasound, contrast-enhanced ultrasound (CEUS) and shear wave dispersion (SWD) imaging. The values of nine ultrasonic parameters were obtained. Hepatic aGVHD was subsequently diagnosed by histopathological analysis. A classification model for predicting hepatic aGVHD was established using principal component analysis and support vector machines.
According to the pathological results, the transplanted rats were categorized into the hepatic aGVHD and non-GVHD (nGVHD) groups. All parameters obtained by MPUS differed statistically between the two groups. The first three contributing percentages of principal component analysis results were resistivity index, peak intensity and shear wave dispersion slope, respectively. The accuracy of classifying aGVHD and nGVHD using support vector machines reached 100%. The accuracy of the multiparameter classifier was significantly higher than that of the single parameter.
The MPUS imaging method has proven to be useful in detecting hepatic aGVHD.

UNASSIGNED: The tendency toward population-based screening programs for prostate cancer (PCa) is expected to increase demand for prebiopsy imaging. This study hypothesizes that a machine learning image classification algorithm for three-dimensional multiparametric transrectal prostate ultrasound (3D mpUS) can detect PCa accurately.
UNASSIGNED: This is a phase 2 prospective multicenter diagnostic accuracy study. A total of 715 patients will be included in a period of approximately 2 yr. Patients are eligible in case of suspected PCa for which prostate biopsy is indicated or in case of biopsy-proven PCa for which radical prostatectomy (RP) will be performed. Exclusion criteria are prior treatment for PCa or contraindications for ultrasound contrast agents (UCAs).
UNASSIGNED: Study participants will undergo 3D mpUS, consisting of 3D grayscale, 4D contrast-enhanced ultrasound, and 3D shear wave elastography (SWE). Whole-mount RP histopathology will provide the ground truth to train the image classification algorithm. Patients included prior to prostate biopsy will be used for subsequent preliminary validation. There is a small, anticipated risk for participants associated with the administration of a UCA. Informed consent has to be given prior to study participation, and (serious) adverse events will be reported.
UNASSIGNED: The primary outcome will be the diagnostic performance of the algorithm for detecting clinically significant PCa (csPCa) on a per-voxel and a per-microregion level. Diagnostic performance will be reported as the area under the receiver operating characteristic curve. Clinically significant PCa is defined as the International Society of Urological grade group ≥2. Full-mount RP histopathology will be used as the reference standard. Secondary outcomes will be sensitivity, specificity, negative predictive value, and positive predictive value for csPCa on a per-patient level, evaluated in patients included prior to prostate biopsy, using biopsy results as the reference standard. A further analysis will be performed on the ability of the algorithm to differentiate between low-, intermediate-, and high-risk tumors.
UNASSIGNED: This study aims to develop an ultrasound-based imaging modality for PCa detection. Subsequent head-to-head validation trials with magnetic resonance imaging have to be performed in order to determine its role in clinical practice for risk stratification in patients suspected for PCa.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide. This study aimed to evaluate the performance of four ultrasound-based techniques for the non-invasive multiparametric (MPUS) assessment of liver fibrosis (LF), steatosis (HS), and inflammation in patients with NAFLD. We included 215 consecutive adult patients with NAFLD (mean age: 54.9 ± 11.7; 54.5% were male), in whom LF, HS, and viscosity were evaluated in the same session using four new ultrasound-based techniques embedded on the Aixplorer MACH 30 system: ShearWave Elastography (2D-SWE.PLUS), Sound Speed Plane-wave UltraSound (SSp.PLUS), Attenuation Plane-wave UltraSound (Att.PLUS), and Viscosity Plane-wave UltraSound (Vi.PLUS). Transient Elastography (TE) with Controlled Attenuation Parameter (CAP) (FibroScan) were considered as control. All elastographic measurements were performed according to guidelines. Valid liver stiffness measurements (LSM) were obtained in 98.6% of patients by TE, in 95.8% of patients by 2D-SWE.PLUS/Vi.PLUS, and in 98.1% of patients by Att.PLUS/SSp.PLUS, respectively. Therefore, 204 subjects were included in the final analysis. A strong correlation between LSMs by 2D-SWE.PLUS and TE (r = 0.89) was found. The best 2D-SWE.PLUS cut-off value for the presence of significant fibrosis (F ≥ 2) was 7 kPa. Regarding steatosis, SSp.PLUS correlated better than Att.PLUS with CAP values: (r = -0.74) vs. (r = 0.45). The best SSp.PLUS cut-off value for predicting the presence of significant steatosis was 1524 m/s. The multivariate regression analysis showed that Vi.PLUS values were associated with BMI and LSM by 2D-SWE.PLUS. In conclusion, MPUS was useful for assessing fibrosis, steatosis, and inflammation in a single examination in patients with NAFLD.

To compare the proportion of clinically significant prostate cancers (PCa) found in lesions detected by multiparametric MRI (mpMRI) with that found in lesions detected by multiparametric ultrasound (mpUSS), in men at risk.
CADMUS (Cancer Detection by Multiparametric Ultrasound of the prostate) is a prospective, multi-centre paired cohort diagnostic utility study with built-in randomisation of order of biopsies. The trial is registered ISRCTN38541912. All patients will undergo the index test under evaluation (mpUSS±biopsies), as well as the standard test (mpMRI±biopsies). Eligible men will be those at risk of harbouring prostate cancer usually recommended for prostate biopsy, either for the first time or as a repeat, who have not had any prior treatment for prostate cancer. Men in need of repeat biopsy will include those with prior negative results but ongoing suspicion, and those with an existing prostate cancer diagnosis but a need for accurate risk stratification. Both scans will be reported blind to the results of the other and the order in which the targeted biopsies derived from the two different imaging modalities are taken will be randomised. Comparison will be drawn between biopsy results of lesions detected by mpUSS with those lesions detected by mpMRI. Agreement over position between the two imaging modalities will be studied.
CADMUS will provide level one evidence on the performance of mpUSS derived targeted biopsies in the identification of clinically significant prostate cancer in comparison to mpMRI targeted biopsies. Recruitment is underway and expected to complete in 2018.