Search

Background: We investigated the tumor suppression effect of an ultrasound-sensitive doxorubicin-loaded liposome-based nanoparticle, IMP301, to enhance the synergistic effect with focused ultrasound (FUS) in an animal model of pancreatic cancer. Methods: Thirty nude mice with xenografts of PANC-1 human pancreatic cancer cells were randomly and prospectively allocated to 6 different groups (5 per group) each for Study-1 (dose–response test) and Study-2 (synergistic effect test). Study-1 consisted of control, gemcitabine, Doxil with FUS, and three different doses of IMP301 (2, 4, 6 mg/kg) with FUS groups. Study-2 consisted of control, FUS only, gemcitabine, Doxil with FUS, and IMP301 (4 mg/kg) with or without FUS groups. Differences in tumor volume and growth rate were evaluated by one-way ANOVA and Student–Newman–Keuls test. Results: In Study-1, 4 mg/kg or greater IMP301 with FUS groups showed lower tumor growth rates of 14 ± 4 mm3/day (mean ± standard deviation) or less, compared to the control, gemcitabine, and Doxil with FUS groups with rates exceeding 28 ± 5 (p < 0.050). The addition of FUS in Study-2 decreased the tumor growth rate in the IMP301-treated groups from 36 ± 17 to 9 ± 6, which was lower than the control, FUS only, gemcitabine, and Doxil with FUS groups (p < 0.050). Conclusions: IMP301 combined with FUS exhibited higher tumor growth suppression compared to the use of a conventional drug alone or the combination with FUS. The present study showed the potential of IMP301 to enhance the synergistic effect with FUS for the treatment of pancreatic cancer. Relevance statement: This article aims to evaluate the synergistic effect of FUS and ultrasound-responsive liposomal drug in tumor growth suppression by using xenograft mouse model of pancreatic ductal adenocarcinoma. FUS-induced ultrasound-sensitive drug release may be a potential noninvasive repeatable treatment option for patients with locally advanced or unresectable pancreatic cancer. Key points: • Modification of conventional drugs combined with FUS would maximize tumor suppression. • IMP301 with FUS had higher tumor suppression effect compared to conventional chemotherapy. • This image-guided drug delivery would enhance therapeutic effects of systemic chemotherapy. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the usefulness of prostate health index (PHI) as an indicator for recommending magnetic resonance imaging (MRI) in patients with prostate-specific antigen (PSA) gray zone level < 10 ng/mL. Methods: 443 patients who underwent prostate biopsy (PB) after serum PHI test and MRI between April 2019 and December 2022 were enrolled. For patients with visible lesion on MRI with Prostate Imaging Reporting and Data System Score (PI-RADS) ≥ 3, MRI-targeted PB was performed in addition to systematic 12-core PB. Results: The optimal cutoff value of PHI for predicting PI-RADS ≥ 3 lesions was 39.6, which was significantly associated with overall prostate cancer (OR 3.07, p = 0.018) and clinically significant prostate cancer (csPCa) (OR 4.15, p = 0.006) at MRI-targeted PB cores. When MRI was restricted to patients with PHI ≥ 39.6 alone, 28.7% of unnecessary MRI could be saved at the cost of missing 13.6% of csPCa. When omitting MRI for patients with PHI < 39.6 and PSAD < 0.12 ng/mL2, unnecessary MRI could be reduced by 20.1% with the risk of missing 6.2% of csPCa. With addition of systematic PB, 21.0% of patients with negative MRI-targeted PB were diagnosed as csPCa. Conclusions: For patients in PSA gray zone, PHI of 39.6 might be an indicator for MRI and further MRI-targeted PB in additional to PSAD of 0.12 ng/mL2, reducing 20.1% of unnecessary MRI with the minimal risk of missing 6.2% of csPCa. To maximize csPCa detection, combining both MRI-targeted and systematic PB should be also considered. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the diagnostic performance of the tumor contact length (TCL) in the prediction of MIBC (muscle-invasive bladder cancer) in lesions corresponding to the vesical imaging-reporting and data system (VIRADS) score 2–3. Methods: This is a single institution, retrospective study targeting 191 consecutive patients assigned of VIRADS score 2–3, who had pre-transurethral resection MRI from July 2019 to September 2021. Logistic regression analyses were performed to determine meaningful predictors of MIBC for this score group, and a nomogram was plotted with those variables. The diagnostic performance of each predictor was compared at predefined thresholds (VIRADS score 3 and TCL 3 cm) using the generalized linear model and ROC analysis. Results: Both VIRADS score and TCL remained independent predictors of MIBC for this score group (odds ratio 7.3 for VIRADS score, and 1.3 for TCL, p < 0.01 for both). The contribution of TCL to the probability of MIBC in the nomogram was greater than that of the VIRADS score. VIRADS score had a sensitivity of 0.54 (14/26), specificity of 0.92 (203/221), and diagnostic accuracy of 0.88 (217/247), and TCL showed a sensitivity of 0.89 (23/26), specificity of 0.95 (209/221), and diagnostic accuracy of 0.94 (232/247). The difference in sensitivity (p = 0.03) and accuracy (p = 0.04) was statistically significant. The AUC was also significantly wider for TCL than for VIRADS (0.97 vs. 0.73, p < 0.01). Conclusion: A simple index, TCL, may be helpful in further risk stratification for MIBC in patients with a score of VIRADS 2–3. Clinical relevance statement: For bladder cancer patients with insufficient qualitative evidence of muscle layer invasion using VIRADS categorization, TCL, a simple quantitative indicator defined as the curvilinear contact length between the bladder wall and the tumor, may be helpful in risk stratification. Key Points: • Even when only lesions with score 2–3 were targeted, VIRADS was still a meaningful indicator of MIBC. • With a predefined threshold of 3 cm applied, TCL outperformed VIRADS in the score 2–3 group, in predicting MIBC. • A longer TCL for a lesion with a VIRADS score 2 may warrant an additional warning for MIBC, whereas a shorter TCL for a lesion with a score 3 may indicate a lower risk of MIBC. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate association between computer tomography (CT)-based features of renal cell carcinoma (RCC) and survival outcomes. Methods: Data of 958 patients with clinical T1b–T2 RCC who underwent partial/radical nephrectomy from June 2003 to March 2022 were retrospectively evaluated. CT images of patients were reviewed by two radiologists for texture analysis of tumor heterogeneity and shape analysis of tumor contour. Patients were divided into three groups according to patterns of CT-based features: (1) favorable feature group (n = 117); (2) intermediate feature group (n = 606); and (3) unfavorable feature group (n = 235). Kaplan–Meier survival analysis and multivariate Cox regression analysis were performed to evaluate overall survival (OS), cancer-specific survival (CSS), and recurrence-free survival (RFS). Results: RCCs with unfavorable CT-based feature showed larger size on CT, higher nuclear grade, higher rate of histologic necrosis, and higher rate of capsular invasion than those in the other two groups (all p < 0.001). Unfavorable feature was associated with poorer OS (p = 0.001), CSS (p < 0.001), and RFS (p < 0.001) on Kaplan–Meier analysis. In multivariate analysis, intermediate and unfavorable features were independent predictors for recurrence (hazard ratio [HR] 2.51, 95% confidence interval [CI] 1.09–5.79, p = 0.031 and HR 3.71, 95% CI 1.58–8.73, p = 0.003, respectively), but not for overall death or RCC-specific death. Conclusions: A combination of irregular tumor contour feature with heterogeneous tumor texture feature on CT is associated with poor RFS in clinical T1b–T2 RCC preoperatively. [ABSTRACT FROM AUTHOR]

Conventional chemotherapy methods have adverse off-target effects and low therapeutic efficiencies of drug release in target tumors. In this study, we proposed a combination therapy of doxorubicin (DOX)-loaded ultrasound (US)-sensitive liposomal nanocarriers (IMP301), microbubbles (MBs) under focused US exposure using convex acoustic lens-attached US (LENS) to tumor treatment. The therapeutic effects of each treatment in a murine melanoma model were evaluated using contrast-enhanced US (CEUS) and micro-computed tomography (micro-CT) imaging, bioluminescence and confocal microscopy imaging, and liquid chromatography–mass spectroscopy (LC/MS) analysis. Tumor-bearing mice were randomly assigned to one of the following groups: (1) G1: IMP301 only (n = 9); (2) G2: IMP301 + LENS (n = 9); (3) G3: IMP301 + MB + LENS (n = 9); (4) G4: DOXIL only (n = 9); and (5) G5: IMP301 without DOXIL group as a control group (n = 4). Ten days after tumor injection, tumor-bearing mice were treated according to each treatment strategy on 10th, 12th, and 14th days from the day of tumor injection. The CEUS images of the tumors in the murine melanoma model clearly showed increased echo signal intensity from MBs as resonant US scattering. The relative tumor volume of the G2 and G3 groups on the micro-CT imaging showed inhibited tumor growth than the reference baseline of the G5 group. DOX signals on bioluminescence and confocal microscopy imaging were mainly located at the tumor sites. LC/MS showed prominently higher intratumoral DOX concentration in the G3 group than in other treated groups. Therefore, this study effectively demonstrates the feasibility of the synergistic combination of IMP301, MBs, and LENS-application for tumor-targeted treatment. Thus, this study can enable efficient tumor-targeted treatment by combining therapy such as IMP301 + MBs + LENS-application. [ABSTRACT FROM AUTHOR]

Objective: To identify patients who can safely evade the magnetic resonance imaging fusion-targeted biopsy (MRIFTB) for prostate imaging reporting and data system (PI-RADS) 3 lesion. Materials and methods: Overall, 755 men with PI-RADS 3–5 lesions who underwent MRIFTB were retrospectively analyzed. Univariate and multivariate analyses were performed to determine significant predictors for clinically significant prostate cancer (CSPCa), defined as Gleason grade group ≥ II. Detection rates and negative predictive values of CSPCa were estimated according to various clinical settings. Results: Median age, prostate-specific antigen (PSA), and PSA density of patients were 66.0 years, 7.39 ng/mL, and 0.19 ng/mL, respectively. Overall detection rates of CSPCa according to PI-RADS 3 (n = 347), 4 (n = 260), and 5 (n = 148) lesions were 15.0%, 30.4%, and 80.4%, respectively. The negative predictive value (NPV) of PI-RADS 3 lesion on MRI was 15.0%. On multivariate analysis, age [≥ 65 years, odds ratio (OR) = 0.427], PSA density (≥ 0.20 ng/mL2, OR = 0.234), prior negative biopsy history (OR = 2.231), and PI-RADS score (4, OR = 0.427; 5, OR = 0.071) were independent predictors for the absence of CSPCa by MRIFTB. When assessed according to various conditions, NPVs of PI-RADS 3 lesions were relatively high in subgroups with low PSA density (< 0.20 ng/mL2) regardless of age or prior biopsy history (NPV range 91.1–91.9%). Contrarily, NPVs in subgroups with high PSA density were relatively low and varied according to age or prior biopsy history groups (NPV range 50.0–86.8%). Conclusions: Men with the PI-RADS 3 lesion and low PSA density might safely evade the MRIFTB, regardless of age or prior biopsy history. [ABSTRACT FROM AUTHOR]

Objectives: To examine the diagnostic performance of Vesical Imaging-Reporting and Data System (VIRADS) and to find a quantitative indicator for predicting muscle layer invasion of bladder cancer. Methods: 3-T MRI of 82 patients performed before transurethral resection of bladder tumors or radical cystectomy between July 2018 and June 2019 were retrospectively analyzed. For one index lesion of each patient, two radiologists independently assigned VIRADS score and measured tumor-wall interface (contact length between tumor and bladder wall) on T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI. Inter-reader agreement was assessed, and logistic regression analysis was performed to find indicators of muscle layer invasion. Comparison of indicators' diagnostic performance was done with receiver operating characteristic (ROC) curve and generalized linear model analyses. Optimal cutoff point was determined by the Youden index J. Results: Inter-reader agreement was at least substantial for VIRADS categorization (κ 0.77–0.81), and almost perfect for tumor-wall interface (intraclass correlation coefficient 0.88–0.90). Tumor-wall interface (odds ratio [OR] 1.90–2.00) and VIRADS score (OR 8.59–8.89) were independently associated with muscle layer invasion (p ≤ 0.02). For VIRADS, area under the ROC curve (AUROC) was 0.94, and the accuracy was 0.93 at score 3, the optimal threshold for predicting muscle layer invasion. Depending on the MRI sequence, tumor-wall interface showed AUROCs of 0.90–0.92 and accuracy of 0.84–0.90 at suggested thresholds (3 ± 0.3 cm). Tumor-wall interface showed insignificant differences in accuracy compared with VIRADS (p > 0.10), except as measured on diffusion-weighted images (p = 0.01). Conclusions: VIRADS is a good predictor of muscle layer invasion. As an independent quantitative indicator, tumor-wall interface may complement VIRADS to enhance prediction. Key Points: • Vesical Imaging-Reporting and Data System (VIRADS) is a promising predictor of muscle invasion of bladder cancer with good reproducibility, as suggested by previous studies. • VIRADS score and the tumor-wall interface (curvilinear contact length between the tumor and the bladder wall) are independent predictors of muscle layer invasion. • As an easy-to-use quantitative indicator, tumor-wall interface is expected to be used as an indicator complementary to VIRADS, a qualitative indicator. [ABSTRACT FROM AUTHOR]

The purpose of this research is to exploit a weak and semi-supervised deep learning framework to segment prostate cancer in TRUS images, alleviating the time-consuming work of radiologists to draw the boundary of the lesions and training the neural network on the data that do not have complete annotations. A histologic-proven benchmarking dataset of 102 case images was built and 22 images were randomly selected for evaluation. Some portion of the training images were strong supervised, annotated pixel by pixel. Using the strong supervised images, a deep learning neural network was trained. The rest of the training images with only weak supervision, which is just the location of the lesion, were fed to the trained network to produce the intermediate pixelwise labels for the weak supervised images. Then, we retrained the neural network on the all training images with the original labels and the intermediate labels and fed the training images to the retrained network to produce the refined labels. Comparing the distance of the center of mass of the refined labels and the intermediate labels to the weak supervision location, the closer one replaced the previous label, which could be considered as the label updates. After the label updates, test set images were fed to the retrained network for evaluation. The proposed method shows better result with weak and semi-supervised data than the method using only small portion of strong supervised data, although the improvement may not be as much as when the fully strong supervised dataset is used. In terms of mean intersection over union (mIoU), the proposed method reached about 0.6 when the ratio of the strong supervised data was 40%, about 2% decreased performance compared to that of 100% strong supervised case. The proposed method seems to be able to help to alleviate the time-consuming work of radiologists to draw the boundary of the lesions, and to train the neural network on the data that do not have complete annotations. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate risk factors for bacillus Calmette–Guerin-induced prostatitis in patients with non-muscle invasive bladder cancer following bacillus Calmette–Guerin therapy. Clinical findings from patients with non-muscle invasive bladder cancer who underwent multi-parametric magnetic resonance imaging before transurethral resection of bladder tumor and post-bacillus Calmette–Guerin therapy from March 2004 to August 2018 were evaluated. The population was grouped into patients with or without newly developed lesions on multi-parametric magnetic resonance imaging performed 3 months after bacillus Calmette–Guerin instillation. Patients with prostate-specific antigen levels ≥ 4 ng/mL or prostate cancer were excluded. Univariable and multivariable analyses were performed to determine the predictors of prostate lesions in patients with prior bacillus Calmette–Guerin exposure. Post bacillus Calmette–Guerin-induced prostatitis was found in 50 of the 194 patients (25.8%). No significant differences were observed between the groups except for prostate volumes (33.8 mL vs. 30.8 mL, P = 0.012) and body mass index (25.2 kg/m2 vs. 24.1 kg/m2, P = 0.044). After bacillus Calmette–Guerin exposure, no significant differences in prostate-specific antigen levels, international prostate symptom scores, or post-voiding residual volume were noted. Multivariable regression analysis showed that body mass index (odds ratio, OR = 1.115, P = 0.038) and prostate volume (OR = 3.080, P = 0.012) were significant predictors of post-bacillus Calmette–Guerin prostate lesions. Body mass index and prostate volume may be clinical predictors of prostate lesions after bacillus Calmette–Guerin exposure. Awareness of potential risk factors for this entity should contribute to the clinical decision-making process for patients following bacillus Calmette–Guerin therapy. [ABSTRACT FROM AUTHOR]

Objectives: To validate how established markers of extraprostatic extension (EPE) are applied to anterior prostate cancers (APCs), and to investigate other novel markers if available.Methods: Among 614 histopathologically confirmed APCs from 2011 to 2016, 221 lesions with PiRADS (verion 2) scores ≥ 4 on 3-T multi-parametric MRI were analyzed retrospectively. Two radiologists independently assessed capsular morphology qualitatively with 5-point scale (normal, thinning, bulging, loss, extracapsular disease), and capsule contact length (arc), tumor dimension, and their ratio (arc-dimension ratio) quantitatively. Reproducibility in measurement was assessed with κ and intra-class correlation coefficients (ICCs). Logistic regression analysis was done to find meaningful indicators of EPE. Diagnostic performance of markers was compared to one another with generalized linear model and multi-reader multi-case ROC analysis.Results: Reproducibility was moderate to substantial (κ 0.45-0.73) for qualitative, and moderate to almost perfect (ICC 0.50-0.87) for quantitative features of EPE. Capsular morphology (odds ratio [OR] 1.818), capsule contact length (OR 1.115), tumor dimension (OR 1.035), and arc-dimension ratio (OR 1.846) were independently associated with EPE (p ≤ 0.019). Capsular bulging and capsule contact length of 10 mm as thresholds of EPE demonstrated sensitivity/specificity of 0.58/0.85 and 0.77/0.68, respectively. Capsule contact length yielded greatest AUC (0.784), followed by capsular morphology (0.778), arc-dimension ratio (0.749), and tumor dimension (0.741). Diagnostic performance of capsular morphology, capsule contact length, and arc-dimension ratio was comparable in predicting EPE.Conclusions: Existing markers of EPE applicable regardless of locations of tumors apply similarly to APCs. Arc-dimension ratio may be a novel marker of EPE of APCs.Key Points: • Existing imaging markers of extraprostatic extension (EPE) which have been applied regardless of locations of tumors are reflected similarly to anterior prostate cancers (APCs). • Measuring tumor dimension without capsular assessment may result in insufficient pre-operative prediction of EPE of APCs. • Arc-dimension ratio (capsule contact length divided by tumor dimension) exhibited highest OR and comparable performance to existing features in predicting EPE of APCs. [ABSTRACT FROM AUTHOR]

We aimed to evaluate the effect of 5 alpha-reductase inhibitor (5-ARI) treatment on prostate cancer (PCa) and clinically significant PCa (csPCa) detection in patients undergoing transrectal ultrasound (TRUS)/magnetic resonance imaging (MRI) fusion biopsy in the current era of multi-parametric MRI (mpMRI). We retrospectively reviewed our TRUS/MRI fusion biopsy database (n = 706). Eighty (11.3%) patients who had used 5-ARI for more than one year at the time of biopsy were stratified as 5-ARI group. Subsequently, we performed comparative analyses of 5-ARI and non-5-ARI groups. csPCa was defined by a Gleason score ≥3 + 4 in a single biopsy core. Chi-squared test was used to evaluate the performance of mpMRI in predicting PCa/csPCa between the two groups. Multivariate logistic regression analyses were performed to evaluate the significant variables associated with PCa detection. There were no significant differences in PCa/csPCa detection rates between 5-ARI and non-5-ARI groups (all, P > 0.05). In multivariate logistic regression analyses for the evaluation of variables associated with csPCa detection, age (odds ratio [OR], 1.062; 95% confidence interval [CI], 1.035–1.090; P < 0.001), pre-biopsy PSA (OR, 1.062; 95% CI, 1.034–1.090; P < 0.001), prostate volume on TRUS (OR, 0.956; 95% CI, 0.943–0.970, P < 0.001), and PI-RADsV2 category (OR, 5.528; 95% CI, 3.017–10.131; P < 0.001) were found to be significant predictors. However, 5-ARI had no significant association with PCa detection (P = 0.384). Conclusively, 5-ARI therapy did not adversely affect PCa/csPCa detection after TRUS/MRI fusion biopsy, which suggests that exposure to 5-ARI may not impair the performance of mpMRI. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the characteristics and histological outcomes in patients with Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions undergoing magnetic resonance imaging-guided fusion-targeted biopsy (MRIFTB). Methods: We retrospectively reviewed 138 patients with PI-RADS category 3 lesions classified using multiparametric MRI who underwent MRIFTB between May 2016 and March 2018. The study population included biopsy-naïve and patients with prior negative biopsy. Univariate and multivariate analyzes were performed to determine significant predictors of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The definition of csPCa was set at Gleason score ≥ 3 + 4. Results: Overall, 114 (82.6%) biopsied lesions were benign and 24 (17.4%) were identified as prostate cancer. Of these 24 lesions, 14 (58.3%) harbored csPCa. Peripheral zone (PZ) lesions were more likely to be associated with malignant disease than transition zone lesions (13.7 vs. 6.2%). Multivariate logistic analysis revealed that age, PZ location, and prostate-specific antigen (PSA) density (P < 0.05) were independent predictors of both PCa and csPCa. Conclusions: A non-negligible number of PI-RADS 3 patients harbor csPCa. Moreover, age, lesion location, and PSA density could be potential clinical predictors of PCa and csPCa. Physicians should be aware of the cancer prevalence of PI-RADS 3 lesions, as the use of the aforementioned factors can help in the decision-making process for these patients. [ABSTRACT FROM AUTHOR]

In this research, we exploit an image-based deep learning framework to distinguish three major subtypes of renal cell carcinoma (clear cell, papillary, and chromophobe) using images acquired with computed tomography (CT). A biopsy-proven benchmarking dataset was built from 169 renal cancer cases. In each case, images were acquired at three phases(phase 1, before injection of the contrast agent; phase 2, 1 min after the injection; phase 3, 5 min after the injection). After image acquisition, rectangular ROI (region of interest) in each phase image was marked by radiologists. After cropping the ROIs, a combination weight was multiplied to the three-phase ROI images and the linearly combined images were fed into a deep learning neural network after concatenation. A deep learning neural network was trained to classify the subtypes of renal cell carcinoma, using the drawn ROIs as inputs and the biopsy results as labels. The network showed about 0.85 accuracy, 0.64–0.98 sensitivity, 0.83–0.93 specificity, and 0.9 AUC. The proposed framework which is based on deep learning method and ROIs provided by radiologists showed promising results in renal cell subtype classification. We hope it will help future research on this subject and it can cooperate with radiologists in classifying the subtype of lesion in real clinical situation. [ABSTRACT FROM AUTHOR]

Purpose: We analyzed the data of consecutive patients who had preoperative multiparametric magnetic resonance imaging (mpMRI) and underwent radical prostatectomy (RP) to evaluate the actual performance of mpMRI among biopsy-proven prostate cancer (PCa) patients in predicting favorable pathology in the real-life clinical setting.Methods: Among a total 730 biopsy-proven PCa patients underwent RP, the preoperative mpMRIs of 534 patients were positive, demonstrating one or more PI-RADs V2 grade ≥ 2 lesion(s). Other 196 mpMRIs were classified as negative, without any suspicious lesion. Pathology was classified to be unfavorable when showing Gleason score (GS) 4/5 or pT3/N1 features. Significant cancer was defined as non-organ-confined, GS 4/5, or cancer volume of ≥ 0.5 mL.Results: Among a total 196 negative preoperative mpMRI patients, final RP pathology showed that 20 (10.2%) had pT3 disease and 2 (1.0%) had pN1 disease. Regarding the pathologic Gleason score, 117 (59.7%) had GS 3 + 4 and 44 (22.4%) had GS ≥ 4 + 3. The rate of a favorable PCa and an insignificant cancer was as low as 14.3% and 10.2%. Even among only the 101 D’Amico low-risk patients with negative MRI, the rates of a favorable pathology and an insignificant cancer were only 18.2% and 12.7%. The sensitivity, specificity, positive, and negative predictive value of mpMRI to predict a significant cancer were 74.3%, 45.5%, 95.5%, and 10.2%, respectively.Conclusions: In the real-life clinical setting, mpMRI demonstrated limited performance in the prediction of favorable and insignificant prostate cancer as a negative mpMRI could not guarantee the absence of unfavorable pathology among PCa patients. [ABSTRACT FROM AUTHOR]

Nanoliposomes are important carriers capable of packaging drugs for various delivery applications through passive targeting tumor sites by enhancing permeability and retention effect. Radiolabeled liposomes have potential applications in radiotherapy and diagnostic imaging. However, the physico-chemical instability of liposomes during manufacturing and storage limits their extensive application. Therefore, considerable numbers of studies have been made on the stability of liposomes over the last few years in order to overcome this problem. In this study, we attempted to prepare polymer-coated liposomes using water-soluble chitosan in order to enhance the stability of rhenium(III) chloride-incorporated liposomes. They were characterized by an electrophoretic light-scattering spectrophotometer, Fourier transform infrared spectroscopy (FT-IR), UV-Vis spectrometer, and phase-contrast microscopy. The chitosan-coated liposomes are spherical and the particle size is about 800-850 nm. Incorporation of chitosan into the liposome bilayer decreased rhenium(III) chloride release from the liposome due to an increased rigidity of the liposome membrane structure. Chitosan-coated liposomes showed a higher stability compared with the stability of non-coated liposomes. The release characteristics of rhenium(III) chloride encapsulated in the liposome were taken as a measure of stability of the liposome membrane. [ABSTRACT FROM AUTHOR]

Purpose: We developed a multiple logistic regression model, an artificial neural network (ANN), and a support vector machine (SVM) model to predict the outcome of a prostate biopsy, and compared the accuracies of each model.Method: One thousand and seventy-seven consecutive patients who had undergone transrectal ultrasound (TRUS)-guided prostate biopsy were enrolled in the study. Clinical decision models were constructed from the input data of age, digital rectal examination findings, prostate-specific antigen (PSA), PSA density (PSAD), PSAD in transitional zone, and TRUS findings. The patients were divided into the training and test groups in a randomized fashion. Areas under the receiver operating characteristic (ROC) curve (AUC, Az) were calculated to summarize the overall performance of each decision model for the task of prostate cancer prediction.Results: The Az values of the ROC curves for the use of multiple logistic regression analysis, ANN, and the SVM were 0.768, 0.778, and 0.847, respectively. Pairwise comparison of the ROC curves determined that the performance of the SVM was superior to that of the ANN or the multiple logistic regression model.Conclusion: Image-based clinical decision support models allow patients to be informed of the actual probability of having a prostate cancer. [ABSTRACT FROM AUTHOR]

Precise sentinel lymph node (SLN) identification is crucial not only for accurate diagnosis of micro-metastases at an early stage of cancer progression but also for reducing the number of SLN biopsies (SLNB) to minimize their severe side effects. Furthermore, it is desirable that an SLNB guidance should be as safe as possible in routine clinical use. Although there are currently various SLNB guidance methods for pre-operative or intra-operative assessment, none are ideal. We propose a real-time SLNB guidance method using contrast-enhanced tri-modal images (i.e., ultrasound, photoacoustic, and fluorescence) acquired by a recently developed hand-held tri-modal probe. The major advantage of tri-modal imaging is demonstrated here through an in vivo study of the technically-difficult case of nodal obstruction that frequently leads to false-negative results in patients. The results in a tumor model in rabbits and normal controls showed that tri-modal imaging is capable of clearly identifying obstructed SLNs and of indicating their metastatic involvement. Based on these findings, we propose an SLNB protocol to help surgeons take full advantage of the complementary information obtained from tri-modal imaging, including for pre-operative localization, intra-operative biopsy guidance and post-operative analysis. [ABSTRACT FROM AUTHOR]