MRI in prostate cancer radiology: what is currently known?

Approaches to the diagnosis and treatment of prostate cancer rely on a combination of magnetic resonance imaging (MRI) and histological data. The purpose of this review is to introduce the reader to the basics of the current diagnostic approach to prostate cancer with a focus on texture analysis (TA). Texture analysis allows the evaluation of relationships between image pixels using mathematical methods, which provides additional information. First-order texture analysis of features can have greater clinical reproducibility than higher-order texture features. Textural features extracted from diffusion coefficient maps have shown the greatest clinical relevance. Future research should focus on integrating machine learning methods to facilitate the use of texture analysis in clinical practice. Development of automated segmentation methods is required to reduce the likelihood of including normal tissue in the area of interest. Texture analysis allows noninvasive separation of patients into groups in terms of possible treatment options. Currently, there are few clinical studies on the differential diagnosis of clinically significant prostate cancer, including Gleason and ISUP grading. Large prospective studies are required to verify the diagnostic potential of textural features.

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Application of texture analysis based on T2-weighted magnetic resonance images in discriminating Gleason scores of prostate cancer

Journal of X-Ray Science and Technology ◽

10.3233/xst-200695 ◽

2020 ◽

Vol 28 (6) ◽

pp. 1207-1218

Author(s):

Ruigen Pan ◽

Xueli Yang ◽

Zhenyu Shu ◽

Yifeng Gu ◽

Lihua Weng ◽

...

Keyword(s):

Prostate Cancer ◽

Magnetic Resonance ◽

Texture Analysis ◽

Gleason Score ◽

Texture Features ◽

Roc Curves ◽

Magnetic Resonance Images ◽

Diagnostic Efficiency ◽

Energy Value ◽

Tumor Region

OBJECTIVE: To investigate the value of texture analysis in magnetic resonance images for the evaluation of Gleason scores (GS) of prostate cancer. METHODS: Sixty-six prostate cancer patients are retrospective enrolled, which are divided into five groups namely, GS = 6, 3 + 4, 4 + 3, 8 and 9–10 according to postoperative pathological results. Extraction and analysis of texture features in T2-weighted MR imaging defined tumor region based on pathological specimen after operation are performed by texture software OmniKinetics. The values of texture are analyzed by single factor analysis of variance (ANOVA), and Spearman correlation analysis is used to study the correlation between the value of texture and Gleason classification. Receiver operating characteristic (ROC) curve is then used to assess the ability of applying texture parameters to predict Gleason score of prostate cancer. RESULTS: Entropy value increases and energy value decreases as the elevation of Gleason score, both with statistical difference among five groups (F = 10.826, F = 2.796, P < 0.05). Energy value of group GS = 6 is significantly higher than that of groups GS = 8 and 9–10 (P < 0.005), which is similar between three groups (GS = 3 + 4, 8 and 9–10). The entropy and energy values correlate with GS (r = 0.767, r = –0.692, P < 0.05). Areas under ROC curves (AUC) of combination of entropy and energy are greater than that of using energy alone between groups GS = 6 and ≥7. Analogously, AUC of combination of entropy and energy are significantly higher than that of using entropy alone between groups GS≤3 + 4 and ≥4 + 3, as well as between groups GS≤4 + 3 and ≥8. CONCLUSION: Texture analysis on T2-weighted images of prostate cancer can evaluate Gleason score, especially using the combination of entropy and energy rendering better diagnostic efficiency.

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Image classification of vaginal microecology detection based on gabor texture and LSTM model

Technology and Health Care ◽

10.3233/thc-213509 ◽

2021 ◽

pp. 1-18

Author(s):

Gaoteng Yuan ◽

Yinping Dong ◽

Xiaofeng Zhou

Keyword(s):

Image Classification ◽

Texture Analysis ◽

Short Term Memory ◽

Imbalanced Data ◽

Region Of Interest ◽

Texture Features ◽

Image Features ◽

Imbalanced Data Sets ◽

Area Of Interest ◽

Gynecological Diseases

BACKGROUND: Gynecological diseases threaten women’s health, and vaginal microecological testing is a common method for detecting gynecological diseases. Efficient and accurate microecological testing methods have always been the goal pursued by gynecologists. OBJECTIVE: In order to automatically identify different types of microbial images in vaginal micromorphology detection, this paper proposes a vaginal microecological image recognition method based on Gabor texture analysis combined with long and short-term memory network (LSTM) model. METHOD: Firstly, we denoise the microecological morphological im-ages, which selects the area of interest and sets the label of the microorganism according to the doctors label. Secondly, texture analysis is carried out for the region of interest, which uses Gabor filters with 8 directions and 5 scales to filter the region of interest to extract the texture features on the image. Comparing the differences between different microbial image features, and screening suitable features to reduce the number of features. Then, we design an LSTM model to analyze the relationship of image features in different categories of microorganisms. Finally, we use the full connection layer and Softmax function to realize the automatic recognition of different microbial images. RESULTS: The experimental results show that the image classification accuracy of 8 common microorganisms is 81.26%. CONCLUSION: Texture analysis combined with LSTM network strategy can identify different kinds of vaginal micro ecological images. Gabor-LSTM model has better classification effect on imbalanced data sets.

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Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study

Scientific Reports ◽

10.1038/s41598-021-81272-x ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Gabriel A. Nketiah ◽

◽

Mattijs Elschot ◽

Tom W. Scheenen ◽

Marnix C. Maas ◽

...

Keyword(s):

Prostate Cancer ◽

Texture Analysis ◽

Multicenter Study ◽

Peripheral Zone ◽

Support Vector ◽

Low Grade ◽

Textural Features ◽

Grade Group ◽

Cancer Aggressiveness ◽

Grade Groups

AbstractT2-weighted (T2W) MRI provides high spatial resolution and tissue-specific contrast, but it is predominantly used for qualitative evaluation of prostate anatomy and anomalies. This retrospective multicenter study evaluated the potential of T2W image-derived textural features for quantitative assessment of peripheral zone prostate cancer (PCa) aggressiveness. A standardized preoperative multiparametric MRI was performed on 87 PCa patients across 6 institutions. T2W intensity and apparent diffusion coefficient (ADC) histogram, and T2W textural features were computed from tumor volumes annotated based on whole-mount histology. Spearman correlations were used to evaluate association between textural features and PCa grade groups (i.e. 1–5). Feature utility in differentiating and classifying low-(grade group 1) vs. intermediate/high-(grade group ≥ 2) aggressive cancers was evaluated using Mann–Whitney U-tests, and a support vector machine classifier employing “hold-one-institution-out” cross-validation scheme, respectively. Textural features indicating image homogeneity and disorder/complexity correlated significantly (p < 0.05) with PCa grade groups. In the intermediate/high-aggressive cancers, textural homogeneity and disorder/complexity were significantly lower and higher, respectively, compared to the low-aggressive cancers. The mean classification accuracy across the centers was highest for the combined ADC and T2W intensity-textural features (84%) compared to ADC histogram (75%), T2W histogram (72%), T2W textural (72%) features alone or T2W histogram and texture (77%), T2W and ADC histogram (79%) combined. Texture analysis of T2W images provides quantitative information or features that are associated with peripheral zone PCa aggressiveness and can augment their classification.

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Overview of Texture Analysis

Computer Vision ◽

10.4018/978-1-5225-5204-8.ch009 ◽

2018 ◽

pp. 221-244

Author(s):

Izem Hamouchene ◽

Saliha Aouat

Keyword(s):

Image Processing ◽

Image Analysis ◽

Texture Analysis ◽

Texture Features ◽

Research Area ◽

Textural Features ◽

Important Research ◽

Texture Characteristic ◽

Important Research Area ◽

Structural Methods

Image analysis is emerging as an important research area. The study of certain methods of image processing by the texture characteristic has been made in this paper. Existing texture analysis algorithms are studied and classified into four categories: statistical methods, structural methods, model based methods and Transform based methods. Each approach is reviewed according to its classification. Many methods have been developed to extract textural features from an image, the authors will talk about the most famous methods and used of texture features extraction with examples and they will give their critics about them. A discussion of these texture methods concludes this study.

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Overview of Texture Analysis

International Journal of Computer Vision and Image Processing ◽

10.4018/ijcvip.2014040103 ◽

2014 ◽

Vol 4 (2) ◽

pp. 32-51

Author(s):

Izem Hamouchene ◽

Saliha Aouat

Keyword(s):

Image Processing ◽

Texture Analysis ◽

Texture Features ◽

Research Area ◽

Textural Features ◽

Important Research ◽

Texture Characteristic ◽

Important Research Area ◽

Structural Methods ◽

Made In

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Activation of the intrinsic-apoptotic pathway in LNCaP prostate cancer cells by genistein- topotecan combination treatments

Functional Foods in Health and Disease ◽

10.31989/ffhd.v3i3.64 ◽

2013 ◽

Vol 3 (3) ◽

pp. 66 ◽

Cited By ~ 2

Author(s):

Vanessa Hörmann ◽

Sivanesan Dhandayuthapani ◽

James Kumi-Diaka ◽

Appu Rathinavelu

Keyword(s):

Prostate Cancer ◽

Cell Death ◽

Cancer Cells ◽

Apoptotic Cell ◽

Treatment Options ◽

Attractive Alternative ◽

Intrinsic Apoptotic Pathway ◽

Prostate Cancer Cells ◽

Apoptotic Pathway ◽

Combination Treatments

Background: Prostate cancer is the second most common cancer in American men. The development of alternative preventative and/or treatment options utilizing a combination of phytochemicals and chemotherapeutic drugs could be an attractive alternative compared to conventional carcinoma treatments. Genistein isoflavone is the primary dietary phytochemical found in soy and has demonstrated anti-tumor activities in LNCaP prostate cancer cells. Topotecan Hydrochloride (Hycamtin) is an FDA-approved chemotherapy for secondary treatment of lung, ovarian and cervical cancers. The purpose of this study was to detail the potential activation of the intrinsic apoptotic pathway in LNCaP prostate cancer cells through genistein-topotecan combination treatments. Methods: LNCaP cells were cultured in complete RPMI medium in a monolayer (70-80% confluency) at 37ºC and 5% CO2. Treatment consisted of single and combination groups of genistein and topotecan for 24 hours. The treated cells were assayed for i) growth inhibition through trypan blue exclusion assay and microphotography, ii) classification of cellular death through acridine/ ethidium bromide fluorescent staining, and iii) activation of the intrinsic apoptotic pathway through Jc-1: mitochondrial membrane potential assay, cytochrome c release and Bcl-2 protein expression.Results: The overall data indicated that genistein-topotecan combination was significantly more efficacious in reducing the prostate carcinoma’s viability compared to the single treatment options. In all treatment groups, cell death occurred primarily through the activation of the intrinsic apoptotic pathway.Conclusion: The combination of topotecan and genistein has the potential to lead to treatment options with equal therapeutic efficiency as traditional chemo- and radiation therapies, but lower cell cytotoxicity and fewer side effects in patients. Key words: topotecan; genistein; intrinsic apoptotic cell death

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Paeonol Inhibits Prostate Cancer Cell Invasion and Epithelial-Mesenchymal Transformation by Inactivation of STAT3 Pathway

Current Topics in Nutraceutical Research ◽

10.37290/ctnr2641-452x.19:15-20 ◽

2020 ◽

Vol 19 (1) ◽

pp. 15-20

Author(s):

Junyi Xiang ◽

Feng Huang ◽

Renhua Huang ◽

Jingzhan Su ◽

Yulong Liu

Keyword(s):

Prostate Cancer ◽

Treatment Options ◽

Surrogate Marker ◽

Cytotoxic Agents ◽

Potential Candidate ◽

Dependent Manner ◽

Ablation Therapy ◽

Androgen Ablation ◽

Mesenchymal Transformation ◽

Dose Dependent

Prostate cancer is one of the leading causes of death in men all over the world. Treatment options such as androgen ablation therapy and cytotoxic agents have many undesirable side effects, narrow therapeutic windows, or other limitations. In this research, we have explored the effects of paeonol on prostate cancer and its mechanism of action. Our results have shown that paeonol reduced the viability of prostate cancer cells in a dose-dependent manner. The wound-healing assay, a surrogate marker of tumor metastasis, showed that the relative wound width of 10 µM group was less than that of 50 µM paeonol-treated cells. Besides, the results of the transwell assay also showed that the number of migrated cells was significantly lower after treatment with 50 µM paeonol compared to the 10 µM group. The Western blot results showed that paeonol treatment induced a decrease in the mesenchymal markers (vimentin and N-cadherin), while the epithelial marker (E-cadherin) increased in a dose-dependent manner suggesting that paeonol effectively inhibits the epithelial-mesenchymal transformation in PC3 cells. Furthermore, the expression of STAT3 and p-STAT3 was also decreased after paeonol treatment, which indicated that the STAT3 signaling pathway was inhibited by paeonol. To conclude, the results summarized in this paper suggest that paeonol could be a potential candidate in the treatment of prostate cancer.

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Prostate cancer chemoprevention in men of African descent: current state of the art and opportunities for future research

Cancer Causes & Control ◽

10.1007/s10552-013-0241-x ◽

2013 ◽

Vol 24 (8) ◽

pp. 1465-1480 ◽

Cited By ~ 1

Author(s):

Ganna Chornokur ◽

Nagi B. Kumar

Keyword(s):

Prostate Cancer ◽

State Of The Art ◽

African Descent ◽

Cancer Chemoprevention ◽

Future Research ◽

Current State

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Decision Making from the Experience of Orthognathic Surgery Patients: A Grounded Theory Approach

JDR Clinical & Translational Research ◽

10.1177/23800844211014440 ◽

2021 ◽

pp. 238008442110144

Author(s):

N.R. Paul ◽

S.R. Baker ◽

B.J. Gibson

Keyword(s):

Decision Making ◽

Grounded Theory ◽

Treatment Options ◽

Study Data ◽

Primary Objective ◽

Major Surgery ◽

Future Research ◽

Decision Making Process ◽

Theory Approach

Introduction: Patients’ decisions to undergo major surgery such as orthognathic treatment are not just about how the decision is made but what influences the decision. Objectives: The primary objective of the study was to identify the key processes involved in patients’ experience of decision making for orthognathic treatment. Methods: This study reports some of the findings of a larger grounded theory study. Data were collected through face-to-face interviews of patients who were seen for orthognathic treatment at a teaching hospital in the United Kingdom. Twenty-two participants were recruited (age range 18–66 y), of whom 12 (male = 2, female = 10) were 6 to 8 wk postsurgery, 6 (male = 2, female = 4) were in the decision-making stage, and 4 (male = 0, female = 4) were 1 to 2 y postsurgery. Additional data were also collected from online blogs and forums on jaw surgery. The data analysis stages of grounded theory methodology were undertaken, including open and selective coding. Results: The study identified the central role of dental care professionals (DCPs) in several underlying processes associated with decision making, including legitimating, mediating, scheduling, projecting, and supporting patients’ decisions. Six categories were related to key aspects of decision making. These were awareness about their underlying dentofacial problems and treatment options available, the information available about the treatment, the temporality of when surgery would be undertaken, the motivations and expectation of patients, social support, and fear of the surgery, hospitalization, and potentially disliking their new face. Conclusion: The decision-making process for orthognathic treatment is complex, multifactorial, and heavily influenced by the role of DCPs in patient care. Understanding the magnitude of this role will enable DCPs to more clearly participate in improving patients’ decision-making process. The findings of this study can inform future quantitative studies. Knowledge Transfer Statement: The results of this study can be used both for informing clinical practice around enabling decision making for orthognathic treatment and also for designing future research. The findings can better inform clinicians about the importance of their role in the patients’ decision-making process for orthognathic treatment and the means to improve the patient experience. It is suggested that further research could be conducted to measure some of the key constructs identified within our grounded theory and assess how these change during the treatment process.

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AR Splicing Variants and Resistance to AR Targeting Agents

Cancers ◽

10.3390/cancers13112563 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2563

Author(s):

Mayuko Kanayama ◽

Changxue Lu ◽

Jun Luo ◽

Emmanuel S. Antonarakis

Keyword(s):

Prostate Cancer ◽

Androgen Receptor ◽

Splice Variants ◽

Treatment Options ◽

Predictive Biomarker ◽

Castration Resistant Prostate Cancer ◽

Treatment Benefit ◽

Novel Biomarkers ◽

The Many ◽

Preclinical And Clinical Studies

Over the past decade, advances in prostate cancer research have led to discovery and development of novel biomarkers and effective treatments. As treatment options diversify, it is critical to further develop and use optimal biomarkers for the purpose of maximizing treatment benefit and minimizing unwanted adverse effects. Because most treatments for prostate cancer target androgen receptor (AR) signaling, aberrations affecting this drug target are likely to emerge following the development of castration-resistant prostate cancer (CRPC), and it is conceivable that such aberrations may play a role in drug resistance. Among the many AR aberrations, we and others have been studying androgen receptor splice variants (AR-Vs), especially AR-V7, and have conducted preclinical and clinical studies to develop and validate the clinical utility of AR-V7 as a prognostic and potential predictive biomarker. In this review, we first describe mechanisms of AR-V generation, regulation and their functions from a molecular perspective. We then discuss AR-Vs from a clinical perspective, focusing on the significance of AR-Vs detected in different types of human specimens and AR-Vs as potential therapeutic targets.

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