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Time management: Improving the timing of post-prostatectomy radiotherapy, clinical trials, and knowledge translation
مدیریت زمان: بهبود زمان رادیوتراپی پس از پروستاتکتومی، آزمایشات بالینی و ترجمه دانش-2021 Background: Management of prostate cancer after surgery is controversial. Past studies on adjuvant radiotherapy
(aRT) for higher-risk features have had conflicting results. Through the collaborative conversations of the global
radiation oncology Twitter-based journal club (#RadOnc #JC), we explored this complex topic to share recent
advances, better understand what the global radiation oncology community felt was important and inspire next
steps.
Methods: We selected the recent publication of a landmark international randomized controlled trial (RCT)
comparing immediate and salvage radiotherapy for prostate cancer, RADICALS-RT, for discussion over the
weekend of January 16 to 17, 2021. Coordination included open access to the article and an asynchronous
portion to decrease barriers to participation, cooperation of study authors (CP, MS) who participated to share
deeper insights including a live hour, and curation of related resources and tweet content through a blog post and
Wakelet journal club summary.
Discussion of Results: Our conversations created 2,370,104 impressions over 599 tweets with 51 participants
spanning 11 countries and 5 continents. A quarter of the participants were from the US (13/51) followed by 10%
from the UK (5/51). Clinical or Radiation Oncologists comprised 59% of active participants (16/27) with 62%
(18/29) reporting giving aRT within the last 5 years. Discussion was interdisciplinary with three urologists
(11%), three trainees (11%), and two physiotherapists (7%). Four months after the journal club its article Altmetric
score had increased by 7% (214 to 229). Thematic analysis of tweet content suggested participants wanted
clarification on definitions of adjuvant (aRT) and salvage radiotherapy (sRT) including indications, timing, and
decision-making tools including guidelines; more interdisciplinary and cross-sectoral collaboration including
with patients for study design including survivorship and meaningful outcomes; more effective knowledge
translation including faster clinical trials; and more data including mature results of current trials, particular
high-risk features (Gleason Group 4+, pT4b+, and margin-positive disease), implications of newer technologies
such as PSMA-PET and genomic classifiers, and better explanations for practice pattern variations including
underutilization of radiotherapy. This was further explored in the context of relevant literature.
Conclusion: Together, this global collaborative review on the postoperative management of prostate cancer
suggested a stronger signal for the uptake of early salvage radiation treatment with careful PSA monitoring, more
sensitive PSA triggers, and expected access to radiotherapy. Questions still remain on potential exceptions and barriers to use. These require better decision-making tools for all practice settings, consideration of newer
technologies, more pragmatic trials, and better use of social media for knowledge translation.
Keywords: Prostate radiotherapy | Adjuvant radiation | Salvage radiation | Journal club |
مقاله انگلیسی |
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Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images
تقسیم بندی دقیق و قوی بر اساس یادگیری عمیق از حجم هدف بالینی پروستات در تصاویر سونوگرافی-2019 The goal of this work was to develop a method for accurate and robust automatic segmentation of the prostate clinical target volume in transrectal ultrasound (TRUS) images for brachytherapy. These images can be difficult to segment because of weak or insufficient landmarks or strong artifacts. We devise a method, based on convolutional neural networks (CNNs), that produces accurate segmentations on easy and difficult images alike. We propose two strategies to achieve improved segmentation accuracy on diffi- cult images. First, for CNN training we adopt an adaptive sampling strategy, whereby the training process is encouraged to pay more attention to images that are difficult to segment. Secondly, we train a CNN ensemble and use the disagreement among this ensemble to identify uncertain segmentations and to estimate a segmentation uncertainty map. We improve uncertain segmentations by utilizing the prior shape information in the form of a statistical shape model. Our method achieves Hausdorffdistance of 2.7 ±2.3 mm and Dice score of 93.9 ±3.5%. Comparisons with several competing methods show that our method achieves significantly better results and reduces the likelihood of committing large segmentation errors. Furthermore, our experiments show that our approach to estimating segmentation uncertainty is better than or on par with recent methods for estimation of prediction uncertainty in deep learning mod- els. Our study demonstrates that estimation of model uncertainty and use of prior shape information can significantly improve the performance of CNN-based medical image segmentation methods, especially on difficult images. Keywords: Image segmentation | Model uncertainty | Shape models | Clustering | Deep learning |
مقاله انگلیسی |
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Microarray-based data mining reveals key genes and potential therapeutic drugs for Cadmium-induced prostate cell malignant transformation
داده کاوی مبتنی بر ریزآرایه ژنهای کلیدی و داروهای درمانی بالقوه را برای تحول بدخیم سلولهای پروستات ناشی از کادمیوم-2019 Increasing evidence showed that Cadmium (Cd) can accumulate in the body and damage cells, resulting in
cancerigenesis of the prostate with complex mechanisms. In the present study, we aimed to explore the possible
key genes, pathways and therapeutic drugs using bioinformatics methods. Microarray-based data were retrieved
and analyzed to screen differentially expressed genes (DEGs) between Cd-treated prostate cells and controls.
Then, functions of the DEGs were annotated and hub genes were screened. Next, key genes were selected from
the hub genes via validation in a prostate cancer cohort from The Cancer Genome Atlas (TCGA). Afterward,
potential drugs were further predicted. Consequently, a gene expression profile, GSE9951, was retrieved. Then,
361 up-regulated and 30 down-regulated DEGs were screened out, which were enriched in various pathways.
Among the DEGs, seven hub genes (HSPA5, HSP90AB1, RHOA, HSPD1, MAD2L1, SKP2, and CCT2) were dysregulated
in prostate cancer compared to normal controls, and two of them (HSPD1 and CCT2) might influence
the prostate cancer prognosis. Lastly, ionomycin was predicted to be a potential agent reversing Cd-induced
prostate cell malignant transformation. In summary, the present study provided novel evidence regarding the
mechanisms of Cd-induced prostate cell malignant transformation, and identified ionomycin as a potential small
molecule against Cd toxicity. Keywords: Cadmium | Differentially expressed genes | Prostate carcinoma | TCGA | Bioinformatics |
مقاله انگلیسی |
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Protein expression information of prostate infection based on data mining
اطلاعات بیانی پروتئین از عفونت پروستات بر اساس داده کاوی-2019 In order to deeply explore the interaction between prostate cancer (PCa)-related proteins and to screenout effective targets for clinical practice, data mining of PCa proteomics literature is conducted, 41 dif-ferentially expressed seed proteins are identified, and a protein interaction network is constructed. Theextended network consists of a mega network and three separate small parts, which are used to findkey nodes and build a backbone network through connectivity screening. Topological analysis of thesenetworks reveals that solute carrier family 2 (glucose transporter) member 4 (SLC2A4) and tubulin -2C(TUBB2C) are centrally located in the protein interaction network. In addition, by using the module anal-ysis, the dense connection area is found. Functional annotations indicate that the biological processesof Ras protein signaling, mitogen-activated protein kinase (MAPK), and neurotrophin and gonadotropin-releasing hormone (GnRH) signaling pathways play important roles in the pathogenesis of PCa. Therefore,further studies of SLC2A4 and TUBB2C proteins, and these biological processes and pathways may providepotential targets for the diagnosis and treatment of PCa. Keywords:Data mining | Protein interaction network | Prostate cancer| Connectivity| Protein expression |
مقاله انگلیسی |
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Comparison of deep learning-based and patch-based methods for pseudo-CT generation in MRI-based prostate dose planning
مقایسه روشهای مبتنی بر یادگیری عمیق و مبتنی بر پچ برای تولید شبه CT در برنامه ریزی دوز پروستات مبتنی بر MRI-2019 Purpose
Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT)
for MRI-based dose planning. This study aims to evaluate and compare DLMs (U-Net and
generative adversarial network (GAN)) using various loss functions (L2, single-scale
perceptual loss (PL), multiscale PL, weighted multiscale PL), and a patch-based method
(PBM).
Materials and Methods
Thirty-nine patients received a VMAT for prostate cancer (78 Gy). T2-weighted MRIs were
acquired in addition to planning CTs. The pCTs were generated from the MRIs using seven
configurations: four GANs (L2, single-scale PL, multiscale PL, weighted multiscale PL), two
U-Net (L2 and single-scale PL), and the PBM. The imaging endpoints were mean absolute
error (MAE) and mean error (ME), in Hounsfield units (HU), between the reference CT
(CTref) and the pCT. Dose uncertainties were quantified as mean absolute differences between
the DVHs calculated from the CTref and pCT obtained by each method. 3D gamma indexes
were analyzed
Results
Considering the image uncertainties in the whole pelvis, GAN L2 and U-Net L2 showed the
lowest MAE (≤34.4 HU). The ME were not different than 0 (p≤0.05). The PBM provided the
highest uncertainties. Very few DVH points differed when comparing GAN L2 or U-Net L2
DVHs and CTref DVHs (p≤0.05). Their dose uncertainties were: ≤0.6% for the prostate PTV
V95%, ≤0.5% for the rectum V70Gy, and ≤0.1% for the bladder V50Gy. The PBM, U-Net PL and
GAN PL presented the highest systematic dose uncertainties. The gamma passrates were
>99% for all DLMs. The mean calculation time to generate one pCT was 15 s for the DLMs
and 62 min for the PBM.
Conclusion
Generating pCT for MRI dose planning with DLMs and PBM provided low dose
uncertainties. In particular, the GAN L2 and U-Net L2 provided the lowest dose uncertainties
together with a low computation time. Keywords: pseudo-CT generation | MRI-only radiotherapy | deep learning | dose calculation | prostate cancer |
مقاله انگلیسی |
6 |
ویژگیهای توجه عمیق برای جداسازی پروستات در فراوادرمانی
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 14 جداسازی خودکار پروستات در فراوادرمانی ترانسرکتال (TRUS) برای بافتبرداری تصاویر هدایتشدهی پروستات و برنامهریزی درمان بسیار حائر اهمیت میباشد. همچنین بهدلیل مرز مبهم و توزیع شدت غیرهمگن پروستات در TRUS، توسعه دادن اینگونه راهحلهای خودکار هنوز چالشبرانگیز باقیمانده است. در این پژوهش، یک شبکهی عصبی عمیق جدید که با ماژولهای ویژگی توجه عمیق (DAF) مجهز شده است، برای جداسازی بهتر پروستات در TRUS با استفاده از استخراج کردن اطلاعات مکمل کدگذاریشده در لایههای مختلف شبکهی عصبی پیچشی (CNN) توسعه داده شده است. همچنین DAF متعلق به ما جهت انتخاب قدرت نفوذ ویژگیهای چندگانهی ادغامشده از طریق لایههای مختلف برای تصحیح کردن ویژگیهای هر لایهی منحصربهفرد، متوقف کردن سروصدای غیرپروستات در لایههای کمعمق CNN و افزایش دادن تعداد جزئیات پروستات درون ویژگیهای لایههای عمیق از مکانیزم توجه استفاده میکند. ما تأثیر شبکهی پیشنهادی را بر روی تصاویر چالشبرانگیز TRUS پروستات و همچنین نتایج تجربی ارزیابی میکنیم تا عملکرد بهتر روشهای نوین را بهوسیلهی یک تفاوت مزیت بزرگ نشان دهیم. |
مقاله ترجمه شده |
7 |
اکسی توسین و سرطان: یک پیوند نوظهور
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 24 هورمون نوروپپتیدی اکسی توسین که از غده ی هیپوفیز خلفی آزاد می شود در برخی فرایندهای فیزیولوژیکی نقش دارد. درک تأثیرات آن به تدریج رو به افزایش است، این به لطف پژوهش های جدید در این حوزه است. اکسی توسین در عین حال که به عنوان یک هورمون دستگاه تولیدمثل شناخته می شود، سایر سیستم های اندامی همچون مغز و سیستم قلبی عروقی را نیز تنظیم می کند. اخیراً پژوهش ها بر بررسی نقش آن در سرطان تمرکز نموده اند و شواهد نوظهور، نقش احتمالی اکسی توسین به عنوان نشانگر زیستی سرطان را نشان می دهند. این مقاله ی مروری، مشاهدات پیونددهنده ی اکسی توسین و سرطان را بیان می کند و تأکید ویژه ای بر سرطان پروستات دارد، در این وضعیت اکسی توسین می تواند تکثیر سلولی را بهبود بخشد. پژوهش ها نشان می دهد اثرات اکسی توسین می توانند به نوع سلول، غلظت هورمون، برهم کنش های آن با سایر هورمون ها در ریزمحیط ها، و موقعیت دقیق گیرنده ی آن در غشای سلول بستگی داشته باشند. بایستی پژوهش های آتی به تبیین هرچه بیشتر نقش اکسی توسین در سرطان بپردازند و مشخص کنند آیا این می تواند یک نشانگر زیستی بالینی برای سرطان یا هدف درمانی باشد یا خیر.
کلیدواژه ها: اکسی توسین | سرطان | پروستات | پانکراس | ورزش |
مقاله ترجمه شده |
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Increased risk of 30-day postoperative complications for diabetic patients following open reduction-internal fixation of proximal humerus fractures: an analysis of 1391 patients from the American College of Surgeons National Surgical Quality Improvement Program database
افزایش خطر عوارض بعد از عمل 30 روزه برای بیماران دیابتی پس از باز شدن فیکسچر بازسازی داخلی شکستگی های انسداد پروستات: یک مطالعه از 1391 بیمار از پایگاه داده برنامه جامع جراحی کالج آمریکایی جراحان-2017 Keywords: Proximal humerus fractures | Diabetes | Postoperative complications | NSQIP | Open reduction-internal fixation | Insulin-dependent diabetes |
مقاله انگلیسی |
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Patient characterization and usage trends of proton beam therapy for localized prostate cancer in the United States: A study of the National Cancer Database
ویژگی های بیمار و روند استفاده از درمان پرتو پروتون برای سرطان پروستات موضعی در ایالات متحده: مطالعه پایگاه ملی سرطان-2017 Purpose: To evaluate usage trends and identify factors associated with proton beam therapy (PBT) compared to alternative forms of
external beam radiation therapy (RT) (EBRT) for localized prostate cancer.
Patients and Methods: The National Cancer Database was queried for men with localized (N0, M0) prostate cancer diagnosed between
2004 and 2013, treated with EBRT, with available data on EBRT modality (photon vs. PBT). Binary multiple logistic regression identified
variables associated with EBRT modality.
Results: In total, 143,702 patients were evaluated with relatively few men receiving PBT (5,709 [4.0%]). Significant differences in
patient and clinical characteristics were identified between those men treated with PBT compared to those treated with photon (odds ratio
[OR]; 95% CI). Patients treated with PBT were generally younger (OR ¼ 0.73; CI: 0.67–0.82), National Comprehensive Cancer Network
low-risk compared to intermediate (0.71; 0.65–0.78) or high (0.44; 0.38–0.5) risk, white vs. black race (0.66; 0.58–0.77), with less
comorbidity (Charlson-Deyo 0 vs. 2þ; 0.70; 0.50–0.98), live in higher income counties (1.55; 1.36–1.78), and live in metropolitan areas
compared to urban (0.21; 0.18–0.23) or rural (0.14; 0.10–0.19) areas. Most patients treated with PBT travelled more than 100 miles to the
treatment facility. Annual PBT utilization significantly increased in both total number and percentage of EBRT over time (2.7%–5.6%;
P o 0.001). PBT utilization increased mostly in men classified as National Comprehensive Cancer Network low-risk (4%–10.2%).
Conclusion: PBT for men with localized prostate cancer significantly increased in the United States from 2004 to 2013. Significant
demographic and prognostic differences between those men treated with photons and protons were identified. r 2017 Elsevier Inc. All
rights reserved.
Keywords: Prostate cancer | Protons | Photons | Patterns of care | Utilization | National Cancer Database (NCDB) |
مقاله انگلیسی |
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Clinical and Psychosocial Predictors of Urologic Chronic Pelvic Pain Symptom Change Over One Year: A Prospective Study from the MAPP Research Network
پیش بینی های بالینی و روانی اجتماعی علائم درد مزمن لگن اورولوژیک بیش از یک سال: مطالعه آینده ای از شبکه تحقیقاتی MAPP-2017 OBJECTIVE: To examine baseline clinical and psychosocial characteristics that predict 12-
month symptom change in men and women with urologic chronic pelvic pain syndromes
(UCPPS).
METHODS: 221 female and 176 male UCPPS patients were recruited from 6 academic medica
centers in the United States and evaluated at baseline with a comprehensive battery of symptom
psychosocial, and illness-impact measures. Based on biweekly symptom reports, a functional
clustering procedure classified participant’s outcome as worse, stable, or improved on pain and
urinary symptom severity. Cumulative logistic modeling was used to examine individual
predictors associated with symptom change as well as multiple predictor combinations and
interactions.
RESULTS: About 60% of participants had stable symptoms with smaller numbers (13% to 22%
showing clear symptom worsening or improvement. For both pain and urinary outcomes the
extent of widespread pain, amount of non-urological symptoms and poorer overall health were
predictive of worsening outcomes. Anxiety, depression and general mental health were not
significant predictors of outcomes, but pain catastrophizing and self-reported stress were
associated with pain outcome. Prediction models did not differ between men and women and for
the most part were independent of symptom duration and age.
CONCLUSION: These results demonstrate for the first time in a large multisite prospective
study that presence of widespread pain, non-urological symptoms and poorer general health are
risk factors for poorer pain and urinary outcomes in both men and women. The results point to
the importance of broad based assessment in UCPPS and future studies of mechanisms that
underlie these findings.
Key words: nterstitial cystitis | chronic prostatitis | chronic overlapping pain conditions | quality of life |
مقاله انگلیسی |