#NAIRG_Publication🧠

🩻 We aimed to predict Montreal Cognitive Assessment (MoCA) scores in Parkinson’s disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and clinical (CF) features at year 0 (baseline) applied to hybrid machine learning systems (HMLSs)

📖 PDF file of this article is available in NAIRG channel

📋Title: Prediction of Cognitive Decline in Parkinson’s Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems


📥 Link :
https://www.mdpi.com/2075-4418/13/10/1691

📎 doi: https://doi.org/10.3390/diagnostics13101691

📎 Journal name:
Diagnostics 2023, 13(10), 1691;

📎 Authors:
Mahdi Hosseinzadeh
Arman Gorji
Ali Fathi Jouzdani
Seyed Masoud Rezaeijo
Arman Rahmim
Mohammad R. Salmanpour

📎 Result:
For the sole usage of RFs and DFs, ANOVA and MLP resulted in averaged accuracies of 59 ± 3% and 65 ± 4% for 5-fold cross-validation, respectively, with hold-out testing accuracies of 59 ± 1% and 56 ± 2%, respectively. For sole CFs, a higher performance of 77 ± 8% for 5-fold cross-validation and a hold-out testing performance of 82 + 2% were obtained from ANOVA and ETC. RF+DF obtained a performance of 64 ± 7%, with a hold-out testing performance of 59 ± 2% through ANOVA and XGBC. Usage of CF+RF, CF+DF

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📋 Title :
Prediction of Cognitive Decline in Parkinson’s Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems

📥 Link:
https://www.mdpi.com/2075-4418/13/10/1691#

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🎊🎉Happy New Year 🎉🎊

#NAIRG_Publication🧠
#Conferences

🩻Although the use of hand-crafted radiomics features (RF) has shown significant promise to improve diagnostic, prognostic, and treatment response assessments, employing deep features (DF) extracted from deep learning (DL) algorithms merits significant investigation in lung cancer disease. We aimed to employ RFs vs. DFs to predict recurrence-free survival (RFS) and overall survival (OS) using machine learning (ML) techniques in lung cancer.


📋 Title:

PET-CT Fusion Based Outcome Prediction in Lung Cancer using Deep and Handcrafted Radiomics Features and Machine Learning


📥 Link :
https://jnm.snmjournals.org/content/64/supplement_1/P1196.abstract

📎 Journal name:
Journal of Nuclear Medicine June 2023, 64 (supplement 1) P1196;

📎 Authors:

Arman Gorji
Ali Fathi Jouzdani
Nima Sanati
Mahdi Hosseinzadeh
Ali Mahboubisarighieh
Seyed Masoud Rezaeijo
Mehdi Maghsudi
Sara Moore
Leung Bonnie
Carlos Uribe
Cheryl Ho
Arman Rahmim
Mohammad R Salmanpour

📎 Result:
In RF framework, SR+ANOVA+MLP and VSMWLS+ANOVA+MLP resulted in MAEs of 506.7± 6.1 and 264.0±6.8 days to predict approximate death (OS) and approximate recurrence time (RFS) while we arrived at the lowest MSEs of 430.3±10.2 and 250.5±10.2 using DF supplied to LP_SR+ANOVA+MLP and CT+MRMR+ HistGB, respectively. In predictions of time to events such as OS and RFS, Wavelet+PCA+RadSF and NSCT_SR+PCA+RadSF linked with DFs obtained c-indexes of 0.59±0.03 and 0.61±0.01, while the highest c-indexes of 0.64 ±0.03 and 0.61±0.05 were obtained by RFs followed by CBF+PCA+RadSF and VSMWLS+PCA+RadSF, respectively.

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📝 Paraquat (PQ) is a nonselective herbicide that induces oxidative reactions and multiple-organ failure on exposure. Crocin, a carotenoid obtained from saffron, has demonstrated many therapeutic effects against neural conditions because of its antioxidant properties. In this study, 30 male Wistar rats were divided into 6 groups to evaluate the protective effects of crocin and crocin-loaded niosomes (NC) against PQ in the brain. The levels of total antioxidant capacity (TAC), lipid peroxidation (LPO), total thiol groups (TTG), superoxide dismutase (SOD), and catalase (CAT) activity were measured as the markers of redox status.

📖 PDF file of this article is available in NAIRG channel

📋 Title: Neuroprotective effects of crocin and crocin-loaded niosomes against the paraquat-induced oxidative brain damage in rats


📥 Link :
https://www.degruyter.com/document/doi/10.1515/biol-2022-0468/html

📎 doi: 
https://doi.org/10.1515/biol-2022-0468

📎 Journal name:
Published by De Gruyter Open Access September 14, 2022

📎 Authors:
Afsoon Daneshvar 
Ali Fathi Jouzdani 
Farzin Firozian 
Sara Soleimani Asl 
Mojdeh Mohammadi and Akram Ranjbar 

📎 Result:
1)The LPO level revealed that PQ induced a significant increase in LPO in the brain compared to control (P < 0.0001).

2)Treatments with crocin or NC resulted in minor differences in TAC levels compared with control, which was not significant.

3) crocin had a significant effect on TTG compared to control (P < 0.01).

4) The assessment of CAT activity revealed a significant difference between the control and all other groups

5)The assessment of SOD activity revealed a significant difference between the control and PQ (P < 0.01) and NC (P < 0.001) groups.

6)Histological evaluations revealed that the PQ-induced rats displayed a significant decrease in cell density in the CA1 region of the hippocampus compared to normal , crocin and NC (P < 0.001) groups. Treatments with crocin (P < 0.01) and NC (P < 0.001) plus PQ led to an enhancement in cell density of CA1 compared to the PQ group. Although treatment with crocin or NC showed no difference in cell count, the bulk and nanoformulations of crocin presented different effect levels in PQ-toxicity rats . No difference was seen between the crocin and NC groups compared to the control group

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📋 Title:
Neuroprotective effects of crocin and crocin-loaded niosomes against the paraquat-induced oxidative brain damage in rats

📎 doi: https://doi.org/10.1515/biol-2022-0468

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#Conferences

🩻Although many studies have focused on handcrafted radiomics features (RF), a much more indepth study, as follows in this study, is necessary to explore usage of deep RFs extracted from deep learning (DL) algorithms to assess survival analysis. We enrolled 215 lung cancer patients with PET, CT, and clinical data from The Cancer Imaging Archive and the Vancouver General Hospital. This study aims to assess 3 approaches, including comparison of i) PET vs. CT images; ii) different region of interests (ROI) used for deep RF extraction; and iii) deep vs. handcrafted RFs in prediction of overall survival (OS; regression task to predict exact time-to-death and survival probability) by hybrid machine learning systems (HMLS), including Analysis of Variance (ANOVA) and principal component analysis (PCA) linked with regression algorithms (RA).

📋 Title:

Region-of-Interest and Handcrafted vs. Deep Radiomics Feature Comparisons for Survival Outcome Prediction: Application to Lung PET/CT Imaging

📥 Link :

https://ieeexplore.ieee.org/document/10338394

📎 doi:
https://doi.org/10.1109/NSSMICRTSD49126.2023.10338394

📎Conference:
2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)


📎 Authors:
A Gorji
M Hosseinzadeh
A Fathi Jouzdani
N Sanati
F Yousefi Rizi
S Moore
B Leung
C Ho
I Shiri
H Zaidi
A Rahmim
MR Salmanpour

📎 Result:
In OS prediction, i) PET-based HMLSs outperformed CT-based HMLSs, ii) deep RFs extracted from the cropped images outperformed deep RFs extracted from other ROIs, receiving the highest mean absolute error (MAE) of 595±126 [range 36-5596 days] by ANOVA+support vector regression, and iii) deep RFs significantly outperformed handcrafted RFs. In survival probability prediction, i) PET-based HMLSs outperformed CT based HMLSs, ii) PET-based deep RFs extracted from the entire image outperformed deep RFs extracted from other ROIs, having the highest c-index of 0.65±0.05 through PCA+Random Survival Forest, and iii) deep RFs outperformed handcrafted RFs

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#Conferences

📋 Title:
Region-of-Interest and Handcrafted vs. Deep Radiomics Feature Comparisons for Survival Outcome Prediction: Application to Lung PET/CT Imaging

📎 doi:

https://doi.org/10.1109/NSSMICRTSD49126.2023.10338394


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📢 Research Talk Series

🗣 Session I: Effective Time Management and Scientific Success in a Very Busy and Distracted World

🎙️ Speaker: Prof. Rahmim
🏢 Affiliation: University of British Columbia (UBC)
👨‍🏫 Position: Professor of Radiology, Physics, and Biomedical Engineering

📅 Date: April 25, 2024
⏰ Time: 19:30 Tehran Time/ 8 Vancouver Time

‼️ Admission: Free


🔗 Register now

https://docs.google.com/forms/d/e/1FAIpQLScJnaQx0P9IGg4GTbEc9Cw5bzmSXNqTktKiMAKpqrnjkxX49g/viewform?usp=sf_link


📢 @NAIRG_Channel.

This first session focuses on: Effective Time Management and Scientific Success in a Very Busy and Distracted World.

Date: April 25, 2024
Time: 19:30 Tehran Time/ 8:00 Vancouver Time

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Dear Colleagues,

This is a gentle reminder that our insightful talk titled "Effective Time Management and Scientific Success in a Very Busy and Distracted World" will commence shortly.

Date: April 25, 2024
Time: 19:30 Tehran Time / 9:00 Vancouver Time

Join us via Zoom at:

Please send a PM to @DendriteDreamer to receive the Zoom link!

If you encounter any difficulties accessing the Zoom link, please try using a VPN in case there are any restrictions. Should you have any inquiries or require assistance with the Zoom platform, please do not hesitate to reach out.

I eagerly anticipate your participation in what promises to be an engaging and enlightening discussion.

Warm regards,

📣  کمیته تحقیقات و فناوری دانشجویی دانشگاه علوم پزشکی همدان با همکاری انجمن علمی علوم اعصاب برگزار می‌کند:

📝 کارگاه پنج جلسه ای پایتون

۱۹ آبان۱۴۰۳: مقدمه ای بر پایتون
۲۶ آبان ۱۴۰۳: فراخوانی داده
۳ آذر ۱۴۰۳: پیش پردازش داده ها
۱۰ آذر ۱۴۰۳: آنالیز آماری
۱۷ آذر ۱۴۰۳: رسم شکل

🗣 مدرس: دکتر سجاد فراشی

⏰ ساعت ۱۶ الی ۱۸

💰هزینه ثبت نام: رایگان

📑 همراه با گواهی

🛑ظرفیت محدود (۱۰ نفر)

📥لینک ثبت نام :https://forms.gle/r1FmPUXX74Je8moY7

🏠محل برگزاری: توسط پیامک برای 10 نفر اول ارسال میشود

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