Journal of Medical Physics
 Home | Search | Ahead of print | Current Issue | Archives | Instructions | Subscription | Login The official journal of AMPI, IOMP and AFOMP      
 Users online: 642  Home  EMail this page Print this page Decrease font size Default font size Increase font size 
Export selected to
Endnote
Reference Manager
Procite
Medlars Format
RefWorks Format
BibTex Format
   Table of Contents - Current issue
Coverpage
July-September 2021
Volume 46 | Issue 3
Page Nos. 135-230

Online since Wednesday, September 8, 2021

Accessed 6,514 times.

PDF access policy
Journal allows immediate open access to content in HTML + PDF

EPub access policy
Full text in EPub is free except for the current issue. Access to the latest issue is reserved only for the paid subscribers.
View as eBookView issue as eBook
Access StatisticsIssue statistics
RSS FeedRSS
Hide all abstracts  Show selected abstracts  Export selected to  Add to my list
REVIEW ARTICLE  

Paradigm shift in radiation treatment planning over multiple treatment modalities Highly accessed article p. 135
Benjamin Insley, I-Chow Hsu, J Adam Martin Cunha
DOI:10.4103/jmp.JMP_66_20  
The inverse planning simulated annealing optimization engine was used to develop a new method of incorporating biological parameters into radiation treatment planning. This method integrates optimization of a radiation schedule over multiple types of delivery methods into a single algorithm. We demonstrate a general procedure of incorporating a functional biological dose model into the calculation of physical dose prescriptions. This paradigm differs from current practice in that it combines biology-informed dose constraints with a physical dose optimizer allowing for the comparison of treatment plans across multiple different radiation types and fractionation schemes.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta
ORIGINAL ARTICLES Top

Magnetic resonance neurography of the brachial plexus using 3D SHINKEI: Comparative evaluation with conventional magnetic resonance sequences for the visualization of anatomy and detection of nerve injury at 1.5t Highly accessed article p. 140
Prashant Prabhakaran Nair, Yogesh K Mariappan, Samir M Paruthikunnan, Asha Kamath, Narayana K Rolla, Indrajit Saha, Rajagopal Kadavigere
DOI:10.4103/jmp.JMP_13_21  
Background and Purpose: This work aims at optimizing and studying the feasibility of imaging the brachial plexus at 1.5T using 3D nerve-SHeath signal increased with INKed rest-tissue RARE imaging (3D SHINKEI) neurography sequence by comparing with routine sequences. Materials and Methods: The study was performed on a 1.5T Achieva scanner. It was designed in two parts: (a) Optimization of SHINKEI sequence at 1.5T; and (b) Feasibility study of the optimized SHINKEI sequence for generating clinical quality magnetic resonance neurography images at 1.5T. Simulations and volunteer experiments were conducted to optimize the T2 preparation duration for optimum nerve-muscle contrast at 1.5T. Images from the sequence under study and other routine sequences from 24 patients clinically referred for brachial plexus imaging were scored by a panel of radiologists for diagnostic quality. Injury detection efficacy of these sequences were evaluated against the surgical information available from seven patients. Results: T2 preparation duration of 50 ms gives the best contrast to noise between nerve and muscle. The images of 3D SHINKEI and short-term inversion recovery turbo spin-echo sequences are of similar diagnostic quality but significantly better than diffusion weighted imaging with background signal suppression. In comparison with the surgical findings, 3D SHINKEI has the lowest specificity; however, it had the highest sensitivity and predictive efficacy compared to other routine sequences. Conclusion: 3D SHINKEI sequence provides a good nerve–muscle contrast and has high predictive efficacy of nerve injury, indicating that it is a potential screening sequence candidate for brachial plexus scans at 1.5T also.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

The dynamic(s) of adipose stem cell system, their survival, and cessation under the influence of electromagnetic fields Highly accessed article p. 148
Anna Trzyna, Dorota B Bądziul, Paweł Jakubczyk, Damian S Bocak, Marian Cholewa, Agnieszka Banaś-Ząbczyk
DOI:10.4103/jmp.JMP_10_21  
Context The electromagnetic field (EMF) is one of the external biophysical factors that can influence stem cells' structure and functionality. Depending on its frequency and magnetic flux density, EMF can have both a positive and negative effect on stem cell biology. Aims: The aim of the study is to define EMF conditions that support beneficial physiological processes and those that lead to pathophysiological phenomena. Understanding the changes and processes occurring in stem cells after exposure to EMFs of different parameters can be an important factor to be applied in stem cell-based therapies and regenerative medicine. Materials and Methods: In this study, using fluorescent microscopy and flow cytometry methods, the influence of EMF on adipose-derived stem cells proliferation, cell cycle, viability, and death were examined. EMF parameters were set in accordance with the ion cyclotron resonance (ICR) theory that influences Ca2+ and Mg2+ ions influx. Results were statistically developed using the ANOVA and effect size (Cohen's d) analyses. Results In this study, the continuous exposure of adipose-derived stem cells to EMF (ICR parameters: 76.6 Hz; 20 μT) causes a statistically significant increase in cell death through the enhancement of apoptotic, necrotic, and autophagic cell numbers. Apart from increased cell deaths after EMF exposure, increased proliferation after 24 h of EMF exposure has been also observed. Conclusions Results presented in this study show that EMF influences stem cell dynamics resulting in a significantly increased cell death, thus altering the stem cell fate. It is important to further establish EMF conditions that support ASCs functioning and beneficial physiological processes for future regenerative medical purposes.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Synthesis, characterization, and cytotoxicity evaluation of polyethylene glycol-coated iron oxide nanoparticles for radiotherapy application p. 154
Madhuri Anuje, Padmaja N Pawaskar, Vishwajeet Khot, Ajay Sivan, Satish Jadhav, Jagruti Meshram, Balu Thombare
DOI:10.4103/jmp.JMP_102_20  
Background: Treatment methods for cancer that are widely being utilized affect both normal and cancerous cells. We report synthesis polyethylene glycol (PEG)-coated Fe3O4 nanoparticles (NPs) and its characteristic properties and appraise its potential as a promising radiation sensitizer candidate in radiotherapy that improves cancer treatment and reduces side effects of radiation. Materials and methods: PEG-coated Fe3O4 NPs were synthesized by chemical coprecipitation method and characterized by studying their size, structure, functional group, stability, magnetization, and cytotoxicity using different techniques. X-ray powder diffraction, Fourier transform infrared spectroscopy, and thermogravimetric analysis results show that Fe3O4 NPs have been functionalized with PEG molecules during the course of synthesis. Results Synthesized NPs have good stability based on zeta-potential study. Dynamic light-scattering results reveal that PEG-coated Fe3O4 has a greater hydrodynamic size than bare Fe3O4. Transmission electron microscopy (TEM) micrograph exhibited that NPs are roughly spherical with size in range of 10–20 nm. Saturation magnetization value of PEG-coated and bare Fe3O4 also confirms coating and shows superparamagnetic behavior. Cytotoxicity evaluation study indicated that PEG-coated Fe3O4 is biocompatible on L929 and toxic on Michigan Cancer Foundation-7 (MCF-7) (breast cancer cells). Conclusion: These characterized properties of PEG-coated Fe3O4 NPs show that it could be used as a potential radiosensitizer candidate in radiotherapy to significantly improve cancer treatment and minimize painful side effects of radiation.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Implementation and challenges of international atomic energy agency/american association of physicists in medicine trs 483 formalism for field output factors and involved uncertainties determination in small fields for tomotherapy p. 162
Rajesh Kinhikar, Suryakant Kaushik, Chandrashekhar Tambe, Sudarshan Kadam, Shrikant Kale, Rituraj Upreti
DOI:10.4103/jmp.JMP_11_21  
Purpose International Atomic Energy Agency published TRS-483 to address the issues of small field dosimetry. Our study calculates the output factor in the small fields of TomoTherapy using different detectors and dosimetric conditions. Furthermore, it estimates the various components of uncertainty and presents challenges faced during implementation. Materials and Methods Beam quality TPR20,10(10) at the hypothetical field size of 10 cm × 10 cm was calculated from TPR20,10(S). Two ionization chambers based on the minimum field width required to satisfy the lateral charge particle equilibrium and one unshielded electron field diode (EFD) were selected. Output factor measurements were performed in various dosimetric conditions. Results Beam quality TPR20,10(10) has a mean value of 0.627 ± 0.001. The maximum variation of output factor between CC01 chamber and EFD diode at the smallest field size was 11.80%. In source to surface setup, the difference between water and virtual water was up to 9.68% and 8.13%, respectively, for the CC01 chamber and EFD diode. The total uncertainty in the ionization chamber was 2.43 times higher compared to the unshielded EFD diode at the smallest field size. Conclusions Beam quality measurements, chamber selection procedure, and output factors were successfully carried out. A difference of up to 10% in output factor can occur if density scaling for electron density in virtual water is not considered. The uncertainty in output correction factors dominates, while positional and meter reading uncertainty makes a minor contribution to total uncertainty. An unshielded EFD diode is a preferred detector in small fields because of lower uncertainty in measurements compared to ionization chambers.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Estimating absorbed dose to breast adipose tissue from mammograms p. 171
Al Maqsudur Rashid, Rabin Dhakal, Hanna Moussa
DOI:10.4103/jmp.JMP_27_21  
Purpose Breast cancer usually originates in the glandular tissue of the breast. However, inflamed adipose tissue surrounding glandular tissue may expedite the local growth of cancerous cells. Exposing adipose tissue to radiation during mammography might cause inflammation in adipose tissue. This inflammation depends on the dose, and thus on the energy deposited from the X-ray mammography. Therefore, estimating the absorbed dose to adipose tissue during mammography is essential in breast cancer research. Materials and Methods Absorbed dose to adipose tissue in the breast is determined using a new geometrical (semi-elliptical) model and Monte Carlo N-Particle transport code (MCNP6). X-ray mammogram images of patient breasts were taken as the basis of the new compressed breast geometry. The source probability density used in the MCNP6 code was generated from a published X-ray spectrum corresponding to tube voltage and air kerma. The relationship between various mammogram parameters such as peak tube voltage, compressed breast thickness, and adipose tissue weight fraction versus estimated absorbed dose is established for analysis. Results Significant influences of adipose tissue weight fraction on absorbed dose were observed. Conclusion Estimating the absorbed dose to breast adipose tissue during mammography and patients' degree of obesity are important factors in breast cancer research.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Framework for machine learning of ct and pet radiomics to predict local failure after radiotherapy in locally advanced head and neck cancers p. 181
Devadhas Devakumar, Goutham Sunny, Krishna Balu, Stephen R Bowen, Ambily Nadaraj, L Jeyseelan, Manu Mathew, Aparna Irodi, Rajesh Isiah, Simon Pavamani, Subhashini John, Hannah Mary T. Thomas
DOI:10.4103/jmp.JMP_6_21  
Context: Cancer Radiomics is an emerging field in medical imaging and refers to the process of converting routine radiological images that are typically qualitatively interpreted to quantifiable descriptions of the tumor phenotypes and when combined with statistical analytics can improve the accuracy of clinical outcome prediction models. However, to understand the radiomic features and their correlation to molecular changes in the tumor, first, there is a need for the development of robust image analysis methods, software tools and statistical prediction models which is often limited in low- and middle-income countries (LMIC). Aims: The aim is to build a framework for machine learning of radiomic features of planning computed tomography (CT) and positron emission tomography (PET) using open source radiomics and data analytics platforms to make it widely accessible to clinical groups. The framework is tested in a small cohort to predict local disease failure following radiation treatment for head-and-neck cancer (HNC). The predictors were also compared with the existing Aerts HNC radiomics signature. Settings and Design: Retrospective analysis of patients with locally advanced HNC between 2017 and 2018 and 31 patients with both pre- and post-radiation CT and evaluation PET were selected. Subjects and Methods: Tumor volumes were delineated on baseline PET using the semi-automatic adaptive-threshold algorithm and propagated to CT; PyRadiomics features (total of 110 under shape/intensity/texture classes) were extracted. Two feature-selection methods were tested for model stability. Models were built based on least absolute shrinkage and selection operator-logistic and Ridge regression of the top pretreatment radiomic features and compared to Aerts' HNC-signature. Average model performance across all internal validation test folds was summarized by the area under the receiver operator curve (ROC). Results: Both feature selection methods selected CT features MCC (GLCM), SumEntropy (GLCM) and Sphericity (Shape) that could predict the binary failure status in the cross-validated group and achieved an AUC >0.7. However, models using Aerts' signature features (Energy, Compactness, GLRLM-GrayLevelNonUniformity and GrayLevelNonUniformity-HLH wavelet) could not achieve a clear separation between outcomes (AUC = 0.51–0.54). Conclusions: Radiomics pipeline included open-source workflows which makes it adoptable in LMIC countries. Additional independent validation of data is crucial for the implementation of radiomic models for clinical risk stratification.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Deep learning approach for analyzing the COVID-19 chest x-rays p. 189
Mohini Manav, Monika Goyal, Anuj Kumar, AK Arya, Hari Singh, Arun Kumar Yadav
DOI:10.4103/jmp.JMP_22_21  
Purpose The purpose of this study is to analyze the utility of Convolutional Neural Network (CNN) in medical image analysis. In this study, deep learning (DL) models were used to classify the X-ray into COVID, viral pneumonia, and normal categories. Materials and Methods In this study, we have compared the results 9 layers CNN model (9 LC) developed by us with 2 transfer learning models (Visual Geometry Group) 16 and VGG19. Two different datasets used in this study were obtained from the Kaggle database and the Radiodiagnosis department of our institution. Results In our study, VGG16 yields the highest accuracy among all three models for different datasets as the Kaggle dataset-94.96% and the department of Radiodiagnosis dataset 85.71%. Although, the precision was found better while using 9 LC and VGG19 for both datasets. Conclusions DL can help the radiologists in the speedy prediction of diseases and detecting minor features of the disease which may be missed by the human eye. In the present study, we have used three models, i.e.,, CNN with 9 LCs, VGG16, and VGG19 transfer learning models for the classification of X-ray images with good accuracy and precision. DL may play a key role in analyzing the medical image dataset.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Validation of American association of physicists in medicine tg 43 dosimetry data in commercial treatment planning system p. 197
Sathiyan Saminathan, K Maheshraja, KM Ganesh
DOI:10.4103/jmp.JMP_20_21  
Aims This study aimed to validate the dosimetric data of low-energy photon-emitting low-dose rate (LE-LDR) brachytherapy seed sources in commercial treatment planning system (TPS). Materials and Methods The LE-LDR seed sources dosimetric data were published in the American Association of Physicists in Medicine (AAPM) Task Group reports TG-43 (1995), TG-43U1 (2004), TG-43U1S1 (2007), and TG-43U1S2. The Bhabha Atomic Research centre (BARC) 125I Ocu-Prosta seed dosimetry data are also available in the literature. The commercially available TPSs are using both two-dimensional (cylindrically symmetric line-source) and one-dimensional (1D) (point source) dose-calculation formalisms. TPS used in this study uses only 1D dose-calculation formalism for permanent implant dosimetry. The point-dose calculation, dose summation, isodose representation, and dose–volume histogram quality assurance tests were performed in this study. The point-source dose-calculation tests were performed for all the available sources in the literature. The others tests were performed for the I-125 BARC Ocu-Prosta seeds. The TPS-calculated doses were validated using manual calculation. Results and Discussion In point-source calculation test, the TPS-calculated point-dose values are within ±2% agreement with manually calculated dose for all the seeds studied. The agreement between the TPS and manually calculated dose is 0.5% for the dose summation test. The isodose line pass through the grid points at an equal distance was verified visually on the computer screen for seed used clinically. In dose–volume histogram test, the TPS-determined volume was compared with the real volume. Conclusion Misinterpretation of the TPS test and/or misunderstanding of the TG-43 dose-calculation formalism may cause large errors. It is very important to validate the TPS using literature provided dosimetric data. The dosimetric data of BARC 125I Ocu-Prosta Seed are validated with other AAPM TG-43-recommended seeds. The dose calculation of Best® NOMOS permanent implant TPS is accurate for all permanent implant seeds studied.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta
TECHNICAL NOTES Top

A feasibility study of stereotactic radiosurgery/stereotactic body radiotherapy/stereotactic ablative radiotherapy practice using tomoedge in helical tomotherapy for lung, liver, and spine targets p. 204
N V. N. Madhusudhana Sresty, A Krishnam Raju, G Deleep Kumar, S Rohit, B Nagarjuna Reddy, VC Sahithya, B Devender Reddy, Yakub Mohd, Tasneem Rushdi, Harjoth Bajwa, S Aparna
DOI:10.4103/jmp.JMP_97_20  
The primary purpose of the study is to evaluate the implementation of Helical TomoTherapy (HT) for eligible stereotactic radiosurgery/stereotactic body radiotherapy/stereotactic ablative radiotherapy (SRS/SBRT/SABR) cases using TomoEDGE option. The study focuses on reduction of treatment time without compromise in plan quality using TomoEDGE. It is a mode in HT that uses a dynamic opening of the jaws during treatment delivery to reduce the dose penumbra which otherwise is not possible with fixed jaws option. Eligible SRS/SBRT/SABR cases of lung, liver, and spine were used in this study. All planning parameters such as dose prescription to target and critical organs, pitch, and modulation factor were same in all the plans of the same patient with modifications in the field width and jaw mode. First set of plans with 2.5 cm width and second set of plans with 5 cm width were done in dynamic TomoEDGE mode. Third set of plans created with 5 cm width fixed jaw mode and fourth set of plans with 2.5 cm fixed jaw mode for comparison purpose were done. Our observations achieved that a significant milestone with reduction of up to 34.3% in treatment time of liver cases, 35.2% in lung cases, and 28.7% in spine cases was observed using dynamic TomoEDGE mode with 5 cm width, while no significant variation in the planning results compared with plans using 2.5 cm dynamic TomoEDGE option. TomoEDGE is an efficient and useful mode in TomoTherapy to reduce the treatment time with bigger field width in SRS/SBRT/SABR cases without significant changes in the plan quality.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Importance of beam-matching between truebeam stx and novalis tx in pre-treatment quality assurance using portal dosimetry p. 211
José Alejandro Rojas-López, Daniel Venencia
DOI:10.4103/jmp.JMP_12_21  
Flexibility and efficiency in a radiotherapy department with different linear accelerators (linacs) can be improved if they are dosimetrically equivalent, and there is no need of plan or patient-specific quality assurance (PSQA) modification. From 2012 to 2017, our institution purchased three Novalis Tx and one TrueBeam STx beam-matched accelerators with the same high-resolution multileaf collimator (MLC). They are matched taking as reference dosimetric data from Novalis Tx SN-5479. We showed the importance of beam-matched dosimetric units by the use of electronic portal image device (EPID) and Delta4 PSQA. It was able to treat patients on a different machine than the machine used for PSQA. Depth dose, beam profiles, output factors, dosimetric leaf gap, and MLC transmission were compared for all energies and linacs. PSQA in all linacs for 30 volumetric-modulated arc therapy plans was also compared. Prostate, breast, and head-and-neck cases were selected to consider low, middle, and high plan complexity, respectively. The comparisons were evaluated using EPID and Delta4 phantom. Dosimetric differences between the three Novalis Tx and TrueBeam STx in all energies were lower than 1%. The only significant difference was observed in Novalis EPID in middle complexity when the criterion was tighter in distance. This result could be related with the nonsymmetric dose delivery of semi arcs. In all other cases, there were no differences in two different EPID evaluations. However, TrueBeam EPID values were slightly higher than Novalis EPID values. This could be associated with the high-resolution novel diode detector TrueBeam EPID. The dosimetric data indicated that the Novalis Tx and TrueBeam STx are equivalent. PSQA using EPID and Delta4 phantom showed that there are no dosimetric differences in any of the linacs. These results revealed the flexibility performance in PSQA by beam-matching.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta

Assessment of uncertainty depending on various conditions in modulation transfer function calculation using the edge method p. 221
Sho Maruyama
DOI:10.4103/jmp.JMP_36_21  
In medical X-ray imaging, to perform optimal operations, it is essential for the user to understand whether a required image quality level which depends on a diagnostic task can be achieved with the imaging system used. This study focuses on the effects of noise on the modulation transfer function (MTF) using the edge method, the most widely used to evaluate the task dependence property. The purpose is to verify the uncertainty of the MTF value at each spatial frequency and examine the conditions under which the accuracy is ensured. By using a Monte Carlo simulation, edge images with various contrast-to-noise ratio (CNR) are acquired. MTFs are then calculated with different edge spread function (ESF) lengths. The uncertainties for each spatial frequency are estimated based on the independent MTF calculations obtained from the five edge data. The uncertainty of the MTF is inversely proportional to the CNR. In the frequency range up to the Nyquist frequency, the uncertainty in five calculations is <0.01 when the CNR is more than 60. In addition, it is observed that the uncertainty increases as the ESF length increases. This relationship depends on the frequency range, but it is proportional to the 0.3–0.5 power of the ESF length. The results in which the uncertainty is most likely to be large in the MTF calculation are clearly shown. Therefore, it is expected to provide an important barometer and useful insights for a proper image quality measurement.
[ABSTRACT]  [HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta
BOOK REVIEW Top

Review of book entitled “shielding techniques for radiation oncology facilities, 3rd edition” p. 228
G Sahani
DOI:10.4103/jmp.JMP_96_21  
[HTML Full text]  [PDF]  [Mobile Full text]  [EPub]  [Sword Plugin for Repository]Beta
 
  Search this journal
    
  Advance Search
 
  Editorial Board 
  The Journal 
  The Association 
  Alerting 
  Feedback 
  Contact Us 

Submit Articles

Alerts