Clinical effectiveness of combined whole body hyperthermia and external beam radiation therapy (EBRT) versus EBRT alone in patients with painful bony metastases: A phase III clinical trial study

PURPOSE

To evaluate the response rate, pain relief duration, and time it took for pain to decline or resolve after radiation therapy (RT) with or without fever-range Whole Body Hyperthermia (WBH) in bony metastatic patients with mainly primary tumor of prostate and breast cancer leading to bone pain.

MATERIALS & METHODS

Bony metastatic patients with pain score ≥4 on the Brief Pain Inventory (BPI) underwent RT of 30 Gy in 10 fractions in combination with WBH with nursing care under medical supervision versus RT-alone. WBH application time was 3-4 h in three fractions with at least 48-h intervals. All patients were stratified primary site, breast or prostate cancer vs others, BPI score, and exclusion criteria. The primary endpoint was complete response (CR) (BPI equal to zero with no increase of analgesics) within two months of follow-up.

RESULTS

Based on this study, the RT-alone group showed the worst pain. The study was terminated after the enrollment of a total of 61 patients, 5 years after the first enrollment (April 2016 to February 2021). Finally, the CR rate in RT + WBH revealed the most significant difference with RT-alone, 47.4% versus 5.3% respectively within 2 months post-treatment (P-value <0.05). The time of complete pain relief was 10 days for RT + WBH, while the endpoint was not reached during the RT-alone arm. Pain progression or stable disease was observed in half of the patients in RT-alone group within 4 weeks after treatment. However, this score was near zero in RT + WBHT patients in two months post-treatment.

CONCLUSIONS

WBH plus RT showed significant increases in pain relief and shorter response time in comparison with RT-alone for patients with bone metastatic lesions.

Deep Radiomics Features of Median Nerves for Automated Diagnosis of Carpal Tunnel Syndrome With Ultrasound Images: A Multi-Center Study

OBJECTIVES

Ultrasound is widely used in diagnosing carpal tunnel syndrome (CTS). However, the limitations of ultrasound in CTS detection are the lack of objective measures in the detection of nerve abnormality and the operator-dependent nature of ultrasound imaging. Therefore, in this study, we developed and proposed externally validated artificial intelligence (AI) models based on deep-radiomics features.

METHODS

We have used 416 median nerves from 2 countries (Iran and Colombia) for the development (112 entrapped and 112 normal nerves from Iran) and validation (26 entrapped and 26 normal nerves from Iran, and 70 entrapped and 70 normal nerves from Columbia) of our models. Ultrasound images were fed to the SqueezNet architecture to extract deep-radiomics features. Then a ReliefF method was used to select the clinically significant features. The selected deep-radiomics features were fed to 9 common machine-learning algorithms to choose the best-performing classifier. The 2 best-performing AI models were then externally validated.

RESULTS

Our developed model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.910 (88.46% sensitivity, 88.46% specificity) and 0.908 (84.62% sensitivity, 88.46% specificity) with support vector machine and stochastic gradient descent (SGD), respectively using the internal validation dataset. Furthermore, both models consistently performed well in the external validation dataset, and achieved an AUC of 0.890 (85.71% sensitivity, 82.86% specificity) and 0.890 (84.29% sensitivity and 82.86% specificity), with SVM and SGD models, respectively.

CONCLUSION

Our proposed AI models fed with deep-radiomics features performed consistently with internal and external datasets. This justifies that our proposed system can be employed for clinical use in hospitals and polyclinics.

Examining the effect of Helicobacter pylori cagPAI variety on gene expression pattern related to gastric cancer

OBJECTIVES

We aimed to determine possible association between heterogeneity of Helicobacter pylori cytotoxin-associated gene pathogenicity island and gene expression profiles in patients with distinct histopathological changes.

METHODS

Gastric biopsies were obtained from seventy five patients. Microbiological and pathological examinations were done and intactness of Helicobacter pylori cagPAI was determined by PCR using 11 pairs of primers flanking cagζ-cagA regions and cagPAI empty site. Alterations at mRNA levels of eight genes were investigated by real-time PCR and their association with cagPAI intactness and histopathological changes examined statistically.

RESULTS

A larger proportion of cagPAI positive strains colonized patients with SAG (52.4%), followed by CG (33.3%), and IM (14.3%). Intact cagPAI was found in 87.5% of the strains obtained from patients with SAG, while significantly lower frequency was detected among those with CG (12.5%) and IM (0%). No significant difference was found among the studied histological groups and fold changes in gene expression of gastric biopsies of Helicobacter pylori infected patients with distinct cagPAI status. However, in each histological group, the strains with more complete gene cluster induced (ErbB2, CCNE1, CTNNB1, and MMP7 in SAG and IM groups) or reduced (TP53, in CG group) expression of the GC associated genes in relatively higher levels. APC, TP53 and E-cadherin were down-regulated in patients with SAG and IM compared with CG patients, irrespective to the status of cagPAI integrity.

CONCLUSIONS

Helicobacter pylori strains that carry more complete cagPAI segment could induce remarkably higher levels of mRNA changes of GC associated genes in all histopathological groups.

Diagnosis of Metastatic Lymph Nodes in Patients With Papillary Thyroid Cancer: A Comparative Multi-Center Study of Semantic Features and Deep Learning-Based Models

OBJECTIVES

Deep learning algorithms have shown potential in streamlining difficult clinical decisions. In the present study, we report the diagnostic profile of a deep learning model in differentiating malignant and benign lymph nodes in patients with papillary thyroid cancer.

METHODS

An in-house deep learning-based model called "ClymphNet" was developed and tested using two datasets containing ultrasound images of 195 malignant and 178 benign lymph nodes. An expert radiologist also viewed these ultrasound images and extracted qualitative imaging features used in routine clinical practice. These signs were used to train three different machine learning algorithms. Then the deep learning model was compared with the machine learning models on internal and external validation datasets containing 22 and 82 malignant and 20 and 76 benign lymph nodes, respectively.

RESULTS

Among the three machine learning algorithms, the support vector machine model (SVM) outperformed the best, reaching a sensitivity of 91.35%, specificity of 88.54%, accuracy of 90.00%, and an area under the curve (AUC) of 0.925 in all cohorts. The ClymphNet performed better than the SVM protocol in internal and external validation, achieving a sensitivity of 93.27%, specificity of 92.71%, and an accuracy of 93.00%, and an AUC of 0.948 in all cohorts.

CONCLUSION

A deep learning model trained with ultrasound images outperformed three conventional machine learning algorithms fed with qualitative imaging features interpreted by radiologists. Our study provides evidence regarding the utility of ClymphNet in the early and accurate differentiation of benign and malignant lymphadenopathy.

Tumor Microenvironment, Radiology, and Artificial Intelligence: Should We Consider Tumor Periphery?

OBJECTIVES

The tumor microenvironment (TME) consists of cellular and noncellular components which enable the tumor to interact with its surroundings and plays an important role in the tumor progression and how the immune system reacts to the malignancy. In the present study, we investigate the diagnostic potential of the TME in differentiating benign and malignant lesions using image quantification and machine learning.

METHODS

A total of 229 breast lesions and 220 cervical lymph nodes were included in the study. A group of expert radiologists first performed medical imaging and segmented the lesions, after which a rectangular mask was drawn, encompassing all of the contouring. The mask was extended in each axis up to 50%, and 29 radiomics features were extracted from each mask. Radiomics features that showed a significant difference in each contour were used to develop a support vector machine (SVM) classifier for benign and malignant lesions in breast and lymph node images separately.

RESULTS

Single radiomics features extracted from extended contours outperformed radiologists' contours in both breast and lymph node lesions. Furthermore, when fed into the SVM model, the extended models also outperformed the radiologist's contour, achieving an area under the receiver operating characteristic curve of 0.887 and 0.970 in differentiating breast and lymph node lesions, respectively.

CONCLUSIONS

Our results provide convincing evidence regarding the importance of the tumor periphery and TME in medical imaging diagnosis. We propose that the immediate tumor periphery should be considered for differentiating benign and malignant lesions in image quantification studies.

Assessing the Changes of Cortical Thickness in Alzheimer Disease With MRI Using Freesurfer Software

Introduction:

In this study, we intend to determine the correlation between the thickness of the cerebral cortex and the severity of the cognitive disorder in Alzheimer disease (AD).

Methods:

A total of 20 (14 women and 6 men) patients diagnosed with AD with a Mean age of 72.95 years, and 10 (7 women and 3 men) cognitively normal (CN) subjects with a Mean age of 70.50 years were included in the study. Of the AD patient and CN subjects, 70% were female, and 30% were male. All individuals underwent 1.5 T Magnetic resonance imaging (MRI). The MRI scanning protocol included 3D MPRAGE (3D-T1W) sequence. All images were analyzed using Freesurfer v5.3, and then the brain cortical thickness in 7 cortical areas (inferior temporal, middle temporal, superior temporal, parahippocampal, pars triangularis, rostral middle frontal, and superior frontal) was calculated.

Results:

The analysis of covariance (ANCOVA) was conducted to compare the mean thickness of each region between the patient and the control group. There was a significant difference in the mean cortical thickness in all regions. In all cases, the mean cortical thickness in CN subjects was greater than in AD patients. However, the mean thickness of pars triangularis left hand in CN subjects was not significantly greater than that in AD patients. The receiver operating characteristic system (ROC) was designed to evaluate the predictive power of the patients and the healthy people. We have selected a thousand cut-off points from 1.5 to 3.5 mm for cortical thickness. When the cut-off points were within 2.276878–2.299680 mm in the left hemisphere, Youden’s index was maximum. The sensitivity and specificity, in this case, were 80%. Also, when the cut-off points were within the range of 2.263278–2.282278 mm in the right hemisphere, the sensitivity and specificity were 90% and 80%, respectively.

Conclusion:

This study demonstrates the importance of quantifying the cortical thickness changes in the early diagnosis of AD. In addition, examining the pattern of changes and quantifying the reduction in the thickness of the cortex is a crucial tool for displaying the local and global atrophy of the brain. Also, this pattern can be used as an alternative marker for the diagnosis of dementia. Finally, to the best of our knowledge, our study is the first to report finding on the cortical thickness that would help the clinician have a better differential diagnosis. Also, this study has checked the possibility of early diagnosis of the disease.

Highlights

Plain Language Summary

The neurodegenerative disorder Alzheimer's disease (AD) is a fast-growing epidemic in aging populations worldwide. In 2050, one new case of AD is estimated to increase up to every 33 seconds. So the diagnosis of AD in the early stage considerably decreases the progress of dementia and helps identify a correct treatment approach. The cortical thickness measured by structural neuroimaging has received a significant surrogate biomarker that could provide powerful tools for the early diagnosis of AD. Since the sensitivity and specificity of MRI are higher, it offers essential advantages for identifying brain atrophy patterns. The manual cortical thickness measurement methods are time-consuming and require experienced anatomists compared with automated methods. In this regard, Freesurfer software, which is a freely available program and provides information for quantifying the functional and structural features of the brain, is used. The current study demonstrates examining the pattern of changes and quantifying the reduction in the thickness of the cortex. This can also be used as an alternative marker for the early diagnosis of dementia using cortical thickness measurment that would help the physicians.

Metabolite Alternations in the Dopamine Circuit Associated with Methamphetamine-Related Psychotic Symptoms: A Proton Magnetic Resonance Spectroscopy Study

Objective: Chronic METH use results in neurodegenerative alternations in the human brain. The present study aimed to assess the long-term METH impact on brain metabolite concentrations in cases meeting the DSM-5 criteria regarding METH use.

Method: We recruited 42 METH users meeting the DSM-5 criteria and 21 healthy controls. Psychotic signs were measured using the Positive and Negative Syndrome Scale (PANSS). Proton magnetic resonance spectroscopy (1HMRS) evaluating Myo-inositol (Ml), Choline (Cho), Glutamine plus Glutamate (Glx), N-acetyl aspartate (NAA), and Creatine (Cre) were obtained in the dopaminergic pathway (Frontal Cortex, Substantia nigra, Ventral Tegmental Area (VTA), Nucleus Accumbens (NAc), Hippocampus, Striatum,) the subjects. All participants collected urine specimens for 24 hours to measure presence of specific metabolites including METH metabolite level, 5-Hydroxy indoleacetic acid metabolite (for serotonin level monitoring), and metanephrine metabolite (for dopamine level monitoring).

Results: Dopamine and Serotonin increased in the METH group (P < 0.001). METH caused an increase in the Cre (P < 0.001) and a decline in the Glx (P < 0.001), NAA (P = 0.008), and MI (P < 0.001) metabolite concentrations of dopamine circuits in METH users in comparison with healthy subjects. We found no change in Cho metabolite concentration. Psychological data and the neurometabolite concentrations in the studied area of the brain were significantly correlated.

Conclusion: There is an association between METH use and active neurodegeneration in the dopamine circuit, and it causes serious mental illness. 1HMRS can detect patient’s deterioration and progression of disease as well as follow-up management in patients with METH use disorder.

Clinical Significance of Diffusion-weighted Magnetic Resonance Imaging on Treatment Efficacy in MS Patients With Acute Attacks

Introduction:

Despite various imaging methods, the accurate diagnosis of numerous neurodegenerative diseases remains controversial. Using advanced imaging techniques, like diffusion-weighted imaging, can help the early detection of Multiple Sclerosis (MS) and evaluation of the treatment efficacy in these patients.

Methods:

In total, 24 MS patients with acute attack and 30 healthy subjects were considered in our study. Region of Interest (ROI) was defined for acute and chronic plaques and Normal-Appearing White Matter (NAWM) in the patients’ group. In the normal group, ROI only was mapped in the white matter in the same regions of the patient. All MS patients were receiving Methylprednisolone for 3 to 5 days. The rate of clinical disability in these patients was also evaluated based on the Expanded Disability Status Scale (EDSS) index. Finally evaluate changes of ADC values of plaques and NAWM before and after treatment.

Results:

The Apparent Diffusion Coefficient (ADC) values of acute plaques, the ADC values of NAWM, the number of enhancement in T1w, and EDSS values suggested a significant difference after treatment compared to before treatment. However, the ADC values of chronic plaques revealed no significant difference after treatment. There was a significant positive correlation between the difference in EDSS values before and after treatment.

Conclusion:

The study results demonstrated that using diffusion technique and ADC values analysis is a proper non-invasive method for MS diagnosis and evaluating treatment efficacy in these patients.

Highlights

Plain Language Summary

Multiple Sclerosis (MS) is a common inflammatory disorder of the central nervous system that could result in physical and mental disabilities in patients. Disease progression usually manifests as a series of attacks. Although there is no proven cure for MS, different treatment strategies aim to modify the cause of the disease, manage its symptoms, and prevent and postpone disability. The most common therapy in acute attacks is using corticosteroid drugs. In addition to the treatment, evaluating the success rate of treatment was also challenging. Historically, clinical assessments method (e.g. EDSS) have been used as the baseline for measuring the therapy’s efficiency. Several supplementary methods, including imaging techniques, are introduced to address this issue. Conventional MRI imaging with injection has been widely accepted to assess the treatment. However, because of the modest sensitivity of conventional MRI to detect subtle pathological changes, there is a poor correlation between its findings and patients’ disability. This study moved from conventional MRI to advanced techniques, such as DWI and its quantitative index named ADC value. This technique can provide information about microstructural changes in MS patients. This method does not require injection, so there are no probable adverse effects and lower scan time. This study emphasizes changes in ADC value and EDSS before and after treatment with methylprednisolone. Our results suggested s that ADC values and EDSS after treatment are significantly different from their typical values. ADC values can be used as a biomarker to evaluate treatment efficiency, yet it is not objective enough to use it alone. So, the combination of DWI imaging with conventional methods might be beneficial in assessing treatment efficiency in MS patients.

A practical artificial intelligence system to diagnose COVID-19 using computed tomography: A multinational external validation study

Computed tomography has gained an important role in the early diagnosis of COVID-19 pneumonia. However, the ever-increasing number of patients has overwhelmed radiology departments and has caused a reduction in quality of services. Artificial intelligence (AI) systems are the remedy to the current situation. However, the lack of application in real-world conditions has limited their consideration in clinical settings. This study validated a clinical AI system, COVIDiag, to aid radiologists in accurate and rapid evaluation of COVID-19 cases. 50 COVID-19 and 50 non-COVID-19 pneumonia cases were included from each of five centers: Argentina, Turkey, Iran, Netherlands, and Italy. The Dutch database included only 50 COVID-19 cases. The performance parameters namely sensitivity, specificity, accuracy, and area under the ROC curve (AUC) were computed for each database using COVIDiag model. The most common pattern of involvement among COVID-19 cases in all databases were bilateral involvement of upper and lower lobes with ground-glass opacities. The best sensitivity of 92.0% was recorded for the Italian database. The system achieved an AUC of 0.983, 0.914, 0.910, and 0.882 for Argentina, Turkey, Iran, and Italy, respectively. The model obtained a sensitivity of 86.0% for the Dutch database. COVIDiag model could diagnose COVID-19 pneumonia in all of cohorts with AUC of 0.921 (sensitivity, specificity, and accuracy of 88.8%, 87.0%, and 88.0%, respectively). Our study confirmed the accuracy of our proposed AI model (COVIDiag) in the diagnosis of COVID-19 cases. Furthermore, the system demonstrated consistent optimal diagnostic performance on multinational databases, which is critical to determine the generalizability and objectivity of the proposed COVIDiag model. Our results are significant as they provide real-world evidence regarding the applicability of AI systems in clinical medicine.

Accurate automated diagnosis of carpal tunnel syndrome using radiomics features with ultrasound images: A comparison with radiologists' assessment

PURPOSE

Ultrasonography is the most common imaging modality used to diagnose carpal tunnel syndrome (CTS). Recently artificial intelligence algorithms have been used to diagnose musculoskeletal diseases accurately without human errors using medical images. In this work, a computer-aided diagnosis (CAD) system is developed using radiomics features extracted from median nerves (MN) to diagnose CTS accurately.

METHOD

This study is performed on 228 wrists from 65 patients and 57 controls, with an equal number of control and CTS wrists. Nerve conduction study (NCS) is considered as the gold standard in this study. Two radiologists used two guides to evaluate and categorize the pattern and echogenicity of MNs. Radiomics features are extracted from B-mode ultrasound images (Ultrasomics), and the robust features are fed into support vector machine classifier for automated classification. The diagnostic performances of two radiologists and the CAD system are evaluated using ROC analysis.

RESULTS

The agreement of two radiologists was excellent for both guide 1 and 2. The honey-comb pattern clearly appeared in control wrists (based on guide 1). In addition, CTS wrists indicated significantly lower number of fascicles in MNs (based on guide 2). The area under ROC curve (AUC) of the radiologist 1 and 2 are 0.658 and 0.667 based on guide 1 and 0.736 and 0.721 based on guide 2, respectively. The CAD system indicated higher performance than two radiologists with AUC of 0.926.

CONCLUSION

The proposed CAD system shows the benefit of using ultrasomics features and can assist radiologists to diagnose CTS accurately.

Multiparametric MRI for the Diagnosis of Tumor Type in Patients Suspicious of Inner Gland Prostate Cancer

PURPOSE

The current study aimed to evaluate multiparametric MRI for the diagnosis of type of tumor (benign ormalignant) in patients suspicious of inner gland prostate cancer.

MATERIALS AND METHODS

This cross-sectional study was conducted on 44 consecutive patients with a clinicalimpression of prostate cancer who were referred to the MRI department of Payambaran Hospital, Tehran, Iranfor confirmative diagnostic evaluation. Cases suspected of tumor relapse and those who previously underwenttreatment for prostate cancer were excluded. Multiparametric MRI was performed for every patient by using a 1.5Tesla device with an integrated endorectal and pelvic-phased array coil. All patients subsequently underwent MRItransrectalultrasound fusion biopsy. The diagnostic value of each sequence was then investigated individually andin combination with other techniques by comparing the results with histological findings from MRI-TRUS fusionbiopsy.

RESULTS

Among the techniques, T2-weighted imaging (T2W) had the highest sensitivity and specificity whiledynamic contrast enhanced (DCE) technique had the least. Diffusion-weighted imaging (DWI) and magnetic resonancespectroscopy (MRS) had a similar sensitivity and specificity and did not significantly differ from T2W.Adding functional techniques to T2W did not improve diagnostic indices compared to T2W alone. Quantitativeevaluation of apparent diffusion coefficient (ADC), DWI, and MRS showed that all techniques were able to differentiatebetween benign and malignant tumors. However, the quantitative combination of these sequences decreaseddiagnostic performance.

CONCLUSION

T2W is the best technique for the diagnosis of type of tumor in terms of benignancy or malignancyin patients suspicious of inner gland prostate cancer. Adding functional imaging measurements to T2W does notimprove its diagnostic value.

Evaluating the Origin of the Brain Metastatic Tumors by Using DWI Parameters

Background: Brain metastases are the most common tumors in the human central nervous system (CNS), with an occurrence 10 times higher than primary brain tumors in adults. A radiologist usually diagnoses these tumors. Typically, magnetic resonance imaging (MRI) has been used to evaluate the status and number of metastases, the design of surgical treatment or radiotherapy, and the response to treatment. This study aimed to consider the origin of metastatic tumors of the brain using diffusionweighted imaging sequence. Methods: In this study, 95 lesions observed in 51 patients with different types of brain metastasis who analyzed with standard brain MRI protocols such as T2-weighted fast spin-echo in sagittal, coronal and axial planes and T1-weighted spin-echo sequences before and after injection of contrast enhancement and diffusion-weighted imaging. The diffusion-weighted imaging included an echoplanar spin-echo sequence with two b values (0,1000 s/mm) and calculated apparent diffusion coefficient (ADC) maps. We measured the ADC-value on normalized ADC maps and compared them with different methods. ANOVA was used to compare ADC among all groups as well as T-test for every two groups. Results: The results showed that patients with lung cancer (squamous cell carcinoma, SCC) had the lowest mean ADC (658.70*10-3 mm2 /s) and breast cancer patients with the highest mean ADC(935.52*10-3 mm2 /s). This study demonstrated that most Brain metastases had low and intermediate ADC values. The analysis showed no significant difference among all groups. However, ADC values in breast cancer and kidney and lung (adenocarcinoma) were statistically higher in comparison to other groups. There were no critical discrepancies between ADC values in brain metastases from Breast cancer and lung cancer (adenocarcinoma) and kidney. Conclusion: It seems that evaluating the origin of the brain metastatic tumors by using diffusion imaging (DWI) parameters could be helpful to prevent invasive methods like biopsies in some situations. Although it needs more studies to achieve this purpose.

Diagnostic Value of Diffusion Weighted Magnetic Resonance Imaging in Evaluation of Metastatic Neck Lymph Nodes in Head and Neck Cancer: A Sample of Iranian Patient

Objective:

To evaluate the diagnostic value of DWI in assessment of metastatic neck lymph node in a sample of Iranian patients with Head and Neck cancer.

Methods:

25 patients with 80 neck lymph nodes were analyzed using 1.5 T MRI. DWI was performed with b values of 0 and 1,000 s/mm². Short axis diameter and ADC values (min, max and mean) were calculated for metastatic and non-metastatic neck LNs and results were compared with histopathological findings. The optimal ADC thresholds were analyzed using receiver coefficient characteristic (ROC) curves for discriminating between metastatic and benign neck lymph nodes.

Result:

Histopathological findings revealed that there are 45% (n=36) metastatic and 55% (n=44) non-metastatic neck LNs respectively. There was no statistically significant difference in short axis diameter between the two groups (p = 0.346). However, The ADC values of metastatic neck LNs were significantly lower than those of non-metastatic neck LNs (p < 0.001); 0.90 ± 0.10 × 10^-3 mm²/s vs 1.06 ± 0.12 × 10^-3 mm²/s ( ADC mean ), 0.78 ± 0.08 × 10^-3 mm²/s vs 0.92 ± 0.20× 10^-3 mm²/s ( ADC min ) and 1.02 ± 0.12 × 10^-3 mm²/s vs 1.24 ± 0.15 × 10^-3 mm²/s (ADC max ). The optimal mean ADC threshold value was equal to 0.996 × 10^-3 mm²/s for differentiating malignant from benign lymph nodes with sensitivity, specificity and accuracy of 80.56 %, 77.27 % and 71.59 % respectively.

Conclusion:

MR diffusion imaging and ADC values as a non-invasive technique can assess metastatic neck LNs in head and neck cancer with higher sensitivity, specificity and accuracy.

The Role of Single Voxel MR Spectroscopy, T2 Relaxation Time and Apparent Diffusion Coefficient in Determining the Cellularity of Brain Tumors by MATLAB Software

Introduction: Brain tumors if timely diagnosed are sure to be treated through shorter processes. MRI amongst others is of Para clinical methods greatly effective in diagnosis phase. Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps provide some information that could reflect tissue cellularity. Neurosurgeons, in particular to detect the tumor cellularity, must send the specimens taken through biopsy to the pathology unit. This study is aimed at determining the tumor cellularity in brain. Materials and Methods: In this cross-sectional study, 32 patients (18 males and 14 females of the range 18 – 77 y/o) between April 2014 and February 2016 who were referred to the neurosurgery department of Shohada-E Tajrish Hospital of Tehran participated. Imaging was made using single voxel MR Spectroscopy, ADC and T2W Multi Echo Pulse Sequence in addition to routine pulse sequences and the images were analyzed using MATLAB software to determine the cellularity of brain tumors in comparison to the biopsy. Results: findings showed that by decreasing T2 relaxation time, the amount of ADC, N-Acetyl Aspartate (NAA) and also, increase Choline metabolite, lead to registering tumors in the lower class on the designed table and these tumors have a higher degree of consistency and cellularity. T2 Relaxation time, the tumors will stand at higher class on the designed table. Also the results indicated that 85% diagnostic weight of T2 relaxation time and 83% diagnostic weight of ADC compared with biopsy could reveal the brain tumor cellularity (P>0.05). Conclusion: some cellular metabolite changes such as NAA and Choline, ADC value and T2 relaxation time feature could effectively be used to distinguish and illustrate the degree of cellularity of brain tumors especially Intra-axial brain tumors (with about 85%. vs. biopsy). We recommend to more data should be used to increase the accuracy percentage of this technique.

Preoperative Evaluation of Tumor Adhesion to Adjacent Brain Tissue in Patients with Meningioma with BSMI Method and Its Comparison with the Width of Edema Around Tumor

Background

This study aims to investigate the ability of BSMI, to preoperative evaluation of tumor adhesion to adjacent brain tissue in patients with meningioma and comparing this method to the width of edema around tumor, using surgery findings as the reference standard.

Methods

Thirty patients with meningioma brain tumor who underwent surgery at Loghman hospital were selected for the study between November 2016 and January 2018. The level of edema according to the classification of Ide et al., (u1995) was compared with the surgical findings with blinded results, and neurosurgeons made a qualitative assessment of tumor adhesion at the time of resection. The ability of BSMI and level of edema to predict the surgical assessment of adhesion was tested using the Fisher Exact Test.

Results

BSMI method was conducted on patients with meningioma brain tumor, which judged 22 (73.3%) patients as adhesion (+) and 8 (26.66%) patients as adhesion (-). In this case, there was a significant relationship between BSMI judgment and surgical findings (p-value<0.0001). The sensitivity, specificity, precision and accuracy was high, at 91.30%, 85.71%, 95.45% and 90%, respectively. Using T2-Weighted SPACE sequence, of the 30 patients, 13 (43.3%) were judged as adhesion (+) and 17 (56.7%) as adhesion (-) from edema, whereas surgical findings evaluated 23 (76.7%) as adhesion (+) and 7 (23.3%) as adhesion (-).The sensitivity was moderate but the specificity was high, at 52.17% and 85.71%, respectively. Other criteria such as precision and accuracy were 62.31% and 60%, respectively.

Conclusions

BSMI evaluated adhesion of the tumor to the adjacent brain tissue with high-accuracy prior to surgery. This method was more effective than Edema method in evaluating adhesion between meningioma and the brain.

Comparison Between Three-Dimensional Diffusion-Weighted PSIF Technique and Routine Imaging Sequences in Evaluation of Peripheral Nerves in Healthy People

Introduction:

The present study aims to evaluate the Three-Dimensional Diffusion-Weighted reversed fast imaging with steady state free precession (3D DW-PSIF) sequence with respect to imaging of the peripheral nerves; the tibial, medial, and lateral plantar nerves in the lower extremity, ulnar and median nerve in the upper extremity, sciatic nerve, brachial plexus, and lumbosacral plexus, and also to compare its usefulness with the current two-dimensional sequences on a 1.5 T MR scanner.

Methods:

A total of 25 healthy subjects underwent MR imaging of peripheral nerves, 5 subjects in each area. In each imaging sequence, including T2W SPAIR and 3D DW-PSIF, images were evaluated for ability to identify the nerves in the related area using a 3-score scale (0–2). Then, by summing up the conspicuity scores, a total certainty score was recorded for each sequence.

Results:

With combining the results of all studies, the conspicuity mean (SD) score was 1.57(0.67) on the 3D DW-PSIF images, and 0.74(0.76) on the T2-weighted images (P<0.001). Regarding the lumbosacral plexus, the corresponding certainty mean (SD) scores were 1.80(0.40) and 1.07(0.74) (P<0.001) and with regard to the brachial plexus, they were 1.23(0.83) and 0.75(0.84), (P<0.001). Regarding the ankle/hind foot they were 1.87(0.35) and 0.40(0.50) (P<0.001) and in the wrist/proximal hand, 1.70(0.48) and 0.50(0.52) (P<0.001). Regarding the sciatic nerve, they were 1.80(0.44) and 0.20(0.44) (P=0.003).

Conclusion:

3D DW PSIF provides better manifestation of nerves compared to routine imaging sequences particularly fat saturated T2W images. This novel imaging technique can be used in MR neurography examination protocol for exact localization of the nerve and evaluation of the nerve pathology.

The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques

BACKGROUND AND OBJECTIVE

Magnetic resonance imaging (MRI) is the most sensitive technique to detect multiple sclerosis (MS) plaques in central nervous system. In some cases, the patients who were suspected to MS, Whereas MRI images are normal, but whether patients don't have MS plaques or MRI images are not enough optimized enough in order to show MS plaques? The aim of the current study is evaluating the efficiency of different MRI sequences in order to better detection of MS plaques.

MATERIALS AND METHODS

In this cross-sectional study which was performed at Shohada-E Tajrish in Tehran - Iran hospital between October, 2011 to April, 2012, included 20 patients who suspected to MS disease were selected by the method of random sampling and underwent routine brain Pulse sequences (Axial T2w, Axial T1w, Coronal T2w, Sagittal T1w, Axial FLAIR) by Siemens, Avanto, 1.5 Tesla system. If any lesion which is suspected to the MS disease was observed, additional sequences such as: Sagittal FLAIR Fat Sat, Sagittal PDw-fat Sat, Sagittal PDw-water sat was also performed.

RESULTS

This study was performed in about 52 lesions and the results in more than 19 lesions showed that, for the Subcortical and Infratentorial areas, PDWw sequence with fat suppression is the best choice, And in nearly 33 plaques located in Periventricular area, FLAIR Fat Sat was the most effective sequence than both PDw fat and water suppression pulse sequences.

CONCLUSION

Although large plaques may visible in all images, but important problem in patients with suspected MS is screening the tiny MS plaques. This study showed that for revealing the MS plaques located in the Subcortical and Infratentorial areas, PDw-fat sat is the most effective sequence, and for MS plaques in the periventricular area, FLAIR fat Sat is the best choice.

Methoxyamine Enhances 5-Fluorouracil-Induced Radiosensitization in Colon Cancer Cell Line HT29

Objective

This study intended to observe the effects of methoxyamine (Mx) on cytotoxic effects and DNA damage caused by 5-Fluorouracil (5-FU) in combination with gamma radiation in a human colon cancer cell line, HT29.

Materials and Methods

In this experimental study, HT29 cells were cultured as a monolayer and treated with different concentrations of 5-FU along with 1 mM Mx for 24 hours. Next, the cells were irradiated with 2 Gy gamma radiation. After the treatments, we assessed for DNA damage, cytotoxicity, and viability by alkaline comet, clonogenic survival, and trypan blue dye exclusion assays.

Results

Cytotoxicity and DNA damage increased with increasing 5-FU concentration. The 1 mM Mx concentration had no significant effect on cytotoxicity and DNA damage from 5-FU; however, it increased the cytotoxic and genotoxic effects of different concentrations of 5-FU when used in combination with 2 Gy gamma radiation.

Conclusion

Mx combined with 5-FU enhanced the radiosensitivity of colon cancer cells.

Diagnostic Efficacy of Coronary Artery Three-Dimensional Steady-State Free Precession Magnetic Resonance Angiography in Comparison with Invasive Coronary Angiography for Detecting Coronary Artery Disease

PURPOSE

To assess the diagnostic value of three-dimensional steady-state free precession magnetic resonance angiography (3D-SSFP MRA) for detecting coronary artery disease (CAD).

MATERIALS AND METHODS

Patients suspected of CAD based on clinical evaluation, underwent invasive coronary angiography (CAG) and Cardiac MRA (CMRA). Collected data in favor of any CAD findings in CMRA were compared to CAG results as the standard diagnostic method in CAD detection. Analysis was performed on per-patient, per-vessel and per-segment bases.

RESULTS

A total of 30 patients (mean age: 43 ± 10 years, 19 men) were enrolled for analysis. On per-patient analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under receiver operator characteristic (ROC) curve of CMRA for detection of coronary artery stenosis were 100% (CI95%: 75% - 100%), 50% (CI95%: 18% - 81%), 73.33% (CI95%: 46% - 90%), 100% (CI95%: 47% - 100%) and 0.827, respectively. On per-vessel analysis, CMRA had a sensitivity of 89.29% (CI95%: 71%-97%), specificity of 80.56% (CI95%: 63% - 91%), PPV of 78.13% (CI95%: 60% - 90%), NPV of 90.63% (CI95%: 74% - 98%) and area under ROC curve of 0.845. On per-segment analysis, sensitivity, specificity, PPV and NPV of CMRA for segmental stenosis detection were 77.78% (CI95%: 60% - 89%), 87% (CI95%: 81% - 92%), 62% (CI95%: 46% - 76%), and 93.89% (CI95%:  88% - 97%), respectively. Area under ROC curve was 0.835 on per-segment analysis.

CONCLUSION

3D SSFP CMRA provides a promising non-invasive diagnostic tool for assessing coronary artery disease.

Diagnostic Value of Diffusion Weighted Magnetic Resonance Imaging in Evaluation of Metastatic Axillary Lymph Nodes in a Sample of Iranian Women with Breast Cancer

Objective:

To evaluate the diagnostic value of diffusion weighted magnetic resonance imaging (DW-MRI) in assessment of metastases in axillary lymph nodes (ALNs) in a sample of Iranian women with breast cancer.

Methods:

A total of 50 axillary lymph nodes from 30 female patients with histologically verified breast cancer were assessed by 1.5 T MRI. DWI was implemented at b-values of 50, 400 and 800 s/mm². Short axis diameter, presence of fatty hilum and apparent diffusion coefficient (ADC) values (min, max and mean) of metastatic and non-metastatic ALNs was compared. Cutoff ADC values to discriminate between benign and malignant axillary lymph nodes were analyzed with receiver coefficient characteristic (ROC) curves.

Result:

The final histopathological examination revealed 46% (n=23) metastatic and 54% (n=27) non-metastatic ALNs. There was no statistically significant difference in short axis diameter between the two groups (p = 0.537). However there was significantly correlation between loss of fatty hilum and presence of metastases (p < 0.001) and ADC values (0.255 ± 0.19×10^-3 mm²/s vs 0.616 ±0.3×10^-3 mm²/s (ADC min), 1.088 ± 0.22×10^-3 mm²/s vs 1.497 ± 0.24×10^-3 mm²/s (ADC max) and 0.824 ± 0.103 ×10^-3 mm²/s vs 1.098 ± 0.23 ×10^-3 mm²/s (ADC mean)) of metastatic ALNs were significantly lower than those of non-metastatic ALNs (p < 0.001). The optimal mean ADC cut-off value for differentiation between metastatic and non-metastatic ALNs was 0.904×10^-3 mm²/s which had a higher specificity (88.9%) and accuracy (91.8%) as compared with ADC min and ADC max.

Conclusion:

DWI-MRI and ADC values are promising imaging methods which can assess metastatic ALNs in breast cancer with high sensitivity, specificity and accuracy.

Assessment of the diagnostic accuracy of double inversion recovery sequence compared with FLAIR and T2W_TSE in detection of cerebral multiple sclerosis lesions

BACKGROUND

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. MRI has an important role in early diagnosis of MS within diagnostic criteria.

AIM

To determine the diagnostic value of the double inversion recovery (DIR) sequence in detection of brain MS lesions.

METHODS

In this cross-sectional study, 55 patients were admitted to the MRI department in Vali-E-Asr Hospital in Qaemshahr, Iran, from May 2016 to February 2016. Imaging was performed on a 1.5T Philips MR system using DIR, fluid attenuated inversion recovery (FLAIR), and T2-weighted turbo spin echo (T2W_TSE) sequences with the same parameters, including field of view (FOV), matrix, slice thickness, voxel size, and number of signal averaging (NSA). The DIR sequence has two different time inversions (TI₁=3400, TI₂=325ms): suppressing cerebrospinal fluid (CSF) and white matter signal. Data analysis was performed using the SPSS version 20, and p-value was gained from the patient-wise analysis by Wilcoxon analysis and paired samples t-test for matched pairs.

RESULTS

More lesions in number and size were depicted on the DIR sequence compared with FLAIR (p=0.000 with a relative ratio of 6) and T2W_TSE (p=0.000 with a relative ratio of 10). DIR demonstrated significantly more intracortical lesions compared with FLAIR (p=0.000 with a relative ratio of 2.53) and T2W_TSE (p=0.000 and relative ratio of 8.87). There was significantly higher contrast ratio between the white matter lesions and the normal appearing white matter (NAWM) in all anatomical regions especially in deep white matter (p=0.001).

CONCLUSION

An increasing total number of MS lesions can be detected by DIR sequence; thus, we recommend adding DIR sequence in routine MR protocols for MS patients.

Diffusion Tensor Imaging for Glioma Grading: Analysis of Fiber Density Index

Introduction:

The most common primary tumors of brain are gliomas and tumor grading is essential for designing proper treatment strategies. The gold standard choice to determine grade of glial tumor is biopsy which is an invasive method. The purpose of this study was to investigate the role of fiber density index (FDi) by means of diffusion tensor imaging (DTI) (as a noninvasive method) in glial tumor grading.

Methods:

A group of 20 patients with histologically confirmed diagnosis of gliomas were evaluated in this study. We used a 1.5 Tesla MR system (AVANTO; Siemens, Germany) with a standard head coil for scanning. Multidirectional diffusion weighted imaging (measured in 12 noncollinear directions), and T1 weighted nonenhanced were performed for all patients. We defined two regions of interest (ROIs); 1) White matter fibers near the tumor and 2) Similar fibers in the contralateral hemisphere.

Results:

FDi of the low-grade gliomas was higher than those of high-grade gliomas, which was significant (P=0.017). FDi ratio (ratio of fiber density in vicinity of the tumor to homologous fiber tracts in the contralateral hemisphere) is higher in low-grade than high-grade tumors, (P=0.05). In addition, we performed ROC (receiver operating characteristic) curve and the area under curve (AUC) was 0.813(P=0.013).

Conclusion:

Our findings prove significant difference in FDi near by low-grade and high-grade gliomas. Therefore, FDi values and ratios are helpful in glial tumor grading.

Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software

Introduction

Timely diagnosis of brain tumors could considerably affect the process of patient treatment. To do so, para-clinical methods, particularly MRI, cannot be ignored. MRI has so far answered significant questions regarding tumor characteristics, as well as helping neurosurgeons. In order to detect the tumor cellularity, neuro-surgeons currently have to sample specimens by biopsy and then send them to the pathology unit. The aim of this study is to determine the tumor cellularity in the brain.

Methods

In this cross-sectional study, 32 patients (18 males and 14 females from 18–77 y/o) were admitted to the neurosurgery department of Shohada-E Tajrish Hospital in Tehran, Iran from April 2012 to February 2014. In addition to routine pulse sequences, T2W Multi echo pulse sequences were taken and the images were analyzed using the MATLAB software to determine the brain tumor cellularity, compared with the biopsy

Results

These findings illustrate the need for more T2 relaxation time decreases, the higher classes of tumors will stand out in the designed table. In this study, the results show T2 relaxation time with a 85% diagnostic weight, compared with the biopsy, to determine the brain tumor cellularity (p<0.05).

Conclusion

Our results indicate that the T2 relaxation time feature is the best method to distinguish and present the degree of intra-axial brain tumors cellularity (85% accuracy compared to biopsy). The use of more data is recommended in order to increase the percent accuracy of this techniques.

Comparative Investigation of Single Voxel Magnetic Resonance Spectroscopy and Dynamic Contrast Enhancement MR Imaging in Differentiation of Benign and Malignant Breast Lesions in a Sample of Iranian Women

PURPOSE

To make a comparison of single voxel magnetic resonance spectroscopy (SV-MRS) and dynamic contrast enhancement (DCE) MRI for differentiation of benign and malignant breast lesions in a sample of Iranian women.

MATERIALS AND METHODS

A total of 30 women with abnormal breast lesions detected in mammography, ultrasound, or clinical breast exam were examined with DCE and SV-MRS. tCho (total choline) resonance in MRS spectra was qualitatively evaluated and detection of a visible tCho peak at 3.2 ppm was defined as a positive finding for malignancy. Different types of DCE curves were persistent (type 1), plateau (type 2), and washout (type 3). At first, lesions were classified according to choline findings and types of DCE curve, finally being compared to pathological results as the standard reference.

RESULTS

this study included 19 patients with malignant lesions and 11 patients with benign ones. While 63.6 % of benign lesions (7 of 11) showed type 1 DCE curves and 36.4% (4 of 11) showed type 2, 57.9% (11of 19) of malignant lesions were type 3 and 42.1% (8 of 19) type 2. Choline peaks were detected in 18 of 19 malignant lesions and in 3 of 11 benign counterparts. 1 malignant and 8 benign cases did not show any visible resonance at 3.2 ppm so SV-MRS featured 94.7% sensitivity, 72.7 % specificity and 86.7% accuracy.

CONCLUSIONS

The present findings indicate that a combined approach using MRS and DCE MRI can improve the specificity of MRI for differentiation of benign and malignant breast lesions.

Assessment of cerebral venous sinus thrombosis using T2 (*)-weighted gradient echo magnetic resonance imaging sequences

BACKGROUND

The purpose of this study is to demonstrate the advantages of gradient echo (GRE) sequences in the detection and characterization of cerebral venous sinus thrombosis compared to conventional magnetic resonance sequences.

METHODS

A total of 17 patients with cerebral venous thrombosis (CVT) were evaluated using different magnetic resonance imaging (MRI) sequences. The MRI sequences included T1-weighted spin echo (SE) imaging, T(*) 2-weighted turbo SE (TSE), fluid attenuated inversion recovery (FLAIR), T(*) 2-weighted conventional GRE, and diffusion weighted imaging (DWI). MR venography (MRV) images were obtained as the golden standard.

RESULTS

Venous sinus thrombosis was best detectable in T(*) 2-weighted conventional GRE sequences in all patients except in one case. Venous thrombosis was undetectable in DWI. T(*) 2-weighted GRE sequences were superior to T(*) 2-weighted TSE, T1-weighted SE, and FLAIR. Enhanced MRV was successful in displaying the location of thrombosis.

CONCLUSION

T(*) 2-weighted conventional GRE sequences are probably the best method for the assessment of cerebral venous sinus thrombosis. The mentioned method is non-invasive; therefore, it can be employed in the clinical evaluation of cerebral venous sinus thrombosis.

Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Staging of Bladder Cancer

INTRODUCTION

Dynamic Contrast Enhanced (DCE)-Magnetic Resonance Imaging (MRI) is a useful technique in which rapid enhancement of tumour by uptake of the contrast agent compared to bladder wall.

AIM

To evaluate the accuracy of dynamic gadolinium-enhanced MRI in staging of bladder cancer through differentiating superficial tumours from invasive tumours and organ-confined tumours from non-organ-confined tumours. In addition, the benefits of DCE-MRI in diagnosis of tumour progression steps were investigated.

MATERIALS AND METHODS

This was a quasi-experimental study in which 45 patients (95.55% men and 4.45% women) were enrolled. Patients with confirmed transitional cell carcinoma by histopathology findings were imaged using 1.5 Tesla MRI systems. Pathology results were considered as the standard reference. Tumour stage was determined by imaging findings and compared with pathologic findings after radical cystectomy. Data were analysed by SPSS version 16 and the level of significance in all tests was considered p<0.001.

RESULTS

The most common stage that was seen in pathology and MRI findings was T3b. Kappa agreement coefficient between MRI and pathology was 0.7 (p<0.001). The accuracy of MRI in differentiating superficial tumours (≤T1) from invasive tumours (≥ T2a), and organ-confined tumours (≤T2b) from non-organ-confined tumours (≥T3b) was 0.97 and 0.84, respectively. The overall accuracy of MRI was 0.77 (p<0.001). Totally, 10 cases of disagreement between MRI and pathological staging were found, eight (80%) of which were overestimated and two cases (20%) underestimated. MRI detection rate was 0% in stage Ta, 100% in stage T1, 66.7% in stage T2, 86.7% in stage T3, and 100% in stage T4. The sensitivity and specificity of MRI in differentiating superficial tumours from invasive tumours were 0.97 and 1, respectively, and in differentiating organ-confined tumours from non-organ-confined tumours were 0.94 and 0.77, respectively. The Spearman's correlation coefficient between the signal enhancement slope of time-intensity curves and tumour stages was 0.88 (p<0.001).

CONCLUSION

Gadolinium-enhanced MRI is an appropriate and useful modality with a high accuracy in determining the stage of the bladder cancer. In addition, this method shows extension and progression of tumour and tumour invasion depth.

Preoperative Grading of Astrocytic Supratentorial Brain Tumors with Diffusion-Weighted Magnetic Resonance Imaging and Apparent Diffusion Coefficient

Background

Diffusion-weighted imaging (DWI) is a form of magnetic resonance imaging (MRI) based on measuring the random Brownian motion of water molecules within the biological tissues and is particularly useful in tumor characterization.

Objectives

The purpose of this study was to evaluate the diagnostic value of DW MRI and the apparent diffusion coefficient (ADC) for preoperative grading of astrocytic supratentorial brain tumors.

Patients and Methods

Twenty-three patients (14 females, 9 males, mean age 43 years) with astrocytic supratentorial brain tumors underwent preoperative conventional MR imaging and DW MRI. The minimum, maximum and mean ADC values and the minimum, maximum and mean DWI signal intensities of each tumor were taken by placing several regions of interest in the tumor on DWI images and ADC maps. To assess the relationship between these values and the tumor grade, we used the Mann-Whitney U test and the Spearman correlation. Receiver operating characteristic (ROC) analysis was used to determine the cutoff value of the minimum, maximum and mean ADC values and the minimum, maximum and mean DWI signal intensities that had the best composition of sensitivity and specificity for differentiating low-grade and high-grade astrocytic brain tumors.

Results

According to the pathology reports, 10 patients had low-grade astrocytomas (grades I, II) and 13 patients had high-grade astrocytomas (grades III, IV). The minimum ADC value showed a significantly inverse correlation with astrocytic tumor grade (P = 0.006). The correlation between the maximum ADC value and the maximum DWI signal intensity with tumor grade was direct (P = 0.013, P = 0.035). According to the ROC analysis, the cutoff values of 0.843 × 10^-3 mm²/s, 2.117 × 10^-3 mm²/s and 165.2 for the minimum ADC, maximum ADC and maximum DWI respectively, obtained the best combination of sensitivity and specificity for distinguishing low-grade and high-grade astrocytomas.

Conclusion

Measuring minimum ADC, maximum ADC and maximum DWI signal intensity can provide valuable information for grading of astrocytic supratentorial brain tumors before surgery.

Effects of resveratrol and methoxyamine on the radiosensitivity of iododeoxyuridine in U87MG glioblastoma cell line

The purpose of this study was to evaluate the combination effect of resveratrol and methoxyamine on radiosensitivity of iododeoxyuridine in spheroid culture of U87MG glioblastoma cell line using colony formation and alkaline comet assays. Spheroids on day-20 with 350 µm diameters were treated with 20 µM resveratrol and/or 6 mM methoxyamine and/or 1 µM iododeoxyuridine for one volume doubling time (67 h), and then irradiated with 2 Gy gamma-radiation ((60)Co) in different groups. After treatment, viability of the cells, colony forming ability and DNA damages were obtained by blue dye exclusion, colony formation and alkaline comet assay, respectively. Our results showed that methoxyamine and resveratrol could significantly reduce colony number and induce the DNA damages of glioblastoma spheroid cells treated with iododeoxyuridine in combination with gamma-rays. Therefore, methoxyamine as base excision repair inhibitor and resveratrol as hypoxia inducible factor 1-alpha inhibitor in combination with iododeoxyuridine as radiosensitizer enhanced the radiosensitization of glioblastoma spheroid cells.

Quantification of diagnostic biomarkers to detect multiple sclerosis lesions employing (1)H-MRSI at 3T

Proton magnetic resonance spectroscopic imaging ((1)H-MRSI) enables the quantification of metabolite concentration ratios in the brain. The major purpose of the current work is to characterize NAA/Cho, NAA/Cr and Myo/Cr in multiple sclerosis (MS) patients, and to estimate their reproducibility in healthy controls. Twelve MS patients and five healthy volunteers were imaged using (1)H-MRSI at 3T. Eddy current correction was performed using a single-voxel non-water suppressed acquisition on an external water phantom. Time-domain quantification was carried out using subtract-QUEST technique, and based on an optimal simulated metabolite database. Reproducibility was evaluated on the same quantified ratios in five normal subjects. An optimal database was created for the quantification of the MRSI data, consisting of choline (Cho), creatine (Cr), N-acetyl aspartate (NAA), lactate (Lac), lipids, myo-inositol (Myo) and glutamine + glutamate (Glx). Decreasing of NAA/Cr and NAA/Cho ratios, as well as an increase in Myo/Cr ratio were observed for MS patients in comparison with control group. Reproducibility of NAA/Cr, NAA/Cho and Myo/Cr in control group was 0.98, 0.87 and 0.64, respectively, expressed as the squared correlation coefficient R (2) between duplicate experiments. We showed that MRSI alongside the time-domain quantification of spectral ratios offers a sensitive and reproducible framework to differentiate MS patients from normals.

ADC values in diffusion-weighted MRI and their relationship with age, gender and BMI in healthy people's pancreases

OBJECTIVE

The aim of this study is to use diffusion-weighted MRI to assess the apparent diffusion coefficient (ADC) values in head, body and tail sections of the pancreas in healthy subjects and the relationships between these values and age, gender and body mass index (BMI) of these cases.

METHODS

This study was conducted on 82 participants who were referred to the Tabesh Medical Imaging Center, Tabriz, Islamic Republic of Iran, during 2013. Echo-planar diffusion-weighted imaging of the pancreas was carried out with b-values of 50, 400 and 800 s mm(-2), and ADC values were assessed for the head, body and tail sections of the pancreas.

RESULTS

The ADC values for the head, body and tail sections of the pancreas in female participants were significantly greater than those in male subjects (p < 0.05). ADC values for these parts among subjects with different BMI differed significantly (p < 0.05). Regarding age, there were no statistically meaningful differences among the ADC values for the three parts (p > 0.05).

CONCLUSION

Gender and BMI effect the ADC values of the three sections of the pancreas. Thus, knowledge of the basic values based on gender and BMI can improve diagnostics. Having looked at age factor, it seems that the ADC values were not significantly different.

ADVANCES IN KNOWLEDGE

According to the results pancreatic ADC values appear to be influenced by gender and BMI but not by age.

Diffusion tensor tractography in the presurgical assessment of cerebral gliomas

Glioma is the most common intra-axial brain tumor characterized by invasion into the surrounding white matter (WM) tracts. These tumors are usually diagnosed by conventional MRI, but this method is unable to describe the relationship between tumor and neighboring WM tracts. Diffusion tensor tractography (DTT) is a new imaging modality which can solve this problem. The current study evaluated the application of DTT imaging in the presurgical assessment of gliomas, and introduces this new modality and its importance to physicians and imaging centers in Iran. Ten patients with intra-axial brain tumor and suspicion of glioma underwent conventional brain MRI pulse sequences and DTT imaging between December 2011 and February 2013 with a 1.5 Tesla system using 64 independent diffusion encoding directions. Acquired images were assessed by the neuroradiologist and neurosurgeon. The treatment strategies were recognized and compared using data before and after the tractography. On the basis of DTT data, the treatment strategy changed from radiotherapy to the craniotomy in seven patients, and in one patient, the neurosurgeon preferred to avoid surgery. In one patient, the treatment technique did not change, and in the last one radiosurgery was replaced by craniotomy. As we can infer from this study, based on the tractography results, the treatment strategy may be changed, and the treatment technique could be devised more accurately and may lead to fewer postoperative neurological deficits and better outcomes.

Ulexite-galena intermediate-weight concrete as a novel design for overcoming space and weight limitations in the construction of efficient shields against neutrons and photons

Recently, due to space and weight limitations, scientists have tried to design and produce concrete shields with increased attenuation of radiation but not increased mass density. Over the past years, the authors' had focused on the production of heavy concrete for radiation shielding, but this is the first experience of producing intermediate-weight concrete. In this study, ulexite (hydrated sodium calcium borate hydroxide) and galena (lead ore) have been used for the production of a special intermediate-weight concrete. Shielding properties of this intermediate-weight concrete against photons have been investigated by exposing the samples to narrow and broad beams of gamma rays emitted from a ⁶⁰Co radiotherapy unit. Densities of the intermediate-weight concrete samples ranged 3.64-3.90 g cm⁻³, based on the proportion of the ulexite in the mix design. The narrow-beam half-value layer (HVL) of the ulexite-galena concrete samples for 1.25 MeV ⁶⁰Co gamma rays was 2.84 cm, much less than that of ordinary concrete (6.0 cm). The Monte Carlo (MC) code MCNP4C was also used to model the attenuation of ⁶⁰Co gamma-ray photons and Am-Be neutrons of the ulexite-galena concrete with different thicknesses. The ⁶⁰Co HVL calculated by MCNP simulation was 2.87 cm, indicating a good agreement between experimental measurements and MC simulation. Furthermore, MC-calculated results showed that thick ulexite-galena concrete shields (60-cm thickness) had a 7.22 times (722 %) greater neutron attenuation compared with ordinary concrete. The intermediate-weight ulexite-galena concrete manufactured in this study may have many important applications in the construction of radiation shields with weight limitations such as the swing or sliding doors that are currently used for radiotherapy treatment rooms.