Extracranial applications of diffusion-weighted magnetic resonance imaging

Diffusion-weighted MRI has become more and more popular in the last couple of years. It is already an accepted diagnostic tool for patients with acute stroke, but is more difficult to use for extracranial applications due to technical challenges mostly related to motion sensitivity and susceptibility variations (e.g., respiration and air-tissue boundaries). However, thanks to the newer technical developments, applications of body DW-MRI are starting to emerge. In this review, we aim to provide an overview of the current status of the published data on DW-MRI in extracranial applications. A short introduction to the physical background of this promising technique is provided, followed by the current status, subdivided into three main topics, the functional evaluation, tissue characterization and therapy monitorin

MRI-guided focused ultrasound surgery in musculoskeletal diseases: the hot topics

MRI-guided focused ultrasound surgery (MRgFUS) is a minimally invasive treatment guided by the most sophisticated imaging tool available in today's clinical practice. Both the imaging and therapeutic sides of the equipment are based on non-ionizing energy. This technique is a very promising option as potential treatment for several pathologies, including musculoskeletal (MSK) disorders. Apart from clinical applications, MRgFUS technology is the result of long, heavy and cumulative efforts exploring the effects of ultrasound on biological tissues and function, the generation of focused ultrasound and treatment monitoring by MRI. The aim of this article is to give an updated overview on a "new" interventional technique and on its applications for MSK and allied sciences

A comparative study on predictive value of malignancy in suspicious breast masses of birads III & above categories using sonoelastography and dynamic MR Mammogram

AIM & OBJECTIVES: To assess and compare the accuracy of Sonoelastogram breast and Dynamic MR Mammogram in predicting benign vs. malignant breast masses in BIRADS III & above lesions, with subsequent recommendation for biopsy. MATERIALS AND METHODS: Prospective cohort study conducted from August 2016 – May 2017, for a period of 10 months with 45 cases (44 female and 1 male) who present with breast masses to Out Patient Department in Government Kilpauk Medical College and Hospital, Chennai. All cases were subjected to conventional B mode Ultrasonogram ; only cases with BIRADS III and above categories were assessed further by Sonoelastography and Dynamic contrast enhanced MR Mammogram. Tsukuba elastographic scoring from 1 to 5 were assigned and Dynamic MR kinetic curve patterns 1 to 3 were analysed based on contrast uptake by the lesion in initial and delayed phases. RESULTS: Among the Final Diagnosis (HPE) of the studied breast pathologies, 19 malignant and 26 Benign lesions are noted. Sensitivity of Dynamic MR Mammogram curve patterns is 89.5% and the specificity is 96.2%. Sensitivity of Sonoelastography is 68.4% and the specificity is 92.3%. The diagnostic accuracy of Dynamic MRI Mammogram is 93.3% and of Sonoelastography is 82.2%.The comparision between Final Diagnosis of breast masses with HPE and Dynamic MR Mammogram curve analysis & Sonoelastography is statistically significant. CONCLUSION: Both Sonoelastography and MR Mammogram are efficient techniques to evaluate breast lesions and can potentially decrease the number of unnecessary biopsies. In our study, both the sensitivity and specificity are high for MR Mammogram compared to Sonoelastography

Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction

سرطان الثدي يعتبر واحد من الامراض القاتلة الشائعة بين النساء في جميع أنحاء العالم. والتشخيص المبكر لسرطان الثدي الكشف المبكر من أهم استراتيجيات الوقاية الثانوية. نظرًا لاستخدام التصوير الطبي على نطاق واسع في تشخيص العديد من الأمراض المزمنة ومراقبتها، فقد تم اقتراح العديد من خوارزميات معالجة الصور على مر السنين لزيادة مجال التصوير الطبي بحيث تصبح عملية التشخيص أكثر دقة وكفاءة. تقدم هذه الدراسة خوارزمية جديدة لاستخراج الخواص العميقة من نوعين من صور الرنين المغناطيسي T2W-TSE و STIR MRI كمدخلات للشبكات العصبية العميقة المقترحة والتي تُستخدم لاستخراج الخواص للتمييز بين فحوصات التصوير بالرنين المغناطيسي للثدي المرضية والصحية. في هذه الخوارزمية، تتم معالجة فحوصات التصوير بالرنين المغناطيسي للثدي مسبقًا قبل خطوة استخراج الخواص لتقليل تأثيرات الاختلافات بين شرائح التصوير بالرنين المغناطيسي، وفصل الثدي الايمن عن الايسر، بالإضافة الى عزل خلفية الصور. وقد كانت أقصى دقة تم تحقيقها لتصنيف مجموعة بيانات تضم 326 شريحة تصوير بالرنين المغناطيسي للثدي 98.77٪. يبدو أن النموذج يتسم بالكفاءة والأداء ويمكن بالتالي اعتباره مرشحًا للتطبيق في بيئة سريرية.Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature extraction step to enhance and preserve the fine details of the breast MRI scans boundaries by using fractional integral entropy FIE algorithm, to reduce the effects of the intensity variations between MRI slices, and finally to separate the right and left breast regions by exploiting the symmetry information. The obtained features are classified using a long short-term memory (LSTM) neural network classifier. Subsequently, all extracted features significantly improves the performance of the LSTM network to precisely discriminate between pathological and healthy cases. The maximum achieved accuracy for classifying the collected dataset comprising 326 T2W-TSE images and 326 STIR images is 98.77%. The experimental results demonstrate that FIE enhancement method improve the performance of CNN in classifying breast MRI scans. The proposed model appears to be efficient and might represent a useful diagnostic tool in the evaluation of MRI breast scans

Quantitative assessment of diffusion-weighted MR imaging in patients with primary rectal cancer: Correlation with FDG-PET/CT

Purpose: The aim of the study was to assess correlations between parameters on diffusionweighted imaging and 2-deoxy-2-[ 18F]fluoro-D-glucose- positron emission tomography/computed tomography (FDG-PET/CT) in rectal cancer. Procedures: Thirty-three consecutive patients with pathologically confirmed rectal adenocarcinoma were included in this study. Apparent diffusion coefficient (ADC) maps were generated to calculate ADC mean (average ADC), ADC min (lowest ADC), tumor volume, and total diffusivity index (TDI). PET/CT exams were performed within 1 week of magnetic resonance imaging. Standardized uptake values (SUVs) were normalized to the injected FDG dose and body weight. SUV max (maximum SUV), SUV mean (average SUV), tumor volume, and total lesion glycolysis (TLG) were calculated using a 50% threshold. Results: Significant negative correlations were found between ADC min and SUV max (r=-0.450, p=0.009), and between ADC mean and SUV mean (r=-0.402, p=0.020). A significant positive correlation was found between TDI and TLG (r=0.634, p<0.001). Conclusion: The significant negative correlations between ADC and SUV suggest an association between tumor cellularity and metabolic activity in primary rectal adenocarcinoma. © Academy of Molecular Imaging and Society for Molecular Imaging, 2010.published_or_final_versionSpringer Open Choice, 21 Feb 201

MR determined brain metabolic pattern in patients with brain metastases and adolescents with low birth weight

The clinical applications of MRS have become a supplement to MR imaging (MRI) for diagnosis and treatment monitoring of several pathologies. In this thesis MR spectroscopy (MRS) has been used to assess brain metastases in adult cancer patients and cerebral metabolites in frontal lobe of adolescents. Children born with very low birth weight are at risk of later neurodevelopment problems. Adolescents with different birth weight were examined using MRI and MRS and multivariate analyses for assessing differences in cerebral metabolites. The results from the multivariate analyses were consistent with observations in earlier published MRI findings, motor skills, psychiatric symptoms and disorders detected in the same participants. The classification of the adolescents was based on metabolic pattern differences which were only explored by the multivariate analyses. When the spectral information shows small or complex differences the interpretations become a challenge. In three of the four papers in this thesis, multivariate analyses were used as a tool to interpret the spectral information. Brain metastasis is the dominating type of brain tumors which represent an oncologic challenge. The incidence of brain metastases is probably increasing due to improved treatment strategy of patient with primary cancer, prolonging their survival and brain metastases get time to develop. In some cases patients have an unknown primary cancer or several primary cancers. If MRS could provide metabolic information about brain metastases especially in differentiating it from the primary cancer, it might be a supplement to the conventional diagnostics and could help to optimize the cancer treatment. In the two last papers in vivo and ex vivo MRS of brain metastases were obtained before treatment and the spectra were analysed by using both principal component analysis and regression analysis. The spectra were classified according to primary cancer and clinical outcome five months after start of treatment. The results showed a significant correlation of spectral findings and clinical outcome of brain metastases patients. From the MR theory, signal-to-noise ratio and resolution in MR spectra should increase by a factor of two with double the magnetic field strength. Different studies using in vivo MRS have shown that the situation varies. In Paper II the effect of increased magnetic field from 1.5T to 3T was investigated in spectra obtained in patients with brain metastases. The comparisons of spectral improvements in SNR and spectral resolution were made by ratio calculations. The gain was smaller than expected probably caused by various definitions of effective volume size at different clinical scanners. In conclusion, in vivo and ex vivo MR spectroscopy can determine metabolic pattern on clinically highly relevant questions.PhD i medisinsk teknologiPhD in Medical Technolog

Contrast-Enhanced Ultrasonography (CEUS) in Imaging of the Reproductive System in Dogs: A Literature Review

The use of contrast-enhanced ultrasound (CEUS) has been widely reported for reproductive imaging in humans and animals. This review aims to analyze the utility of CEUS in characterizing canine reproductive physiology and pathologies. In September 2022, a search for articles about CEUS in canine testicles, prostate, uterus, placenta, and mammary glands was conducted on PubMed and Scopus from 1990 to 2022, showing 36 total results. CEUS differentiated testicular abnormalities and neoplastic lesions, but it could not characterize tumors. In prostatic diseases, CEUS in dogs was widely studied in animal models for prostatic cancer treatment. In veterinary medicine, this diagnostic tool could distinguish prostatic adenocarcinomas. In ovaries, CEUS differentiated the follicular phases. In CEH-pyometra syndrome, it showed a different enhancement between endometrium and cysts, and highlighted angiogenesis. CEUS was shown to be safe in pregnant dogs and was able to assess normal and abnormal fetal–maternal blood flow and placental dysfunction. In normal mammary glands, CEUS showed vascularization only in diestrus, with differences between mammary glands. CEUS was not specific for neoplastic versus non-neoplastic masses and for benign tumors, except for complex carcinomas and neoplastic vascularization. Works on CEUS showed its usefulness in a wide spectrum of pathologies of this non-invasive, reliable diagnostic procedur

Emerging methods for prostate cancer imaging: evaluating cancer structure and metabolic alterations more clearly

Imaging plays a fundamental role in all aspects of the cancer management pathway. However, conventional imaging techniques are largely reliant on morphological and size descriptors that have well-known limitations, particularly when considering targeted-therapy response monitoring. Thus, new imaging methods have been developed to characterise cancer and are now routinely implemented, such as diffusion-weighted imaging, dynamic contrast enhancement, positron emission technology (PET) and magnetic resonance spectroscopy. However, despite the improvement these techniques have enabled, limitations still remain. Novel imaging methods are now emerging, intent on further interrogating cancers. These techniques are at different stages of maturity along the biomarker pathway and aim to further evaluate the cancer microstructure (vascular, extracellular and restricted diffusion for cytometry in tumours) magnetic resonance imaging (MRI), luminal water fraction imaging] as well as the metabolic alterations associated with cancers (novel PET tracers, hyperpolarised MRI). Finally, the use of machine learning has shown powerful potential applications. By using prostate cancer as an exemplar, this Review aims to showcase these potentially potent imaging techniques and what stage we are at in their application to conventional clinical practice

New directions in head and neck imaging

Computerized tomography (CT) and magnetic resonance imaging (MRI), positron emission tomography (PET) and the hybrid modality of PET/CT are sensitive and reliable tools for detection and staging of head and neck cancers. This article describes the role of PET/CT in initial staging of head and neck squamous cell carcinoma, the utility of CT/MR perfusion imaging in qualitative analysis of tumor tissue, and the usefulness of diffusion weighted MR and dynamic contrast-enhanced MR imaging in head and neck oncological imaging. J. Surg. Oncol. 2008;97:644–648. © 2008 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58636/1/21022_ftp.pd

Effectivity of combined diffusion-weighted imaging and contrast-enhanced MRI in malignant and benign breast lesions

Purpose: Mammography is the most commonly used diagnostic test for breast lesion detection and evaluation, but in dense breast parenchyma it lowers its sensitivity to detect small lesions. Sensitivity and specificity improves with combined use of contrast-enhanced magnetic resonance imaging (CE-MRI) and diffusion-weighted imaging (DWI) in differentiating benign and malignant breast lesions. The aim of the study was to evaluate the effectivity of combined dynamic CE-MRI and DWI in differentiating benign and malignant lesions, and to calculate the apparent diffusion coefficient (ADC) values of malignant and benign lesions of the breast. Material and methods: Fifty-seven patients with 68 lesions were included in the study. MRI of breast using different sequences was acquired on 1.5 Tesla Machine with dedicated breast coils. Dynamic CE-MRI along with DWI was acquired for each patient. Histopathological reports were accepted as the standard of reference. Results: Out of 68 lesions, 37 were malignant on biopsy (54.4%) and 31 were benign (45.5%). The sensitivity of CE-MRI was 92%, specificity 84.21%, positive predictive values (PPV) 88.46 %, and negative predictive values (NPP) 88.89%. The sensitivity of DWI-MRI was 91.6%, specificity was 90.6%, PPV 91.6%, and NPP 90.6%. The sensitivity of combined DWI-MRI and CE-MRI was 95.0%, specificity was 96.43%, PPV 97.44%, and NPP 93.10%. Mean ADCs of benign lesions (b = 800) was 1.905 ± 0.59 × 10-3 mm (2)/s, which was significantly higher than those of malignant lesions (b = 800) 1.014 ± 0.47 × 10-3 mm (2)/s. Conclusions: Multi-parametric MRI is an excellent non-invasive modality with high sensitivity and specificity to differen­tiate malignant from benign breast lesions