Magnetic Resonance Spectroscopy of the Breast at 3T: Pre- and Post-Contrast Evaluation for Breast Lesion Characterization

Purpose. To determine whether in vivo proton magnetic resonance spectroscopy at 3T can provide accurate breast lesion characterization, and to determine the effect of gadolinium on the resonance of tCho. Methods. Twenty-four positive-mammogram patients were examined on a 3T MR scanner. 1H-MRS was performed before and after gadolinium administration. tCho peak was qualitatively evaluated before and after contrast injection. Results. Fourteen out of 27 lesions proved to be malignant after histopathological diagnosis. Using 1H-MRS, before contrast injection, 6/14 confirmed malignancies and 11/13 benign lesions were correctly classified; while, after contrast injection, 11/14 confirmed malignancies and 12/13 benign processes were correctly classified. Post gadolinium 1H-MRS proved useful in picking up tCho signal, improving the overall accuracy, sensitivity, and specificity by 35%, 83%, and 9%, respectively. Conclusion. 1H-MRS overall accuracy, sensitivity, and specificity in detecting breast lesion's malignancy were increased after gadolinium administration. It is prudent to perform 1H-MRS before contrast injection in large breast lesions to avoid choline underestimation. In cases of small or non-mass lesions, it is recommended to perform 1H-MRS after contrast injection for better voxel prescription to enable a reliable preoperative diagnosis

Imaging of traumatic lesions of abdominal viscera

Trauma to the abdomen accounts for approximately 10% of trauma deaths. The injury may be blunt or penetrating. Abdominal organs are frequently injured from blunt trauma. Rapid acceleration-deceleration of abdominal viscera at the moment of impact generates shearing forces that result in transection or laceration of the underlying parenchyma and vessels, most commonly at points of attachment or relative fixation. Prompt recognition and management of intra-abdominal organ injury is essential in order to minimize morbidity and mortality. New imaging modalities have altered the diagnostic approach to these patients. The use of computed tomography (CT) and ultrasound has largely replaced diagnostic peritoneal lavage (DPL) in the initial evaluation of abdominal injury in hemodynamically stable patients. Ultrasound is an important method in the rapid evaluation of abdominal trauma as it is non-invasive, safe, cost-effective, readily available, portable, can be repeated as often as required and involves no radiation or use of contrast material. Its use is established in the detection of intraperitoneal fluid, but it has low sensitivity (83%) in the detection of injuries to abdominal viscera and the evaluation of the retroperitoneum. In addition, its use is further limited by the body habitus, the presence of excessive bowel gas, the existence of open wounds or subcutaneous emphysema, and by reduced ability of the patient to cooperate. Computed tomography has become the method of choice in the diagnosis of blunt abdominal trauma. It has been shown to be highly sensitive, specific and accurate in detecting the presence and the extent of injury to the abdomen. CT also provides important additional information regarding associated extra-abdominal injuries (e.g., pneumothorax, fractures). In addition, it provides useful information in patients in whom clinical abdominal examination is either equivocal or unreliable, due often to altered mental status. The overall trend towards nonoperative management of abdominal trauma is due to part in the ability of helical CT not only to define injury but to exclude significant injury, thereby making possible the avoidance of unnecessary surgery. Nowadays, magnetic resonance imaging is not used in acute abdominal trauma because of the lengthy imaging times, monitoring difficulties, the artefacts created by the metallic instruments these patients usually carry, and the lack of availability of the equipment in many centers

Reproducibility of apparent diffusion coefficient measurements evaluated with different workstations

Aim To evaluate apparent diffusion coefficient (ADC) measurements of breast lesions on different computer platforms to address post-processing influences on ADC measurement reproducibility. Materials and methods One hundred biopsy-proven breast lesions were included in this prospective study. MRI examination was performed at 3 T using standard sequences and an echo planar diffusion-weighted imaging sequence with b-values of 0 and 850 s/mm2. The images were reviewed by two radiologists in consensus. Regions of interest were placed manually within the lesion, following its contour. Care was taken to exclude adjacent normal tissue or necrotic tissue and cystic components within the lesion. The mean ADC value was measured for each lesion on two different platforms: On the MRI workstation that came with the scanner and on a commercially available DICOM (digital imaging and communication in medicine) viewer. Agreement between workstation measurements was evaluated using intraclass correlation coefficient and Bland–Altman plots. Results Fifty-nine malignant and 41 benign lesions were analysed. Of the benign lesions, 28 were mass lesions and 13 were non-mass-like enhancements. In addition, 46 of the malignant lesions were masses and 13 were non-mass-like enhancements. Agreement between the two workstation measurements was high (intraclass correlation coefficients=0.981). Using Bland–Altman plots, no systematic differences were identified between workstations. Limits of agreement ranged between a minimum of –0.071×10−3 mm2/s and a maximum of 0.102×10−3 mm2/s. Conclusion ADC measurements are reproducible among the workstations considered in this study. © 2017 The Royal College of Radiologist

Mobile platforms supporting health professionals: Need, technical requirements, and applications

Mobile computing is beginning defining the future of healthcare. The vast majority of mHealth applications are related to fitness, training and self-monitoring; limited applications are targeting physicians and doctor-patient interactions. However this can change. In this chapter the background of applications related to medical imaging and clinical and laboratory medicine is analyzed. A technological framework supporting mHealth applications in an agnostic manner is also introduced. Within this framework there are implemented two application examples, one application (ImaginX) supporting a health ecosystem (hospitals, radiologists, clinicians, patients) for medical image management. The second application (HPVGuard) supports a divergent but cooperating environment of laboratory and clinical doctors and patients involved in cervical cancer prevention and control. The two applications are analyzed and issues related to user acceptance and future directions are presented. mHealth has the potential to shape health future not by just translating existing applications but by inspiring new ideas. © 2017 by IGI Global. All rights reserved

Incorporating diffusion-weighted imaging in a diagnostic algorithm for multiparametric MR mammography

Background: Apparent diffusion coefficient (ADC) measurements are not incorporated in BI-RADS classification. Purpose: To assess the probability of malignancy of breast lesions at magnetic resonance mammography (MRM) at 3 T, by combining ADC measurements with the BI-RADS score, in order to improve the specificity of MRM. Material and Methods: A total of 296 biopsy-proven breast lesions were included in this prospective study. MRM was performed at 3 T, using a standard protocol with dynamic sequence (DCE-MRI) and an extra echo-planar diffusion-weighted sequence. A freehand region of interest was drawn inside the lesion, and ADC values were calculated. Each lesion was categorized according to the BI-RADS classification. Logistic regression analysis was employed to predict the probability of malignancy of a lesion. The model combined the BI-RADS classification and the ADC value. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were calculated. Results: In total, 153 malignant and 143 benign lesions were analyzed; 257 lesions were masses and 39 lesions were non-mass-like enhancements. The sensitivity and specificity of the combined method were 96% and 86%, respectively, in contrast to 95% and 81% with BI-RADS classification alone. Conclusion: We propose a method of assessing the probability of malignancy in breast lesions by combining BI-RADS score and ADC values into a single formula, increasing sensitivity and specificity compared to BI-RADS classification alone. © The Foundation Acta Radiologica 2021

Cancer vascularization: Implications in radiotherapy?

Purpose: Although hypoxia is considered a major cause of failure of radiotherapy, the mechanisms of tumor hypoxia are unclear, and effective ways for its correction or targeting are missing. Tumoral vasculature is the vehicle for the hemoglobin to reach the tumoral stroma, Although anemia has long been focused on as an important parameter related to tumor hypoxia, differences in vascular density may also affect the intratumoral access of hemoglobin. Methods and Materials: In the present study, we examined the vascular density in 1459 human carcinomas. The distribution of the vascular density within tumors was studied in 436 non-small-cell lung carcinomas and 298 breast carcinomas. Results: The vascular density was found to vary up to 22-fold even among tumors of the same histology. Overall, the vascular density was significantly higher in the tumor periphery as compared to inner areas, Three different patterns of vascularization were identified in both lung and breast cancer specimens; (I) tumors with low or (2) tumors with high vessel density throughout the tissue section, and (3) tumors with high vessel density in the tumor periphery and low in inner areas. The death rate following surgery showed a direct association with the vascular density in lung, breast, colon, and endometrial cancer, In inoperable gastric cancer patients treated with chemotherapy, and in head and neck cancer patients treated with radical chemoradiotherapy there was a 'U-like' association of the death rate with the vascular density suggesting that very low (poor oxygen and drug availability) and very high (intensified angiogenic pathways) vascularization are both linked to poor outcome. Conclusion: The present study stresses the importance of the vascular density as a putative variable that may have affected the results of large clinical trials that investigated the role of anemia, hyperbaric oxygen, hypoxic sensitizers, or even of combined chemoradiotherapy in the outcome of radiation treatment. (C) 2000 Elsevier Science Inc

Mobile platforms supporting health professionals: Need, technical requirements, and applications

Mobile computing is beginning defining the future of healthcare. The vast majority of mHealth applications are related to fitness, training and self-monitoring; limited applications are targeting physicians and doctor-patient interactions. However this can change. In this chapter the background of applications related to medical imaging and clinical and laboratory medicine is analyzed. A technological framework supporting mHealth applications in an agnostic manner is also introduced. Within this framework there are implemented two application examples, one application (ImaginX) supporting a health ecosystem (hospitals, radiologists, clinicians, patients) for medical image management. The second application (HPVGuard) supports a divergent but cooperating environment of laboratory and clinical doctors and patients involved in cervical cancer prevention and control. The two applications are analyzed and issues related to user acceptance and future directions are presented. mHealth has the potential to shape health future not by just translating existing applications but by inspiring new ideas. © 2016 by IGI Global. All rights reserved

Contrast-enhanced and unenhanced diffusion-weighted imaging of the breast at 3 T

Aim: To evaluate the effect of intravenous gadolinium contrast agent on diffusion-weighted sequences and apparent diffusion coefficient (ADC) measurements at 3 T. Materials and methods: Sixty-two biopsy-proven breast lesions were included in this prospective study. Magnetic resonance imaging (MRI) was performed at 3 T, using four echo-planar diffusion-weighted sequences (7,100 ms repetition time, 84 ms echo time) with b-values of 0 and 850, and 0 and 1,000 s/mm2. The first pair of DWI sequences was taken before intravenous contrast medium injection. The second pair of sequences was taken 6.5 minutes after intravenous contrast medium administration (right after the dynamic T1 sequence). A freeform region of interest (ROI) was drawn inside the lesion excluding adjacent normal tissue, necrotic, or cystic components and ADC values were calculated. The paired samples t-test was used to assess differences between ADC measurements before and after intravenous contrast medium administration. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were calculated for each diffusion sequence. Results: Twenty-seven malignant and 35 benign lesions were analysed. Fifty-eight lesions were masses, and four lesions were non-mass-like enhancements (NMLEs). Two of the NMLEs were malignant, and two were benign lesions. The contrast-enhanced ADC measurements were lower than the unenhanced measurements on b=850 and 1,000 s/mm2 (p<0.05). The receiver operating characteristic (ROC) analysis displayed similar area under the curve values between the different diffusion sequences. Conclusion: The injection of intravenous contrast medium reduces ADC values; however, the effect of contrast medium is modest. Sensitivity and specificity are not significantly affected. © 2018 The Royal College of Radiologist

Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis

Over the years, MR systems have evolved from imaging modalities to advanced computational systems producing a variety of numerical parameters that can be used for the noninvasive preoperative assessment of breast pathology. Furthermore, the combination with state-of-the-art image analysis methods provides a plethora of quantifiable imaging features, termed radiomics that increases diagnostic accuracy towards individualized therapy planning. More importantly, radiomics can now be complemented by the emerging deep learning techniques for further process automation and correlation with other clinical data which facilitate the monitoring of treatment response, as well as the prediction of patient's outcome, by means of unravelling of the complex underlying pathophysiological mechanisms which are reflected in tissue phenotype. The scope of this review is to provide applications and limitations of radiomics towards the development of clinical decision support systems for breast cancer diagnosis and prognosis. © 2018 Ioannis Tsougos et al