Venous thromboembolism (VTE) is the second leading cause of death in patients with cancer. These patients are at a high risk of VTE recurrence and bleeding during anticoagulant therapy. The International Initiative on Thrombosis and Cancer is an independent academic working group aimed at establishing a global consensus for the treatment and prophylaxis of VTE in patients with cancer. The International Initiative on Thrombosis and Cancer last updated its evidence-based clinical practice guidelines in 2016 with a free, web-based mobile phone application, which was subsequently endorsed by the International Society on Thrombosis and Haemostasis. The 2019 International Initiative on Thrombosis and Cancer clinical practice guidelines, which are based on a systematic review of the literature published up to December, 2018, are presented along with a Grading of Recommendations Assessment Development and Evaluation scale methods, with the support of the French National Cancer Institute. These guidelines were reviewed by an expanded international advisory committee and endorsed by the International Society on Thrombosis and Haemostasis. Results from head-to-head clinical trials that compared direct oral anticoagulant with low-molecular-weight heparin are also summarised, along with new evidence for the treatment and prophylaxis of VTE in patients with cancer.

/pdf/2019-international-clinical-practice-guidelines-for-the-1i79gau8u9.pdf

2019 international clinical practice guidelines for the treatment and prophylaxis of venous thromboembolism in patients with cancer.

American Society of Hematology 2021 guidelines for management of venous thromboembolism: prevention and treatment in patients with cancer

Diffusion weighted imaging (DWI) is a method of signal contrast generation based on the differences in Brownian motion. DWI is a method to evaluate the molecular function and micro-architecture of the human body. DWI signal contrast can be quantified by apparent diffusion coefficient maps and it acts as a tool for treatment response evaluation and assessment of disease progression. Ability to detect and quantify the anisotropy of diffusion leads to a new paradigm called diffusion tensor imaging (DTI). DTI is a tool for assessment of the organs with highly organised fibre structure. DWI forms an integral part of modern state-of-art magnetic resonance imaging and is indispensable in neuroimaging and oncology. DWI is a field that has been undergoing rapid technical evolution and its applications are increasing every day. This review article provides insights in to the evolution of DWI as a new imaging paradigm and provides a summary of current role of DWI in various disease processes.

Diffusion weighted imaging: Technique and applications

Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools.

Level of Evidence: 5

J. Magn. Reson. Imaging 2016

/pdf/diffusion-weighted-breast-mri-clinical-applications-and-1mmrs6cbdp.pdf

Diffusion-weighted breast MRI: Clinical applications and emerging techniques

Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advances in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties-cellularity, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: 1) cancer detection and diagnosis; 2) cancer grading, staging, and classification; and 3) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multicenter clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:23-40.

/pdf/diffusion-mri-of-cancer-from-low-to-high-b-values-1v7r36zdyo.pdf

Diffusion MRI of cancer: From low to high b-values.

OBJECTIVE. The purpose of this article is to investigate whether apparent diffusion coefficient (ADC) might be used as a universal biomarker for response evaluation in different tumors. SUBJECTS AND METHODS. Twenty-one patients with lung cancer, 12 patients with esophageal cancer, 19 patients with liver metastases, 24 patients with gastric cancer, and 26 patients with rectal cancer were recruited to the study. Percentage changes in the ADC and changes in the size of responding and nonresponding lesions of different tumors after treatment were analyzed using repeated measures analysis of variance. RESULTS. There was no significant difference among the percentage ADC changes of different tumors (F = 1.57; p = 0.192). Clear differences were seen in the percentage ADC changes between responding and nonresponding tumors (F = 21.62; p < 0.001), which were significant at every time point after the start of treatment (early time point, F = 19.75 and p < 0.001; middle time point, F = 11.23 and p = 0.001; and later...

https://www.ajronline.org/doi/pdfplus/10.2214/AJR.10.4912

Early evaluation of cancer response by a new functional biomarker: apparent diffusion coefficient.

Diffusion-weighted MR imaging is a promising technique that may be helpful in predicting responses to targeted therapy in patients with gastrointestinal stromal tumors through the early changes in apparent diffusion coefficients at 1 week after therapy.

Gastrointestinal Stromal Tumors Treated with Imatinib Mesylate: Apparent Diffusion Coefficient in the Evaluation of Therapy Response in Patients

Objective To explore the correlation between the spectral computed tomography (CT) imaging parameters and the Ki-67 labeling index in lung adenocarcinoma. Methods Spectral CT imaging parameters [iodine concentrations of lesions (ICLs) in the arterial phase (ICLa) and venous phase (ICLv), normalized IC in the aorta (NICa/NICv), slope of the spectral HU curve (λHUa/λHUv) and monochromatic CT number enhancement on 40 keV and 70 keV images (CT40keVa/v, CT70keVa/v)] in 34 lung adenocarcinomas were analyzed, and common molecular markers, including the Ki-67 labeling index, were detected with immunohistochemistry. Different Ki-67 labeling indexes were measured and grouped into four grades according to the number of positive-stained cells (grade 0, ≤1%; 1% 30%). One-way analysis of variance (ANOVA) was used to compare the four different grades, and the Bonferroni method was used to correct the P value for multiple comparisons. A Spearman correlation analysis was performed to further research a quantitative correlation between the Ki-67 labeling index and spectral CT imaging parameters. Results CT40keVa, CT40keVv, CT70keVa and CT70keVv increased as the grade increased, and CT70keVa and CT70keVv were statistically significant (P<0.05). These four parameters and the Ki-67 labeling index showed a moderate positive correlation with lung adenocarcinoma nodules. ICL, NIC and λHU in the arterial and venous phases were not significantly different among the four grades. Conclusions The spectral CT imaging parameters CT40keVa, CT40keVv, CT70keVa and CT70keVv gradually increased with Ki-67 expression and showed a moderate positive correlation with lung adenocarcinomas. Therefore, spectral CT imaging parameter-enhanced monochromatic CT numbers at 70 keV may indicate the extent of proliferation of lung adenocarcinomas.

Spectral CT imaging parameters and Ki-67 labeling index in lung adenocarcinoma.

Background: The aim of this study was to investigate differences in the imaging features of mass-like tuberculosis and lung cancer on conventional MR sequences to improve the diagnostic ability for pulmonary masses.
 Methods: Thirty patients with suspicious pulmonary lesions were enrolled and diagnosed with tuberculosis by pathology or comprehensive clinical diagnoses. Twenty-six cases of lung cancer were retrospectively analyzed. Transverse fat-suppressed T2-weighted (T2W) imaging and T1-weighted (T1W) imaging were obtained at 1.5 Tesla. The imaging characteristics of lesions on the T2W and T1W images were compared between the two groups. The imaging features of enlarged mediastinal lymph nodes on T2W images were studied and compared. Results: On T2W images, there was a higher percentage of lesions containing hypointensity in the tuberculosis group (GTB) than in the lung cancer group (GLC) (P=0.004).The incidence of lesions demonstrating heterogeneous intensity was significantly greater in the GTB than in the GLC (70.0% vs . 7.7%, P=0.001). Approximately 92.3% of the lung cancer cases showed hyperintensity, a proportion substantially greater than that in the GTB (6.7%). On T1W images, more cases showed hyperintensity in the GTB than in the GLC (43.3% vs . 7.7%, P=0.003). The signal intensity ratios (SIRs) of the lesion to rhomboid muscle on T2W and T1W images were significantly different between the two groups. The mean intrasubject standard deviation (SD) of lesions in the GTB was markedly greater than that in the GLC on both T2W and T1W images. Benign mediastinal lymph nodes in the GTB showed a variety of signals on T2W images, whereas 80% of metastatic mediastinal lymph nodes displayed slight homogeneous hyperintensity, and this difference between the two groups was statistically significant. Conclusions: Conventional MR sequences can reveal the essential differences between mass-like tuberculosis and lung cancer and may be helpful for discriminating pulmonary masses.

/pdf/conventional-mri-to-detect-the-differences-between-mass-like-1gf491fa2e.pdf

Conventional MRI to detect the differences between mass-like tuberculosis and lung cancer.

Objective: To determine the value of diffusion-tensor imaging (DTI) as an adjunct to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for improved accuracy of differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive breast carcinoma (IBC).
 Methods: The MRI data of 63 patients pathologically confirmed as breast cancer were analyzed. The conventional MRI analysis metrics included enhancement style, initial enhancement characteristic, maximum slope of increase, time to peak, time signal intensity curve (TIC) pattern, and signal intensity on FS-T2WI. The values of apparent diffusion coefficient (ADC), directionally-averaged mean diffusivity (D avg ), exponential attenuation (EA), fractional anisotropy (FA), volume ratio (VR) and relative anisotropy (RA) were calculated and compared between DCIS and IBC. Multivariate logistic regression was used to identify independent factors for distinguishing IBC and DCIS. The diagnostic performance of the diagnosis equation was evaluated using the receiver operating characteristic (ROC) curve. The diagnostic efficacies of DCE-MRI, DWI and DTI were compared independently or combined.
 Results: EA value, lesion enhancement style and TIC pattern were identified as independent factor for differential diagnosis of IBC and DCIS. The combination diagnosis showed higher diagnostic efficacy than a single use of DCE-MRI (P=0.02), and the area of the curve was improved from 0.84 (95% CI, 0.67-0.99) to 0.94 (95% CI, 0.85-1.00).
 Conclusions: Quantitative DTI measurement as an adjunct to DCE-MRI could improve the diagnostic performance of differential diagnosis between DCIS and IBC compared to a single use of DCE-MRI.

Diffusion-tensor imaging as an adjunct to dynamic contrast-enhanced MRI for improved accuracy of differential diagnosis between breast ductal carcinoma in situ and invasive breast carcinoma.

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