Non-contrast-enhanced magnetic resonance imaging: Objective figures in differentiation between acute and chronic deep venous thrombosis in the lower extremities

[Translation into French and republication of: "Recurrent venous thromboembolism in anticoagulated cancer patients: diagnosis and treatment"]

Patients with cancer are at significantly increased risk of venous thromboembolism (VTE), due both to the impact of malignant disease itself and to the impact of certain anticancer drugs on haemostasis. This is true both for first episode venous thromboembolism and recurrence. The diagnosis and management of VTE recurrence in patients with cancer poses particular challenges, and these are reviewed in the present article, based on a systematic review of the relevant scientific literature published over the last decade. Furthermore, it is uncertain whether diagnostic algorithms for venous thromboembolism, validated principally in untreated non-cancer patients, are also valid in anticoagulated cancer patients: the available data suggests that clinical decision rules and D-dimer testing perform less well in this clinical setting. In patients with cancer, computed tomography pulmonary angiography and venous ultrasound appear to be the most reliable diagnostic tools for diagnosis of pulmonary embolism and deep vein thrombosis respectively. Options for treatment of venous thromboembolism include low molecular weight heparins (at a therapeutic dose or an increased dose), fondaparinux or oral direct factor Xa inhibitors. The choice of treatment should take into account the nature (pulmonary embolism or VTE) and severity of the recurrent event, the associated bleeding risk, the current anticoagulant treatment (type, dose, adherence and possible drug-drug interactions) and cancer progression.

Recurrent venous thromboembolism in anticoagulated cancer patients: Diagnosis and treatment

Patients with cancer are at significantly increased risk of venous thromboembolism (VTE), due both to the impact of malignant disease itself and to the impact of certain anticancer drugs on haemostasis. This is true both for first episode venous thromboembolism and recurrence. The diagnosis and management of VTE recurrence in patients with cancer poses particular challenges, and these are reviewed in the present article, based on a systematic review of the relevant scientific literature published over the last decade. Furthermore, it is uncertain whether diagnostic algorithms for venous thromboembolism, validated principally in untreated non-cancer patients, are also valid in anticoagulated cancer patients: the available data suggests that clinical decision rules and D-dimer testing perform less well in this clinical setting. In patients with cancer, computed tomography pulmonary angiography and venous ultrasound appear to be the most reliable diagnostic tools for diagnosis of pulmonary embolism and deep vein thrombosis respectively. Options for treatment of venous thromboembolism include low molecular weight heparins (at a therapeutic dose or an increased dose), fondaparinux or oral direct factor Xa inhibitors. The choice of treatment should take into account the nature (pulmonary embolism or VTE) and severity of the recurrent event, the associated bleeding risk, the current anticoagulant treatment (type, dose, adherence and possible drug-drug interactions) and cancer progression.

Noncontrast MRI in assessing venous reflux of legs using QFlow analysis and radial basis function neural network technique

Since venous reflux is difficult to quantify, triggered angiography non-contrast-enhanced (TRANCE)-magnetic resonance imaging (MRI) is a novel tool for objectively evaluating venous diseases in the lower extremities without using contrast media. This study included 26 pre-intervention patients with superficial venous reflux in the lower extremities and 15 healthy volunteers. The quantitative flow (QFlow) analyzed the phase shift information from the pixels within the region of interest from MRI. The fast and simple radial basis function neural network (RBFNN) learning model is constructed by determining the parameters of the radial basis function and the weights of the neural network. The input parameters were the variables generated through QFlow, while the output variables were morbid limbs with venous reflux and normal limb classification. The stroke volume, forward flow volume, absolute stroke volume, mean flux, stroke distance, and mean velocity of greater saphenous veins from QFlow analysis could be used to discriminate the morbid limbs of pre-intervention patients and normal limbs of healthy controls. The neural network successfully classified the morbid and normal limbs with an accuracy of 90.24% in the training stage. The classification of venous reflux using the RBFNN model may assist physicians in clinical settings.

A Novel Tool for a Challenging Disease: Stasis Leg Ulcers Assessed Using QFlow in Triggered Angiography Noncontrast Enhanced Magnetic Resonance Imaging

Imaging characteristics of stasis leg ulcers (SLUs) are not easily demonstrated through existing diagnostic tools. Early diagnosis and treatment are crucial. This pilot study was conducted to assess the quantitative flow (QFlow) in triggered angiography noncontrast enhanced (TRANCE) magnetic resonance imaging (MRI) to identify the hemodynamics of victims with stasis leg ulcers (SLUs). This study included 33 patients with SLUs and 14 healthy controls (HC). The 33 patients with SLUs were divided into a reflux (15 patients) and a nonreflux group (18 patients). QFlow was done in the reflux, the nonreflux, and the HC. The stroke volume (SV), forward flow volume (FFV), absolute flow volume (AFV), mean flow (MF), and mean velocity (MV) were higher in the reflux than in the HC group in most segments, namely the external iliac vein (EIV), popliteal vein (PV), and great saphenous vein (GSV) (SV, p = 0.008; FFV, p = 0.008; absolute stroke volume (ASV), p = 0.008; MF, p = 0.002; MV, p = 0.009). No differences in the QFlow patterns were found in the GSV segment between the nonreflux group and the HC. Excellent performance in discriminating SLU with superficial venous reflux was reported for SV in the EIV and the PV (area under the curve (AUC) = 0.851 and 0.872), FFV in the EIV and PV (AUC = 0.854 and 0.869), ASV in the EIV and PV (AUC = 0.848 and 0.881), and MF in the EIV and PV (AUC = 0.866 and 0.868). The cutoff levels of SV/FFV/ASV/MF in the EIV/FV/PV/GSV for discriminating the SLU with superficial venous reflux were identified (p < 0.005). In conclusion, SLUs present different QFlow patterns by different etiology. The QFlow parameters of all vessel segments were higher in the morbid limbs of the reflux group than HC. The GSV segment of the nonreflux group displayed a pattern like the HC.

Using Non-Contrast MRA to Discriminate between Obstructive and Nonobstructive Venous Diseases of the Legs

BACKGROUND

Venous interventions of the legs are less predictable owing to a lock of objective tools.

METHODS

One hundred and twenty patients with lower extremity venous disease were evaluated anatomically using TRANCE MRI. Then, a QFlow analysis was performed in 53 patients with only one leg affected for hemodynamic evaluation. Those patients with complete QFlow were classified into obstructive and nonobstructive.

RESULTS

The QFlow-namely, stroke volume, forward flow volume, mean flux, stroke distance (SD), and mean velocity (MV) in the external iliac vein (EIV), femoral vein (FV), popliteal vein (PV), and great saphenous vein (GSV). The obstructed group had a shorter SD and lower MV in the EIV, EIV/FV, and GSV/PV (SD: p-values of 0.025, 0.05, and 0.043, respectively; MV: p-values of 0.02, 0.05, and 0.048, respectively). A good performance in discriminating obstructive venous disease was reported for SD in the EIV (area under the curve (AUC) = 67.9%, 95% confidence interval (CI) = 53.2-82.7%), EIV/FV (AUC = 72.4%, 95% CI = 58.2-86.5%), and GSV/PV (AUC = 67.9%, 95% CI = 51.7-84.1%). The SD in the EIV, EIV/FV, and GSV/PV had the ability to discriminate between obstructive and nonobstructive diseases (p-values of 0.025, 0.005, and 0.043). The MV in the EIV, EIV/FV, and GSV/PV had ability to discriminate between obstructive and nonobstructive venous diseases (p-values of 0.02, 0.005, and 0.048).

CONCLUSIONS

The SD and MV were lower for obstructive than nonobstructive disease in the EIV.

Superficial Venous Reflux Intervention Guided by Triggered Angiography Non-Contrast-Enhanced Sequence Magnetic Resonance Imaging: Different QFlow Pattern from Health Controls

(1) Background: To assess the effectiveness of triggered angiography non-contrast-enhanced (TRANCE)-magnetic resonance imaging (MRI) in superficial venous reflux and its difference from health controls. (2) Methods: Thirty patients underwent TRANCE MRI before surgical intervention of their superficial venous reflux of the legs. Ten healthy volunteers were included as a control. (3) Results: TRANCE MRI involves the major tributaries, thus enhances the additional ablations in 20% of patients. QFlow pattern of superficial venous reflux (QFlow GSV/PV MF ratio > 1) was compared with the duplex scan (SFJ reflux) using Cohen’s kappa coefficient at 0.967. The 30 morbid legs undergoing TRANCE MRI-guide interventions and the healthy volunteers’ legs on the same side were compared. The stroke volumes (SV) are higher in EIV (p = 0.021) in the left-leg-intervention group. The mean flux (MF) is higher in the EIV (p = 0.012) and trend of increasing in GSV segment (p = 0.087) in the left-leg-intervention group. The QFlow of 10 patients with right leg intervention are higher in GSV in the right-leg-intervention group (SV p = 0.002; FFV p = 0.001; MF p = 0.001). QFlow data is shown for all legs for superficial venous intervention with GSV/PV (MF) ratio > 1. (4) Conclusions: Typical figures in QFlow (GSV/PV MF ratio > 1) could be observed in the morbid limbs but not in the controls.

Discriminating Reflux from Non-Reflux Diseases of Superficial Veins in Legs by Novel Non-Contrast MR with QFlow Technique

Objectives: To find an objective diagnostic tool for the superficial veins in legs. Methods: This study included 137 patients who underwent TRANCE-MRI from 2017 to 2020 (IRB: 202001570B0). Among them, 53 with unilateral leg venous diseases underwent a QFlow scan and were classified into the reflux and non-reflux groups according to the status of the great saphenous veins. Results: The QFlow, namely stroke volume (SV), forward flow volume (FFV), mean flux (MF), stroke distance (SD), and mean velocity (MV) measured in the external iliac, femoral, popliteal, and great saphenous vein (GSV). The SV, FFV, SD, MF, SD, and MV in the GSV (morbid/non-morbid limbs) demonstrated a favorable ability to discriminate reflux from non-reflux in the ROC curve. The SD in the GSV and GSV/PV ratio (p = 0.049 and 0.047/cutoff = 86 and 117.1) and the MV in the EIV/FV ratio, GSV, and GSV/PV ratio (p = 0.035, 0.034, and 0.025/cutoff = 100.9, 86.1, and 122.9) exhibited the ability to discriminate between reflux and non-reflux group. The SD, MV, and FFV have better ability to discriminate a reflux from non-reflux group than the SV and MF. Conclusions: QFlow may be used to verify the reflux of superficial veins in the legs. An increasing GSV/PV ratio is a hallmark of reflux of superficial veins in the legs.