Perfusion-Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver

Introduction. In order to improve the efficacy of intravoxel incoherent motion (IVIM) parameters in characterising specific tissues, a new concept is introduced: the perfusion–diffusion ratio (PDR), which expresses the relationship between the signal S b decline rate as a result of IVIM and the rate of signal S b decline due to diffusion. The aim of this study was to investigate this novel approach in the differentiation of solid primary liver lesions. Material and Methods. Eighty-three patients referred for liver MRI between August 2017 and January 2020 with a suspected liver tumour were prospectively examined with the standard liver MRI protocol extended by DWI-IVIM sequence. Patients with no liver lesions, haemangiomas, or metastases were excluded. The final study population consisted of 34 patients with primary solid liver masses, 9 with FNH, 4 with regenerative nodules, 10 with HCC, and 11 with CCC. The PDR coefficient was introduced, defined as the ratio of the rate of signal S b decrease due to the IVIM effect to the rate of signal S b decrease due to the diffusion process, for b = 0 . Results. No significant differences were found between benign and malignant lesions in the case of IVIM parameters ( f , D , or D ∗ ) and ADC. Significant differences were observed only for PDR, with lower values for malignant lesions ( p = 0.03 ). The ROC analysis yielded an AUC value for PDR equal to 0.74, with a cut-off value of 5.06, sensitivity of 81%, specificity of 77%, and accuracy of 79%. Conclusion. PDR proved to be more effective than IVIM parameters and ADC in the differentiation of solid benign and malignant primary liver lesions.

Follow-up Strategies in Focal Liver Lesions and Treatment Methods

Today, advances in cross-sectional imaging have led to the detection and early recognition of incidental/focal liver lesions (FCL). In approximately 17,000 cases of chest CT, incidental liver lesions were found in 6% [1]. In general, FCL consists of hepatocytes, biliary epithelium, mesenchymal tissue, connective tissue, or metastasized cells from distant sites. Most incidental lesions are benign, some may require careful management and treatment. In evaluating the lesion, the patient's clinical history, underlying disease and age factor should be considered. FCL can be detected at a rate of 10-30% in normal healthy and chronic liver disease patients, and even in oncology patients with malignancy, FCLs can be highly benign (50-80%)

Laparoscopic Liver Resection: Surgical Techniques

Laparoscopic liver resection has evolved from a technique to remove small anterior liver lesions with smaller incisions to a major method for the performance of almost every type of liver resection.

Can optimized model-based iterative reconstruction improve the contrast of liver lesions in CT?

Background Computed tomography is a standard imaging procedure for the detection of liver lesions, such as metastases, which can often be small and poorly contrasted, and therefore hard to detect. Advances in image reconstruction have shown promise in reducing image noise and improving low-contrast detectability. Purpose To examine a novel, specialized, model-based iterative reconstruction (MBIR) technique for improved low-contrast liver lesion detection. Material and Methods Patient images with reported poorly contrasted focal liver lesions were retrospectively reconstructed with the low-contrast attenuating algorithm (FIRST-LCD) from primary raw data. Liver-to-lesion contrast, signal-to-noise, and contrast-to-noise ratios for background and liver noise for each lesion were compared for all three FIRST-LCD presets with the established hybrid iterative reconstruction method (AIDR-3D). An additional visual conspicuity score was given by two experienced radiologists for each lesion. Results A total of 82 lesions in 57 examinations were included in the analysis. All three FIRST-LCD algorithms provided statistically significant increases in liver-to-lesion contrast, with FIRSTMILD showing the largest increase (40.47 HU in AIDR-3D; 45.84 HU in FIRSTMILD; P < 0.001). Substantial improvement was shown in contrast-to-noise metrics. Visual analysis of the lesions shows decreased lesion visibility with all FIRST methods in comparison to AIDR-3D, with FIRSTSTR showing the closest results ( P < 0.001). Conclusion Objective image metrics show promise for MBIR methods in improving the detectability of low-contrast liver lesions; however, subjective image quality may be perceived as inferior. Further improvements are necessary to enhance image quality and lesion detection.