Prediction of prostate cancer grade using fractal analysis of perfusion MRI: retrospective proof-of-principle study

Correlation between left atrial appendage morphology based on fractal dimension quantification and its hemodynamic parameters in patients with atrial fibrillation

AIMS

To investigate the relationship between left atrial appendage (LAA) morphology, quantified based on fractal dimension (FD), and LAA hemodynamic parameters in patients with atrial fibrillation (AF), in an effort to reveal the effect of LAA shape on blood flow.

MATERIALS AND METHODS

225 patients with AF who underwent cardiac computed tomography angiography (CTA) and transesophageal echocardiography (TEE) were enrolled. LAA morphology was quantified based on FD on cardiac CTA images, and LAA hemodynamic parameters, including injection fraction (EF), filling peak flow velocity (FV), maximum speed of emptying (PEV), and wall motion velocity (WMV), were assessed using TEE.

RESULTS

We divided the patients with AF into two groups based on a mean LAA FD of 1.32: the low FD group (n=124) and the high FD group (n=101). Compared to the low FD group, there were more patients with LAA circulatory stasis/thrombus (P=0.008) in the high FD group, as well as lower LAA FV (P=0.004), LAA PEV (P=0.007), and LAA WMV (P=0.007). LAA FD was an independent and significant determinant of LAA EF (β = -11.755, P=0.001), LAA FV (β = -17.364, P=0.004), LAA PEV (β = -18.743, P<0.001), and LAA WMV (β = -7.740, P=0.001) in multiple linear regression analysis.

CONCLUSIONS

LAA FD is an essential determinant of LAA hemodynamic parameters, suggesting that the relatively complex morphology of the LAA may influence its hemodynamics, which can correlate with embolic events.

Prostate Cancer Microvascular Routes: Exploration and Measurement Strategies

Angiogenesis is acknowledged as a pivotal feature in the pathology of human cancer. Despite the absence of universally accepted markers for gauging the comprehensive angiogenic activity in prostate cancer (PCa) that could steer the formulation of focused anti-angiogenic treatments, the scrutiny of diverse facets of tumoral blood vessel development may furnish significant understanding of angiogenic processes. Malignant neoplasms, encompassing PCa, deploy a myriad of strategies to secure an adequate blood supply. These modalities range from sprouting angiogenesis and vasculogenesis to intussusceptive angiogenesis, vascular co-option, the formation of mosaic vessels, vasculogenic mimicry, the conversion of cancer stem-like cells into tumor endothelial cells, and vascular pruning. Here we provide a thorough review of these angiogenic mechanisms as they relate to PCa, discuss their prospective relevance for predictive and prognostic evaluations, and outline the prevailing obstacles in quantitatively evaluating neovascularization via histopathological examinations.

MRI Assessment of Changes in Tumor Vascularization during Neoadjuvant Anti-Angiogenic Treatment in Locally Advanced Breast Cancer Patients

Anti-VEGF (vascular endothelial growth factor) treatment improves response rates, but not progression-free or overall survival in advanced breast cancer. It has been suggested that subgroups of patients may benefit from this treatment; however, the effects of adding anti-VEGF treatment to a standard chemotherapy regimen in breast cancer patients are not well studied. Understanding the effects of the anti-vascular treatment on tumor vasculature may provide a selection of patients that can benefit. The aim of this study was to study the vascular effect of bevacizumab using clinical dynamic contrast-enhanced MRI (DCE-MRI). A total of 70 women were randomized to receive either chemotherapy alone or chemotherapy with bevacizumab for 25 weeks. DCE-MRI was performed at baseline and at 12 and 25 weeks, and in addition 25 of 70 patients agreed to participate in an early MRI after one week. Voxel-wise pharmacokinetic analysis was performed using semi-quantitative methods and the extended Tofts model. Vascular architecture was assessed by calculating the fractal dimension of the contrast-enhanced images. Changes during treatment were compared with baseline and between the treatment groups. There was no significant difference in tumor volume at any point; however, DCE-MRI parameters revealed differences in vascular function and vessel architecture. Adding bevacizumab to chemotherapy led to a pronounced reduction in vascular DCE-MRI parameters, indicating decreased vascularity. At 12 and 25 weeks, the difference between the treatment groups is severely reduced.

Can the Gleason score be predicted in patients with prostate cancer? A dynamic contrast-enhanced MRI, (68)Ga-PSMA PET/CT, PSA, and PSA-density comparison study

PURPOSE

The present study aims to evaluate whether perfusion parameters in prostate magnetic resonance imaging (MRI), (68)Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT), prostate-specific antigen (PSA), and PSA density can be used to predict the lesion grade in patients with prostate cancer (PCa).

METHODS

The study included a total of 137 PCa cases in which 12-quadrant transrectal ultrasound-guided prostate biopsy (TRUSBx) was performed, the Gleason score (GS) was determined, and pre-biopsy multiparametric prostate MRI and (68)Ga-PSMA PET/CT examinations were undertaken. The patient population was evaluated in three groups according to the GS: (1) low risk; (2) intermediate risk; (3) high risk. The PSA, PSA density, pre-TRUSBx (68)Ga-PSMA PET/CT maximum standardized uptake value (SUVmax), perfusion MRI parameters [maximum enhancement, maximum relative enhancement, T0 (s), time to peak (s), wash-in rate (s-1), and wash-out rate (s-1)] were retrospectively evaluated.

RESULTS

There was no significant difference between the three groups in relation to the PSA, PSA density, and (68)Ga-PSMA PET/CT SUVmax (P > 0.05). However, the values of maximum enhancement, maximum relative enhancement (%), T0 (s), time to peak (s), wash-in rate (s-1), and wash-out rate (s-1) significantly differed among the groups. A moderate positive correlation was found among the prostate volume, PSA (r = 0.490), and (68)Ga-PSMA SUVmax (r = 0.322) in the patients. The wash-out rate (s-1) and wash-in rate (s-1) had the best diagnostic test performance (area under the curve: 89.1% and 78.4%, respectively).

CONCLUSION

No significant correlation was found between the (68)Ga-PSMA PET/CT SUVmax and the GS. The wash-out rate was more successful in estimating the pretreatment GS than the (68)Ga-PSMA PET/CT SUVmax.

The Fractal Viewpoint of Tumors and Nanoparticles

Even though the promising therapies against cancer are rapidly improved, the oncology patients population has seen exponential growth, placing cancer in 5th place among the ten deadliest diseases. Efficient drug delivery systems must overcome multiple barriers and maximize drug delivery to the target tumors, simultaneously limiting side effects. Since the first observation of the quantum tunneling phenomenon, many multidisciplinary studies have offered quantum-inspired solutions to optimized tumor mapping and efficient nanodrug design. The property of a wave function to propagate through a potential barrier offer the capability of obtaining 3D surface profiles using imaging of individual atoms on the surface of a material. The application of quantum tunneling on a scanning tunneling microscope offers an exact surface roughness mapping of tumors and pharmaceutical particles. Critical elements to cancer nanotherapeutics apply the fractal theory and calculate the fractal dimension for efficient tumor surface imaging at the atomic level. This review study presents the latest biological approaches to cancer management based on fractal geometry.

Differentiation of hepatocellular adenoma by subtype and hepatocellular carcinoma in non-cirrhotic liver by fractal analysis of perfusion MRI

Background

To investigate whether fractal analysis of perfusion differentiates hepatocellular adenoma (HCA) subtypes and hepatocellular carcinoma (HCC) in non-cirrhotic liver by quantifying perfusion chaos using four-dimensional dynamic contrast-enhanced magnetic resonance imaging (4D-DCE-MRI).

Results

A retrospective population of 63 patients (47 female) with histopathologically characterized HCA and HCC in non-cirrhotic livers was investigated. Our population consisted of 13 hepatocyte nuclear factor (HNF)-1α-inactivated (H-HCAs), 7 β-catenin-exon-3-mutated (b^ex3-HCAs), 27 inflammatory HCAs (I-HCAs), and 16 HCCs. Four-dimensional fractal analysis was applied to arterial, portal venous, and delayed phases of 4D-DCE-MRI and was performed in lesions as well as remote liver tissue. Diagnostic accuracy of fractal analysis was compared to qualitative MRI features alone and their combination using multi-class diagnostic accuracy testing including kappa-statistics and area under the receiver operating characteristic curve (AUC). Fractal analysis allowed quantification of perfusion chaos, which was significantly different between lesion subtypes (multi-class AUC = 0.90, p < 0.001), except between I-HCA and HCC. Qualitative MRI features alone did not allow reliable differentiation between HCA subtypes and HCC (κ = 0.35). However, combining qualitative MRI features and fractal analysis reliably predicted the histopathological diagnosis (κ = 0.89) and improved differentiation of high-risk lesions (i.e., HCCs, b^ex3-HCAs) and low-risk lesions (H-HCAs, I-HCAs) from sensitivity and specificity of 43% (95% confidence interval [CI] 23–66%) and 47% (CI 32–64%) for qualitative MRI features to 96% (CI 78–100%) and 68% (CI 51–81%), respectively, when adding fractal analysis.

Conclusions

Combining qualitative MRI features with fractal analysis allows identification of HCA subtypes and HCCs in patients with non-cirrhotic livers and improves differentiation of lesions with high and low risk for malignant transformation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01223-6.

Fractal analysis of perfusion imaging in synovitis: a novel imaging biomarker for grading inflammatory activity based on assessing angiogenesis

Objectives

The mutual and intertwined dependence of inflammation and angiogenesis in synovitis is widely acknowledged. However, no clinically established tool for objective and quantitative assessment of angiogenesis is routinely available. This study establishes fractal analysis as a novel method to quantitatively assess inflammatory activity based on angiogenesis in synovitis.

Methods

First, we established a pathophysiological framework for synovitis including fractal analysis of software perfusion phantoms, which allowed to derive explainability with a known and controllable reference standard for vascular structure. Second, we acquired MRI datasets of patients with suspected rheumatoid arthritis of the hand, and three imaging experts independently assessed synovitis analogue to Rheumatoid Arthritis MRI Scoring (RAMRIS) criteria. Finally, we performed fractal analysis of dynamic first-pass perfusion MRI in vivo to evaluate angiogenesis in relation to inflammatory activity with RAMRIS as reference standard.

Results

Fractal dimension (FD) achieved highly significant discriminability for different degrees of inflammatory activity (p<0.01) in software phantoms with known ground-truth of angiogenic structure. FD indicated increasingly chaotic perfusion patterns with increasing grades of inflammatory activity (Spearman’s ρ=0.94, p<0.001). In 36 clinical patients, fractal analysis quantitatively and objectively discriminated individual RAMRIS scores (p≤0.05). Area under the receiver-operating curve was 0.84 (95% CI 0.7 to 0.89) for fractal analysis when considering RAMRIS as ground-truth. Fractal analysis additionally identified angiogenesis in cases where RAMRIS underestimated inflammatory activity.

Conclusions

Based on angiogenesis and perfusion pathophysiology, fractal analysis non-invasively enables comprehensive, objective and quantitative characterisation of inflammatory angiogenesis with subjective and qualitative RAMRIS as reference standard. Further studies are required to establish the clinical value of fractal analysis for diagnosis, prognostication and therapy monitoring in inflammatory arthritis.

Accuracy of fractal analysis and PI-RADS assessment of prostate magnetic resonance imaging for prediction of cancer grade groups: a clinical validation study

Objectives

Multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) assessment is sensitive but not specific for detecting clinically significant prostate cancer. This study validates the diagnostic accuracy of the recently suggested fractal dimension (FD) of perfusion for detecting clinically significant cancer.

Materials and methods

Routine clinical MR imaging data, acquired at 3 T without an endorectal coil including dynamic contrast-enhanced sequences, of 72 prostate cancer foci in 64 patients were analyzed. In-bore MRI-guided biopsy with International Society of Urological Pathology (ISUP) grading served as reference standard. Previously established FD cutoffs for predicting tumor grade were compared to measurements of the apparent diffusion coefficient (25th percentile, ADC₂₅) and PI-RADS assessment with and without inclusion of the FD as separate criterion.

Results

Fractal analysis allowed prediction of ISUP grade groups 1 to 4 but not 5, with high agreement to the reference standard (κ_FD = 0.88 [CI: 0.79–0.98]). Integrating fractal analysis into PI-RADS allowed a strong improvement in specificity and overall accuracy while maintaining high sensitivity for significant cancer detection (ISUP > 1; PI-RADS alone: sensitivity = 96%, specificity = 20%, area under the receiver operating curve [AUC] = 0.65; versus PI-RADS with fractal analysis: sensitivity = 95%, specificity = 88%, AUC = 0.92, p < 0.001). ADC₂₅ only differentiated low-grade group 1 from pooled higher-grade groups 2–5 (κ_ADC = 0.36 [CI: 0.12–0.59]). Importantly, fractal analysis was significantly more reliable than ADC₂₅ in predicting non-significant and clinically significant cancer (AUC_FD = 0.96 versus AUC_ADC = 0.75, p < 0.001). Diagnostic accuracy was not significantly affected by zone location.

Conclusions

Fractal analysis is accurate in noninvasively predicting tumor grades in prostate cancer and adds independent information when implemented into PI-RADS assessment. This opens the opportunity to individually adjust biopsy priority and method in individual patients.

Key Points

• Fractal analysis of perfusion is accurate in noninvasively predicting tumor grades in prostate cancer using dynamic contrast-enhanced sequences (κ_FD = 0.88).

• Including the fractal dimension into PI-RADS as a separate criterion improved specificity (from 20 to 88%) and overall accuracy (AUC from 0.86 to 0.96) while maintaining high sensitivity (96% versus 95%) for predicting clinically significant cancer.

• Fractal analysis was significantly more reliable than ADC₂₅ in predicting clinically significant cancer (AUC_FD = 0.96 versus AUC_ADC = 0.75).