Spatiotemporal heterogeneity of tumor vasculature during tumor growth and antiangiogenic treatment: MRI assessment using permeability and blood volume parameters

Voxel-wise mapping of DCE-MRI time-intensity-curve profiles enables visualizing and quantifying hemodynamic heterogeneity in breast lesions

OBJECTIVES

To propose a novel model-free data-driven approach based on the voxel-wise mapping of DCE-MRI time-intensity-curve (TIC) profiles for quantifying and visualizing hemodynamic heterogeneity and to validate its potential clinical applications.

MATERIALS AND METHODS

From December 2018 to July 2022, 259 patients with 325 pathologically confirmed breast lesions who underwent breast DCE-MRI were retrospectively enrolled. Based on the manually segmented breast lesions, the TIC of each voxel within the 3D whole lesion was classified into 19 subtypes based on wash-in rate (nonenhanced, slow, medium, and fast), wash-out enhancement (persistent, plateau, and decline), and wash-out stability (steady and unsteady), and the composition ratio of these 19 subtypes for each lesion was calculated as a new feature set (type-19). The three-type TIC classification, semiquantitative parameters, and type-19 features were used to build machine learning models for identifying lesion malignancy and classifying histologic grades, proliferation status, and molecular subtypes.

RESULTS

The type-19 feature-based model significantly outperformed models based on the three-type TIC method and semiquantitative parameters both in distinguishing lesion malignancy (respectively; AUC = 0.875 vs. 0.831, p = 0.01 and 0.875vs. 0.804, p = 0.03), predicting tumor proliferation status (AUC = 0.890 vs. 0.548, p = 0.006 and 0.890 vs. 0.596, p = 0.020), but not in predicting histologic grades (p = 0.820 and 0.970).

CONCLUSION

In addition to conventional methods, the proposed computational approach provides a novel, model-free, data-driven approach to quantify and visualize hemodynamic heterogeneity.

CLINICAL RELEVANCE STATEMENT

Voxel-wise intra-lesion mapping of TIC profiles allows for visualization of hemodynamic heterogeneity and its composition ratio for differentiation of malignant and benign breast lesions.

KEY POINTS

• Voxel-wise TIC profiles were mapped, and their composition ratio was compared between various breast lesions. • The model based on the composition ratio of voxel-wise TIC profiles significantly outperformed the three-type TIC classification model and the semiquantitative parameters model in lesion malignancy differentiation and tumor proliferation status prediction in breast lesions. • This novel, data-driven approach allows the intuitive visualization and quantification of the hemodynamic heterogeneity of breast lesions.

Assessing Tumor Microenvironment Characteristics and Stratifying EPR with a Nanobubble Companion Nanoparticle via Contrast-Enhanced Ultrasound Imaging

The tumor microenvironment is characterized by dysfunctional endothelial cells, resulting in heightened vascular permeability. Many nanoparticle-based drug delivery systems attempt to use this enhanced permeability combined with impaired lymphatic drainage (a concept known as the 'enhanced permeability and retention effect' or EPR effect) as the primary strategy for drug delivery, but this has not proven to be as clinically effective as anticipated. The specific mechanisms behind the inconsistent clinical outcomes of nanotherapeutics have not been clearly articulated, and the field has been hampered by a lack of accessible tools to study EPR-associated phenomena in clinically relevant scenarios. While medical imaging has tremendous potential to contribute to this area, it has not been broadly explored. This work examines, for the first time, the use of multiparametric dynamic contrast-enhanced ultrasound (CEUS) with a novel nanoscale contrast agent to examine tumor microenvironment characteristics noninvasively and in real-time. We demonstrate that CEUS imaging can: (1) evaluate tumor microenvironment features and (2) be used to help predict the distribution of doxorubicin-loaded liposomes in the tumor parenchyma. CEUS using nanobubbles (NBs) was carried out in two tumor types of high (LS174T) and low (U87) vascular permeability, and time-intensity curve (TIC) parameters were evaluated in both models prior to injection of doxorubicin liposomes. Consistently, LS174T tumors showed significantly different TIC parameters, including area under the rising curve (2.7x), time to peak intensity (1.9x) and decorrelation time (DT, 1.9x) compared to U87 tumors. Importantly, the DT parameter successfully predicted tumoral nanoparticle distribution (r = 0.86 ± 0.13). Ultimately, substantial differences in NB-CEUS generated parameters between LS174T and U87 tumors suggest that this method may be useful in determining tumor vascular permeability and could be used as a biomarker for identifying tumor characteristics and predicting sensitivity to nanoparticle-based therapies. These findings could ultimately be applied to predicting treatment efficacy and to evaluating EPR in other diseases with pathologically permeable vasculature.

The assessment of pathological response to neoadjuvant chemotherapy in muscle-invasive bladder cancer patients with DCE-MRI and DWI: a systematic review and meta-analysis

OBJECTIVE

The purpose of this meta-analysis was to determine the value of dynamic contrast-enhanced-MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in evaluating the pathological response of muscle invasive bladder cancer (MIBC) to neoadjuvant chemotherapy (NAC), and further indirectly compare the diagnostic performance of DCE-MRI and DWI.

METHODS

Literatures associated to DCE-MRI and DWI in the evaluation of pathological response of MIBC to NAC were searched from PubMed, Cochrane Library, web of science, and EMBASE databases. The quality assessment of diagnostic accuracy studies 2 tool was used to assess the quality of studies. Pooled sensitivity (SE), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curves (AUC) with their 95% confidence intervals (CIs) were calculated to evaluate the diagnostic performance of DCE-MRI and DWI in predicting the pathological response to NAC in patients with MIBC.

RESULTS

There were 11 studies involved, 6 of which only underwent DCE- MRI examination, 4 of which only underwent DWI examination, and 1 of which underwent both DCE- MRI and DWI examination. The pooled SE, SP, PLR, NLR, DOR of DCE-MRI were 0.88 (95% CI: 0.78-0.93), 0.88 (95% CI: 0.67-0.96), 7.4 (95% CI: 2.3-24.2), 0.14 (95% CI: 0.07-0.27), and 53 (95% CI: 10-288), respectively. The pooled SE, SP, PLR, NLR, DOR of DWI were 0.83 (95% CI: 0.75-0.88), 0.88 (95% CI: 0.81-0.93), 7.1 (95% CI: 4.3-11.7), 0.20 (95% CI: 0.14-0.28), and 36 (95% CI:18-73), respectively. The AUCs of SROC curve for DCE-MRI and DWI were 0.93 (95% CI: 0.91-0.95) and 0.92 (95% CI: 0.89-0.94), respectively. There were no significant differences between DWI and DCE-MRI for SE, SP, and AUC.

CONCLUSION

This meta-analysis demonstrated high diagnostic performance of both DCE-MRI and DWI in predicting the pathological response to NAC in MIBC. DWI might be a potential substitute for DCE-MRI, with no significant difference in diagnostic performance between the two. However, caution should be taken when applying our results, as our results were based on indirect comparison.

ADVANCES IN KNOWLEDGE

No previous studies have comprehensively analysed the value of DCE-MRI and DWI in evaluating the pathological response to NAC in MIBC. According to the current study, both DCE-MRI and DWI yielded high diagnostic performance, with the AUCs of 0.93 and 0.92, respectively. Indirect comparison no significant difference in the diagnostic performanceof DCE-MRI and DWI.

Multi-ligand functionalized blood-to-tumor sequential targeting strategies in the field of glioblastoma nanomedicine

Glioblastoma (GBM) is an unmet clinical need characterized by a standard of care (SOC) 5-year survival rate of only 5%, and a treatment mostly palliative. Significant hurdles in GBM therapies include an effective penetration of therapeutics through the brain protective barrier, namely the blood-brain barrier (BBB), and a successful therapeutic delivery to brain-invading tumor cells post-BBB crossing. These hurdles, along with the poor prognosis and critical heterogeneity of the disease, have shifted attention to treatment modalities with capacity to precisely and sequentially target (i) BBB cells, inducing blood-to-brain transport, and (ii) GBM cells, leading to a higher therapeutic accumulation at the tumor site. This sequential targeting allows therapeutic molecules to reach the brain parenchyma and compromise molecular processes that support tumor cell invasion. Besides improving formulation and pharmacokinetics constraints of drugs, nanomedicines offer the possibility of being surface functionalized with multiple possibilities of targeting ligands, while delivering the desired therapeutic cargos to the biological sites of interest. Targeting ligands exploit the site-specific expression or overexpression of specific molecules on BBB and GBM cells, triggering brain plus tumor transport. Since the efficacy of single-ligand functionalized nanomedicines is limited due to the GBM anatomical site (brain) and disease complexity, this review presents an overview of multi-ligand functionalized, BBB and GBM sequentially- and dual-targeted nanomedicines reported in literature over the last 10 years. The role of the BBB in GBM progression, treatment options, and the multiple possibilities of currently available targeting ligands will be summarized. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Ultra-small micelles together with UTMD enhanced the therapeutic effect of docetaxel on Glioblastoma

Owing to the difficult-to-penetrate blood-brain barrier (BBB), glioblastoma (GBM) doesn't respond well to the current chemical therapeutics. In this study, ultra-small micelles (NMs) self-assembled by RRR-a-tocopheryl succinate-grafted-ε-polylysine conjugate (VES-g-ε-PLL) as the delivery vehicle of chemical therapeutics in conjunction with ultrasound-targeted microbubble destruction (UTMD) to surmount BBB and treat GBM. Docetaxel (DTX) as a hydrophobic model drug was incorporated into NMs. DTX-loaded micelles (DTX-NMs) with 3.08% of drug loading exhibited a hydrodynamic diameter (33.2 nm) and positive Zeta potential (16.9 mV), having a remarkable tumor-permeating capacity. Furthermore, DTX-NMs presented good stability in physiologic condition. The sustained-release release profile of DTX-NMs was also displayed by dynamic dialysis. Treatment of DTX-NMs together with UTMD led to more pronounced apoptosis of C6 tumor cells than DTX-NMs alone. Moreover, compared with the DTX solution or DTX-NMs alone, the combination of DTX-NMs with UTMD had a stronger inhibitory effect on tumor growth for GBM-bearing rats. The median survival period of GBM-bearing rats was extended to 75 days in the DTX-NMs+UTMD group from under 25 days in the control group. The invasive growth of glioblastoma was largely inhibited by the combination of DTX-NMs with UTMD, which was demonstrated by staining of Ki67, caspase-3, and CD31, together with TUNEL assay. In conclusion, the combination of ultra-small micelles (NMs) with UTMD may be a promising strategy to overcome the limitations of the first-line chemotherapeutics against GBM.

Nondestructive protein sampling with electroporation facilitates profiling of spatial differential protein expression in breast tumors in vivo

Excision tissue biopsy, while central to cancer treatment and precision medicine, presents risks to the patient and does not provide a sufficiently broad and faithful representation of the heterogeneity of solid tumors. Here we introduce e-biopsy—a novel concept for molecular profiling of solid tumors using molecular sampling with electroporation. As e-biopsy provides access to the molecular composition of a solid tumor by permeabilization of the cell membrane, it facilitates tumor diagnostics without tissue resection. Furthermore, thanks to its non tissue destructive characteristics, e-biopsy enables probing the solid tumor multiple times in several distinct locations in the same procedure, thereby enabling the spatial profiling of tumor molecular heterogeneity.We demonstrate e-biopsy in vivo, using the 4T1 breast cancer model in mice to assess its performance, as well as the inferred spatial differential protein expression. In particular, we show that proteomic profiles obtained via e-biopsy in vivo distinguish the tumors from healthy breast tissue and reflect spatial tumor differential protein expression. E-biopsy provides a completely new molecular sampling modality for solid tumors molecular cartography, providing information that potentially enables more rapid and sensitive detection at lesser risk, as well as more precise personalized medicine.

Artificial Intelligence Algorithm in Classification and Recognition of Primary Hepatic Carcinoma Images under Magnetic Resonance Imaging

This study aimed to discuss the application value of the bias field correction algorithm in magnetic resonance imaging (MRI) images of patients with primary hepatic carcinoma (PHC). In total, 52 patients with PHC were selected as the experimental group and divided into three subgroups: mild (15 cases), moderate (19 cases), and severe (18 cases) according to pathological grading. Another 52 patients with hepatic nodules in the same period were included in the control group. All the patients underwent dynamic contrast-enhanced (DCE) MRI examination, and the image qualities of MRI before and after bias field correction were compared. The DCE-MRI perfusion parameters were measured, including the transport constant Ktrans, reverse rate constant Kep, extravascular extracellular volume fraction (Ve), plasma volume (Vp), microvascular density (MVD), hepatic artery perfusion index (HPI), mean transit time of contrast agent (MTT), time to peak (TTP), blood volume (BV), hepatic arterial perfusion (HAP), full perfusion (FP), and portal venous perfusion (PVP). It was found that the sensitivity (93.63%), specificity (71.62%), positive predictive value (95.63%), negative predictive value (71.62%), and accuracy (90.01%) of MRI examination processed by the bias field correction algorithm were all significantly greater than those before processing (P < 0.05). The Ktrans, Kep, Ve, Vp, and MVD of patients in the experimental group were significantly larger than those of the control group, and severe group> moderate group> mild group (P < 0.05). HPI, MTT, TTP, BV, and HAP of patients in the experimental group were also significantly greater than those of the control group, which was shown as severe group > moderate group > mild group (P < 0.05). FP and PVP of the experimental group were significantly lower than those of the control group, and severe group < moderate group < mild group (P < 0.05). It was suggested that in MRI images of patients with PHC, the bias field correction algorithm could significantly improve the diagnosis rate. Each perfusion parameter was related to the pathological grading, which could be used to evaluate the prognosis of patients.

Nanomedicine for brain cancer

CNS tumors remain among the deadliest forms of cancer, resisting conventional and new treatment approaches, with mortality rates staying practically unchanged over the past 30 years. One of the primary hurdles for treating these cancers is delivering drugs to the brain tumor site in therapeutic concentration, evading the blood-brain (tumor) barrier (BBB/BBTB). Supramolecular nanomedicines (NMs) are increasingly demonstrating noteworthy prospects for addressing these challenges utilizing their unique characteristics, such as improving the bioavailability of the payloadsviacontrolled pharmacokinetics and pharmacodynamics, BBB/BBTB crossing functions, superior distribution in the brain tumor site, and tumor-specific drug activation profiles. Here, we review NM-based brain tumor targeting approaches to demonstrate their applicability and translation potential from different perspectives. To this end, we provide a general overview of brain tumor and their treatments, the incidence of the BBB and BBTB, and their role on NM targeting, as well as the potential of NMs for promoting superior therapeutic effects. Additionally, we discuss critical issues of NMs and their clinical trials, aiming to bolster the potential clinical applications of NMs in treating these life-threatening diseases.

Spatiotemporal heterogeneity of tumor vasculature during tumor growth and antiangiogenic treatment: MRI assessment using permeability and blood volume parameters

Tumor heterogeneity is an important concept when assessing intratumoral variety in vascular phenotypes and responses to antiangiogenic treatment. This study explored spatiotemporal heterogeneity of vascular alterations in C6 glioma mice during tumor growth and antiangiogenic treatment on serial MR examinations (days 0, 4, and 7 from initiation of vehicle or multireceptor tyrosine kinase inhibitor administration). Transvascular permeability (TP) was quantified on dynamic‐contrast‐enhanced MRI (DCE‐MRI) using extravascular extracellular agent (Gd‐DOTA); blood volume (BV) was estimated using intravascular T₂ agent (SPION). With regard to region‐dependent variability in vascular phenotypes, the control group demonstrated higher TP in the tumor center than in the periphery, and greater BV in the tumor periphery than in the center. This distribution pattern became more apparent with tumor growth. Antiangiogenic treatment effect was regionally heterogeneous: in the tumor center, treatment significantly suppressed the increase in TP and decrease in BV (ie, typical temporal change in the control group); in the tumor periphery, treatment‐induced vascular alterations were insignificant and BV remained high. On histopathological examination, the control group showed greater CD31, VEGFR2, Ki67, and NG2 expression in the tumor periphery than in the center. After treatment, CD31 and Ki67 expression was significantly suppressed only in the tumor center, whereas VEGFR2 and α‐caspase 3 expression was decreased and NG2 expression was increased in the entire tumor. These results demonstrate that MRI can reliably depict spatial heterogeneity in tumor vascular phenotypes and antiangiogenic treatment effects. Preserved angiogenic activity (high BV on MRI and high CD31) and proliferation (high Ki67) in the tumor periphery after treatment may provide insights into the mechanism of tumor resistance to antiangiogenic treatment.