T1 mapping as a surrogate marker of chemotherapy response evaluation in patients with osteosarcoma

Imaging Assessment of the Efficacy of Chemotherapy in Primary Malignant Bone Tumors: Recent Advances in Qualitative and Quantitative Magnetic Resonance Imaging and Radiomics

Recent studies have shown that MRI demonstrates promising results for evaluating the chemotherapy efficacy in bone sarcomas. This article reviews current methods for evaluating the efficacy of malignant bone tumors and the application of MRI in this area, and emphasizes the advantages and limitations of each modality. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Intratumoral heterogeneity after targeted therapy in murine cancer models with differing degrees of malignancy

INTRODUCTION

Conventional morphologic and volumetric assessment of treatment response is not suitable for adequately assessing responses to targeted cancer therapy. The aim of this study was to evaluate changes in tumor composition after targeted therapy in murine models of breast cancer with differing degrees of malignancy via non-invasive magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Mice bearing highly malignant 4T1 tumors or low malignant 67NR tumors were treated with either a combination of two immune checkpoint inhibitors (ICI, anti-PD1 and anti-CTLA-4) or the multi-tyrosine kinase inhibitor sorafenib, following experiments with macrophage-depleting clodronate-loaded liposomes and vessel-stabilizing angiopoietin-1. Mice were imaged on a 9.4 T small animal MRI system with a multiparametric (mp) protocol, comprising T1 and T2 mapping and diffusion-weighted imaging. Tumors were analyzed ex vivo with histology.

RESULTS AND DISCUSSIONS

All treatments led to an increase in non-viable areas, but therapy-induced intratumoral changes differed between the two tumor models and the different targeted treatments. While ICI treatment led to intratumoral hemorrhage, sorafenib treatment mainly induced intratumoral necrosis. Treated 4T1 tumors showed increasing and extensive areas of necrosis, in comparison to 67NR tumors with only small, but also increasing, necrotic areas. After either of the applied treatments, intratumoral heterogeneity, was increased in both tumor models, and confirmed ex vivo by histology. Apparent diffusion coefficient with subsequent histogram analysis proved to be the most sensitive MRI sequence. In conclusion, mp MRI enables to assess dedicated therapy-related intratumoral changes and may serve as a biomarker for treatment response assessment.

T1 mapping and extracellular volume fraction measurement to evaluate the poor-prognosis factors in patients with cervical squamous cell carcinoma

PURPOSE

To evaluate the clinical feasibility of T₁ mapping and extracellular volume fraction (ECV) measurement in assessing prognostic factors in patients with cervical squamous cell carcinoma (CSCC).

MATERIALS AND METHODS

A total of 117 CSCC patients and 59 healthy volunteers underwent T₁ mapping and diffusion-weighted imaging (DWI) on a 3 T system. Native T₁ , contrast-enhanced T₁ , ECV, and apparent diffusion coefficient (ADC) were calculated and compared based on surgico-pathologically verified deep stromal infiltration, parametrial invasion (PMI), lymphovascular space invasion (LVSI), lymph node metastasis, stage, histologic grade, and the Ki-67 labeling index (LI).

RESULTS

Native T₁ , contrast-enhanced T₁ , ECV, and ADC values were significantly different between CSCC and the normal cervix (all p < 0.05). No significant differences were observed in any parameters of CSCC when the tumors were grouped by stromal infiltration or lymph node status, respectively (all p > 0.05). In subgroups of the tumor stage and PMI, native T₁ was significantly higher for advanced-stage (p = 0.032) and PMI-positive CSCC (p = 0.001). In subgroups of the grade and Ki-67 LI, contrast-enhanced T₁ was significantly higher for high-grade (p = 0.012) and Ki-67 LI ≥ 50% tumors (p = 0.027). ECV was significantly higher in LVSI-positive CSCC than in LVSI-negative CSCC (p < 0.001). ADC values showed a significant difference for the grade (p < 0.001) but none for the other subgroups.

CONCLUSION

Both T₁ mapping and DWI could stratify the CSCC histologic grade. In addition, T₁ mapping and ECV measurement might provide more quantitative metrics for noninvasively predicting poor prognostic factors and aiding in preoperative risk assessment in CSCC patients.

An updated systematic review of radiomics in osteosarcoma: utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics

Objective

To update the systematic review of radiomics in osteosarcoma.

Methods

PubMed, Embase, Web of Science, China National Knowledge Infrastructure, and Wanfang Data were searched to identify articles on osteosarcoma radiomics until May 15, 2022. The studies were assessed by Radiomics Quality Score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, Checklist for Artificial Intelligence in Medical Imaging (CLAIM), and modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The evidence supporting radiomics application for osteosarcoma was rated according to meta-analysis results.

Results

Twenty-nine articles were included. The average of the ideal percentage of RQS, the TRIPOD adherence rate and the CLAIM adherence rate were 29.2%, 59.2%, and 63.7%, respectively. RQS identified a radiomics-specific issue of phantom study. TRIPOD addressed deficiency in blindness of assessment. CLAIM and TRIPOD both pointed out shortness in missing data handling and sample size or power calculation. CLAIM identified extra disadvantages in data de-identification and failure analysis. External validation and open science were emphasized by all the above three tools. The risk of bias and applicability concerns were mainly related to the index test. The meta-analysis of radiomics predicting neoadjuvant chemotherapy response by MRI presented a diagnostic odds ratio (95% confidence interval) of 28.83 (10.27–80.95) on testing datasets and was rated as weak evidence.

Conclusions

The quality of osteosarcoma radiomics studies is insufficient. More investigation is needed before using radiomics to optimize osteosarcoma treatment. CLAIM is recommended to guide the design and reporting of radiomics research.