Predictive value of DCE-MRI and IVIM-DWI in osteosarcoma patients with neoadjuvant chemotherapy

The presence of a fat layer after neoadjuvant chemotherapy as an indicator of prognosis in osteosarcoma

Objective

This study aimed to evaluate the potential of magnetic resonance imaging (MRI) to monitor the response in patients with osteosarcoma receiving chemotherapy and to assess the correlation between the presence of a fat layer surrounding the tumor after neoadjuvant chemotherapy and prognosis.

Methods

In total, 28 patients with osteosarcoma were included in this retrospective study. All patients underwent chemotherapy and surgery. MRI scans of the patients were evaluated before and after neoadjuvant chemotherapy. The prognostic factors included histological response and alkaline phosphatase (ALP) level. Relapse and survival at follow-up were defined as patient outcomes. The log-rank test was used to compare these factors with various MRI characteristics (e.g. change in maximum lesion length before and after chemotherapy, change in maximum edema, and fat layer presence after chemotherapy).

Results

The median time of follow-up was 64.3 ± 41.5 months. The 3- and 5-year event-free survival rates were 75.0% and 67.9%, respectively. ALP levels after chemotherapy were associated with tumor necrosis (p = 0.01). Change in maximum lesion length [p = 0.044; odds ratio (OR) = 0.035; confidence interval (CI): 0.01-0.911] was a predictor of survival. Changes in edema on T2-weighted sequences (p = 0.979; OR = 0.989, CI: 0.437-2.242) were not significant. The presence of a fat layer (p = 0.013; OR = 0.000; confidence CI: 0.000-0.018) predicted good event-free survival.

Conclusions

The presence of a fat layer correlated with good prognosis in patients with osteosarcoma. MRI characteristics in the early stages could help to inform decision-making about treatment strategy.

Intratumoral Heterogeneity Assessment of the Extracellular Bone Matrix and Immune Microenvironment in Osteosarcoma Using Digital Imaging to Predict Therapeutic Response

The assessment of chemotherapy response in osteosarcoma (OS) based on the average percentage of viable cells is limited, as it overlooks the spatial heterogeneity of tumor cell response (foci of resistant cells), immune microenvironment, and bone microarchitecture. Despite the resulting positive classification for response to chemotherapy, some patients experience early metastatic recurrence, demonstrating that our conventional tools for evaluating treatment response are insufficient. We studied the interactions between tumor cells, immune cells (lymphocytes, histiocytes, and osteoclasts), and bone extracellular matrix (ECM) in 18 surgical resection samples of OS using multiplex and conventional immunohistochemistry (IHC: CD8, CD163, CD68, and SATB2), combined with multiscale characterization approaches in territories of good and poor response (GRT/PRT) to treatment. GRT and PRT were defined as subregions with <10% and ≥10% of viable tumor cells, respectively. Local correlations between bone ECM porosity and density of immune cells were assessed in these territories. Immune cell density was then correlated to overall patient survival. Two patterns were identified for histiocytes and osteoclasts. In poor responder patients, CD68 osteoclast density exceeded that of CD163 histiocytes but was not related to bone ECM load. Conversely, in good responder patients, CD163 histiocytes were more numerous than CD68 osteoclasts. For both of them, a significant negative local correlation with bone ECM porosity was found (P < .01). Moreover, in PRT, multinucleated osteoclasts were rounded and intermingled with tumor cells, whereas in GRT, they were elongated and found in close contact with bone trabeculae. CD8 levels were always low in metastatic patients, and those initially considered good responders rapidly died from their disease. The specific recruitment of histiocytes and osteoclasts within the bone ECM, and the level of CD8 represent new features of OS response to treatment. The associated prognostic signatures should be integrated into the therapeutic stratification algorithm of patients after surgery.

Relative Wash-In Rate in Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a New Prognostic Biomarker for Event-Free Survival in 82 Patients with Osteosarcoma: A Multicenter Study

BACKGROUND

The decreased perfusion of osteosarcoma in dynamic contrast-enhanced (DCE) MRI, reflecting a good histological response to neoadjuvant chemotherapy, has been described.

PURPOSE

In this study, we aim to explore the potential of the relative wash-in rate as a prognostic factor for event-free survival (EFS).

METHODS

Skeletal high-grade osteosarcoma patients, treated in two tertiary referral centers between 2005 and 2022, were retrospectively included. The relative wash-in rate (rWIR) was determined with DCE-MRI before, after, or during the second cycle of chemotherapy (pre-resection). A previously determined cut-off was used to categorize patients, where rWIR < 2.3 was considered poor and rWIR ≥ 2.3 a good radiological response. EFS was defined as the time from resection to the first event: local recurrence, new metastases, or tumor-related death. EFS was estimated using Kaplan-Meier's methodology. Multivariate Cox proportional hazard model was used to estimate the effect of histological response and rWIR on EFS, adjusted for traditional prognostic factors.

RESULTS

Eighty-two patients (median age: 17 years; IQR: 14-28) were included. The median follow-up duration was 11.8 years (95% CI: 11.0-12.7). During follow-up, 33 events occurred. Poor histological response was not significantly associated with EFS (HR: 1.8; 95% CI: 0.9-3.8), whereas a poor radiological response was associated with a worse EFS (HR: 2.4; 95% CI: 1.1-5.0). In a subpopulation without initial metastases, the binary assessment of rWIR approached statistical significance (HR: 2.3; 95% CI: 1.0-5.2), whereas its continuous evaluation demonstrated a significant association between higher rWIR and improved EFS (HR: 0.7; 95% CI: 0.5-0.9), underlining the effect of response to chemotherapy. The 2- and 5-year EFS for patients with a rWIR ≥ 2.3 were 85% and 75% versus 55% and 50% for patients with a rWIR < 2.3.

CONCLUSION

The predicted poor chemo response with MRI (rWIR < 2.3) is associated with shorter EFS even when adjusted for known clinical covariates and shows similar results to histological response evaluation. rWIR is a potential tool for future response-based individualized healthcare in osteosarcoma patients before surgical resection.

A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer

Purpose

This study aimed to develop and validate a clinicopathological model to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and identify key prognostic factors.

Methods

This retrospective study analyzed data from 279 breast cancer patients who received NAC at Zhejiang Provincial People's Hospital from 2011 to 2021. Additionally, an external validation dataset, comprising 50 patients from Lanxi People's Hospital and Second Affiliated Hospital, Zhejiang University School of Medicine from 2022 to 2023 was utilized for model verification. A multivariate logistic regression model was established incorporating clinical, ultrasound features, circulating tumor cells (CTCs), and pathology variables at baseline and post-NAC. Model performance for predicting pCR was evaluated. Prognostic factors were identified using survival analysis.

Results

In the 279 patients enrolled, a pathologic complete response (pCR) rate of 27.96% (78 out of 279) was achieved. The predictive model incorporated independent predictors such as stromal tumor-infiltrating lymphocyte (sTIL) levels, Ki-67 expression, molecular subtype, and ultrasound echo features. The model demonstrated strong predictive accuracy for pCR (C-statistics/AUC 0.874), especially in human epidermal growth factor receptor 2 (HER2)-enriched (C-statistics/AUC 0.878) and triple-negative (C-statistics/AUC 0.870) subtypes, and the model performed well in external validation data set (C-statistics/AUC 0.836). Incorporating circulating tumor cell (CTC) changes post-NAC and tumor size changes further improved predictive performance (C-statistics/AUC 0.945) in the CTC detection subgroup. Key prognostic factors included tumor size >5cm, lymph node metastasis, sTIL levels, estrogen receptor (ER) status and pCR. Despite varied pCR rates, overall prognosis after standard systemic therapy was consistent across molecular subtypes.

Conclusion

The developed predictive model showcases robust performance in forecasting pCR in NAC-treated breast cancer patients, marking a step toward more personalized therapeutic strategies in breast cancer.

Clinical Interpretation of Intravoxel Incoherent Motion Perfusion Imaging in the Brain

Intravoxel incoherent motion (IVIM) perfusion imaging extracts information on blood motion in biological tissue from diffusion-weighted MR images. The method is attractive from a clinical stand point, because it measures in essence local quantitative perfusion, without intravenous contrast injection. Currently, the clinical interpretation of IVIM perfusion maps focuses on the IVIM perfusion fraction maps, but improvements in image quality of the IVIM pseudo-diffusion maps, using advanced postprocessing tools involving artificial intelligence, could lead to an increased interest in this parameters, as it could provide additional local perfusion information in the clinical setting, not otherwise available with other perfusion techniques.

Tumor steatosis and glutamine synthetase expression in patients with advanced hepatocellular carcinoma receiving atezolizumab plus bevacizumab therapy

AIM

The anti-programmed death-ligand 1 antibody atezolizumab and vascular endothelial growth factor-neutralizing antibody bevacizumab in combination (Atezo + Bev) have become the first-line therapy in advanced hepatocellular carcinoma (HCC). Distinct types of tumor immune microenvironment (TIME) and their associations with specific molecular subclasses and driver gene mutations have been identified in HCC; however, these insights are mainly based on surgically resected early-stage tumors. The current study aimed to reveal the biology and TIME of advanced HCC and their significance in predicting clinical outcomes of Atezo + Bev therapy.

METHODS

Thirty-three patients with advanced HCC who were scheduled for treatment with Atezo + Bev therapy were included in this study. Pretreatment tumor biopsy, pre- and posttreatment diffusion-weighted magnetic resonance imaging (MRI) with nine b values (0-1500 s/mm2 ), and other clinicopathologic factors were analyzed.

RESULTS

Compared with resectable HCC, advanced HCC was characterized by higher proliferative activity, a higher frequency of Wnt/β-catenin-activated HCC, and lower lymphocytic infiltration. Prognostically, two metabolism-related factors, histopathologically determined tumor steatosis and/or glutamine synthetase (GS) expression, and MRI-determined tumor steatosis, were the most significant prognostic indicators for progression-free survival (PFS) and overall survival after Atezo + Bev therapy. Furthermore, changes in the pre- and posttreatment true diffusion coefficients on MRI, which might reflect changes in TIME after treatment, were significantly associated with better PFS.

CONCLUSIONS

The biology and TIME of HCC were strikingly different in advanced HCC compared with those of surgically resected HCC. Two metabolism-related factors, pathologically determined tumor steatosis and/or GS expression, and MRI-determined tumor steatosis, were found to be the most significant prognostic indicators for Atezo + Bev therapy in advanced HCC.

Pitfalls of Diffusion-Weighted Imaging: Clinical Utility of T2 Shine-through and T2 Black-out for Musculoskeletal Diseases

Diffusion-weighted imaging (DWI) with an apparent diffusion coefficient (ADC) value is a relatively new magnetic resonance imaging (MRI) sequence that provides functional information on the lesion by measuring the microscopic movement of water molecules. While numerous studies have evaluated the promising role of DWI in musculoskeletal radiology, most have focused on tumorous diseases related to cellularity. This review article aims to summarize DWI-acquisition techniques, considering pitfalls such as T2 shine-through and T2 black-out, and their usefulness in interpreting musculoskeletal diseases with imaging. DWI is based on the Brownian motion of water molecules within the tissue, achieved by applying diffusion-sensitizing gradients. Regardless of the cellularity of the lesion, several pitfalls must be considered when interpreting DWI with ADC values in musculoskeletal radiology. This review discusses the application of DWI in musculoskeletal diseases, including tumor and tumor mimickers, as well as non-tumorous diseases, with a focus on lesions demonstrating T2 shine-through and T2 black-out effects. Understanding these pitfalls of DWI can provide clinically useful information, increase diagnostic accuracy, and improve patient management when added to conventional MRI in musculoskeletal diseases.

Intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging for neoadjuvant chemotherapy response evaluation in patients with osteosarcoma

OBJECTIVES

This study aims to explore the role of quantitative intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters in characterizing changes in osteosarcoma (OS) patients receiving neoadjuvant chemotherapy (NACT).

MATERIAL AND METHODS

Twenty-seven patients with histologically proven OS were examined prospectively and divided into good-response group (n = 14) and poor-response group (n = 13). IVIM and DCE-MRI sequences were performed at baseline (pre-NACT) and after three cycles of NACT (post-NACT). Apparent diffusion coefficient (ADC) and IVIM bi-exponential model parameters, including diffusion coefficient (D-Bi), perfusion coefficient (D*-Bi), and perfusion fraction (f-Bi), were evaluated. DCE-MRI parameters, including quantitative parameters (volume transfer constant [K^trans], elimination rate constant [Kep], and extravascular extracellular space volume ratio [Ve]) and semi-quantitative parameters (initial area under the gadolinium curve [IAUGC] and contrast enhancement rate [CER]), were also measured.

RESULTS

D-Bi, D*-Bi, and f-Bi post-NACT and ΔD-Bi were statistically different between the good- and poor-response groups (Z₁ =  - 3.348, Z₂ =  - 2.572, Z₃ =  - 2.378, t = 2.235, P < 0.05). ADC, f-Bi, K^trans, IAUGC, Kep, and CER post-NACT were statistically different from those at pre-NACT (P < 0.05). The receiver operating characteristic curve showed that f-Bi post-NACT had the best performance among all parameters, with area under the curve of 0.769, sensitivity of 1, and specificity of 0.538. The correlation analysis showed that the efficacy of NACT was negatively correlated with D-Bi, D*-Bi post-NACT, and ΔD-Bi (r₁ =  - 0.530, r₂ =  - 0.411, r₃ =  - 0.434, P₁ = 0.008, P₂ = 0.046, P₃ = 0.034) and significantly positively correlated with f-Bi post-NACT (r = 0.482, P = 0.017).

CONCLUSIONS

The IVIM quantitative parameters D-Bi, D*-Bi, and f-Bi post-NACT and ΔD-Bi could be used as noninvasive imaging biomarkers for early response assessment of NACT in OS.