Soft tissue sarcoma: DWI and DCE-MRI parameters correlate with Ki-67 labeling index

Dynamic contrast-enhanced and diffusion-weighted MRI of cervical carcinoma: Correlations with Ki-67 proliferation status

OBJECTIVES

To investigate the association of quantitative parameter (apparent diffusion coefficient [ADC]) from diffusion-weighted imaging (DWI) and various quantitative and semiquantitative parameters from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) with Ki-67 proliferation index (PI) in cervical carcinoma (CC).

METHODS

A total of 102 individuals with CC who received 3.0 T MRI examination (DWI and DCE MRI) between October 2016 and December 2022 were enrolled in our investigation. Two radiologists separately assessed the ADC parameter and various quantitative and semiquantitative parameters including (volume transfer constant [Ktrans], rate constant [kep], extravascular extracellular space volume fraction [ve], volume fraction of plasma [vp], time to peak [TTP], maximum concentration [MaxCon], maximal slope [MaxSlope] and area under curve [AUC]) for each tumor. Their association with Ki-67 PI was analyzed by Spearman association analysis. The discrepancy between low-proliferation and high-proliferation groups was subsequently analyzed. The receiver operating characteristic (ROC) curve analysis utilized to identify optimal cut-off points for significant parameters.

RESULTS

Both ADC (ρ = -0.457, p < 0.001) and Ktrans (ρ = -0.467, p < 0.001) indicated a strong negative association with Ki-67 PI. Ki-67 PI showed positive correlations with TTP, MaxCon, MaxSlope and AUC (ρ = 0.202, 0.231, 0.309, 0.235, respectively; all p values<0.05). Compared with the low-proliferation group, high-Ki-67 group presented a significantly lower ADC (0.869 ± 0.125 × 10-3 mm2/s vs. 1.149 ± 0.318 × 10-3 mm2/s; p < 0.001) and Ktrans (1.314 ± 1.162 min-1vs. 0.391 ± 0.390 min-1; p < 0.001), also significantly higher MaxCon values (0.756 ± 0.959 vs. 0.422 ± 0.341; p < 0.05) and AUC values (2.373 ± 3.012 vs. 1.273 ± 1.000; p < 0.05). The cut-offs of ADC, Ktrans, MaxCon and AUC for discrimating low- and high-Ki-67 groups were 0.920 × 10-3 mm2/s, 0.304 min-1, 0.209 and 1.918, respectively.

CONCLUSIONS

ADC, Ktrans, TTP, MaxCon, MaxSlope and AUC are associated with Ki-67 PI. ADC and Ktrans exhibited high performance to discriminate low and high Ki-67 status of CC.

Prediction of PD-L1 and Ki-67 status in primary central nervous system diffuse large B-cell lymphoma by diffusion and perfusion MRI: a preliminary study

OBJECTIVE

To assess whether diffusion and perfusion MRI derived parameters could non-invasively predict PD-L1 and Ki-67 status in primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL).

METHODS

We retrospectively analyzed DWI, DSC-PWI, and morphological MRI (mMRI) in 88 patients with PCNS-DLBCL. The mMRI features were compared using chi-square tests or Fisher exact test. Minimum ADC (ADCmin), mean ADC(ADCmean), relative minimum ADC (rADCmin), relative mean ADC (rADCmean), and relative maximum CBV (rCBVmax) values were compared in PCNS-DLBCL with different molecular status by using the Mann-Whitney U test. The diagnostic performances were evaluated by receiver operating characteristic curves.

RESULTS

PCNS-DLBCL with high PD-L1 expression demonstrated a significantly higher ADCmin value than those with low PD-L1. The ADCmean and rADCmean values were significantly lower in PCNS-DLBCL with high Ki-67 status compared with those in low Ki-67 status. Other ADC, CBV parameters, and mMRI features did not show any association with these molecular statuses The diagnostic efficacy of ADC values in assessing PD-L1 and Ki-67 status was relatively low, with area under the curves (AUCs) values less than 0.7.

CONCLUSIONS

DWI-derived ADC values can provide some relevant information about PD-L1 and Ki-67 status in PCNS-DLBCL, but may not be sufficient to predict their expression due to the rather low diagnostic performance.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiation of soft tissue sarcoma from benign lesions: a systematic review of literature

OBJECTIVE

To systematically review the literature assessing the role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in the differentiation of soft tissue sarcomas from benign lesions.

MATERIALS AND METHODS

A comprehensive literature search was performed with the following keywords: multiparametric magnetic resonance imaging, DCE-MR perfusion, soft tissue, sarcoma, and neoplasm. Original studies evaluating the role of DCE-MRI for differentiating benign soft-tissue lesions from soft-tissue sarcomas were included.

RESULTS

Eighteen studies with a total of 965 imaging examinations were identified. Ten of twelve studies evaluating qualitative parameters reported improvement in discriminative power. One of the evaluated qualitative parameters was time-intensity curves (TIC), and malignant curves (TIC III, IV) were found in 74% of sarcomas versus 26.5% benign lesions. Six of seven studies that used the semiquantitative approach found it relatively beneficial. Four studies assessed quantitative parameters including Ktrans (contrast transit from the vascular compartment to the interstitial compartment), Kep (contrast return to the vascular compartment), and Ve (the volume fraction of the extracellular extravascular space) in addition to other parameters. All found Ktrans, and 3 studies found Kep to be significantly different between sarcomas and benign lesions. The values for Ve were variable. Additionally, eight studies assessed diffusion-weighted imaging (DWI), and 6 of them found it useful.

CONCLUSION

Of different DCE-MRI approaches, qualitative parameters showed the best evidence in increasing the diagnostic performance of MRI. Semiquantitative and quantitative approaches seemed to improve the discriminative power of MRI, but which parameters and to what extent is still unclear and needs further investigation.

Qualitative and quantitative MRI analysis of alveolar soft part sarcoma: correlation with histological grade and Ki-67 expression

OBJECTIVE

To investigate the correlation between MRI findings and histological features for preoperative prediction of histological grading and Ki-67 expression level in alveolar soft part sarcoma (ASPS).

METHODS

A retrospective analysis was conducted on 63 ASPS patients (Jan 2017-May 2023). All patients underwent 3.0-T MRI examinations, including conventional sequences, dynamic contrast-enhanced scans with time-intensity curve analysis, and diffusion-weighted imaging with apparent diffusion coefficient (ADC) measurements. Patients were divided into low-grade (histological Grade I) and high-grade (histological Grade II/III) groups based on pathology. Immunohistochemistry was used to assess Ki-67 expression levels in ASPS. Statistical analysis included chi-square tests, Wilcoxon rank-sum test, binary logistic regression analysis, Spearman correlation analysis, and receiver operating characteristic curve analysis of various observational data.

RESULTS

There were 29 low-grade and 34 high-grade patients (26 males and 37 females) and a wide age range (5-68 years). Distant metastasis, tumor enhancement characteristics, and ADC values were independent predictors of high-grade ASPS. High-grade ASPS had lower ADC values (p = 0.002), with an area under the curve (AUC), sensitivity, and specificity of 0.723, 79.4%, and 58.6%, respectively, for high-grade prediction. There was a negative correlation between ADC values and Ki-67 expression (r = -0.526; p < 0.001). When the cut-off value of ADC was 0.997 × 10-3 mm²/s, the AUC, sensitivity, and specificity for predicting high Ki-67 expression were 0.805, 65.6%, and 83.9%, respectively.

CONCLUSION

Qualitative and quantitative MRI parameters are valuable for predicting histological grading and Ki-67 expression levels in ASPS.

CRITICAL RELEVANCE STATEMENT

This study will help provide a more nuanced understanding of ASPS and guide personalized treatment strategies.

KEY POINTS

There is limited research on assessing ASPS prognosis through MRI. Metastasis, enhancement, and ADC correlated with histological grade; ADC related to Ki-67 expression. MRI provides clinicians with valuable information on ASPS grading and proliferation activity.

Amide Proton Transfer-Weighted Imaging in Assessing the Aggressive and Proliferative Potential of Bladder Cancer

BACKGROUND

Ki-67 and human epidermal growth factor receptor 2 (HER2) are known oncogenes involved in bladder cancer (BCa) patient risk stratification. Preoperative assessment of their expression level can assist in clinical treatment decision-making. Recently, amide proton transfer-weighted (APTw) MRI has shown promising potential in the diagnosis of several malignancies. However, few studies reported the value of APTw imaging in evaluating Ki-67 and HER2 status of BCa.

PURPOSE

To investigate the feasibility of APTw MRI in assessing the aggressive and proliferative potential regarding the expression levels of Ki-67 and HER2 in BCa.

STUDY TYPE

Retrospective.

SUBJECTS

114 patients (mean age, 64.78 ± 11.93 [SD] years; 97 men) were studied.

FIELD STRENGTH/SEQUENCE

APTw MRI acquired by a three-dimensional fast-spin-echo sequence at 3.0 T MRI system.

ASSESSMENT

Patient pathologic findings, included histologic grade and the expression status of Ki-67 and HER2, were reviewed by one uropathologist. The APTw values of BCa were independently measured by two radiologists and were compared between high-/low-tumor grade group, high-/low-Ki-67 expression group, and high-/low-HER2 expression group.

STATISTICAL TESTS

The interclass correlation coefficient, independent sample t-test, Mann-Whitney U test, Spearman's rank correlation, and receiver operating characteristic curve (ROC) analysis were used. P < 0.05 was considered statistically significant.

RESULTS

Significantly higher APTw values were found in high-grade BCa patients (7.72% vs. 4.29%, P < 0.001), high-Ki-67 expression BCa patients (8.40% vs. 3.25%, P < 0.001) and HER2 positive BCa patients (8.24% vs. 5.40%, P = 0.001). APTw values were positively correlated with Ki-67 (r = 0.769) and HER2 (r = 0. 356) expression status. The area under the ROC curve of the APTw values for detecting Ki-67 and HER2 expression status were 0.883 (95% CI: 0.790-0.945) and 0.713 (95% CI: 0.592-0.816), respectively.

DATA CONCLUSIONS

APTw MRI is a potential method to assess the biological and proliferation potential of BCa.

LEVEL OF EVIDENCE: 4

TECHNICAL EFFICACY

Stage 2.

Applying dynamic contrast-enhanced MRI tracer kinetic models to differentiate benign and malignant soft tissue tumors

BACKGROUND

To explore the potential of different quantitative dynamic contrast-enhanced (qDCE)-MRI tracer kinetic (TK) models and qDCE parameters in discriminating benign from malignant soft tissue tumors (STTs).

METHODS

This research included 92 patients (41females, 51 males; age range 16-86 years, mean age 51.24 years) with STTs. The qDCE parameters (Ktrans, Kep, Ve, Vp, F, PS, MTT and E) for regions of interest of STTs were estimated by using the following TK models: Tofts (TOFTS), Extended Tofts (EXTOFTS), adiabatic tissue homogeneity (ATH), conventional compartmental (CC), and distributed parameter (DP). We established a comprehensive model combining the morphologic features, time-signal intensity curve shape, and optimal qDCE parameters. The capacities to identify benign and malignant STTs was evaluated using the area under the curve (AUC), degree of accuracy, and the analysis of the decision curve.

RESULTS

TOFTS-Ktrans, EXTOFTS-Ktrans, EXTOFTS-Vp, CC-Vp and DP-Vp demonstrated good diagnostic performance among the qDCE parameters. Compared with the other TK models, the DP model has a higher AUC and a greater level of accuracy. The comprehensive model (AUC, 0.936, 0.884-0.988) demonstrated superiority in discriminating benign and malignant STTs, outperforming the qDCE models (AUC, 0.899-0.915) and the traditional imaging model (AUC, 0.802, 0.712-0.891) alone.

CONCLUSIONS

Various TK models successfully distinguish benign from malignant STTs. The comprehensive model is a noninvasive approach incorporating morphological imaging aspects and qDCE parameters, and shows significant potential for further development.

Synovial Sarcoma in the Extremity: Diversity of Imaging Features for Diagnosis and Prognosis

Synovial sarcomas are rare and highly aggressive soft-tissue sarcomas, primarily affecting adolescents and young adults aged 15-40 years. These tumors typically arise in the deep soft tissues, often near the large joints of the extremities. While the radiological features of these tumors are not definitely indicative, the presence of calcification in a soft-tissue mass (occurring in 30% of cases), adjacent to a joint, strongly suggests the diagnosis. Cross-sectional imaging characteristics play a crucial role in diagnosing synovial sarcomas. They often reveal significant characteristics such as multilobulation and pronounced heterogeneity (forming the "triple sign"), in addition to features like hemorrhage and fluid-fluid levels with septa (resulting in the "bowl of grapes" appearance). Nevertheless, the existence of non-aggressive features, such as gradual growth (with an average time to diagnosis of 2-4 years) and small size (initially measuring < 5 cm) with well-defined margins, can lead to an initial misclassification as a benign lesion. Larger size, older age, and higher tumor grade have been established as adverse predictive indicators for both local disease recurrence and the occurrence of metastasis. Recently, the prognostic importance of CT and MRI characteristics for synovial sarcomas was elucidated. These include factors like the absence of calcification, the presence of cystic components, hemorrhage, the bowl of grape sign, the triple sign, and intercompartmental extension. Wide surgical excision remains the established approach for definitive treatment. Gaining insight into and identifying the diverse range of presentations of synovial sarcomas, which correlate with the prognosis, might be helpful in achieving the optimal patient management.

Apparent diffusion coefficient values effectively predict cell proliferation and determine oligodendroglioma grade

This study aims to evaluate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) values in differentiating oligodendroglioma of various grades and explore the correlation between ADC and Ki-67. The preoperative MRI data of 99 patients with World Health Organization (WHO) grades 2 (n = 42) and 3 (n = 57) oligodendroglioma confirmed by surgery and pathology were retrospectively analyzed. Conventional MRI features, ADCmean, ADCmin, and normalized ADC (nADC) were compared between the two groups. A receiver operating characteristic curve was used to evaluate each parameter's diagnostic efficacy in differentiating the two tumor types. Each tumor's Ki-67 proliferation index was also measured to explore its relationship with the ADC value. Compared with WHO2 grade tumors, WHO3 grade tumors had a larger maximum diameter and more significant cystic degeneration/necrosis, edema, and moderate/severe enhancement (all P < 0.05). The ADCmin, ADCmean, and nADC values of the WHO3 and WHO2 grade tumors were significantly different, and the ADCmin value most accurately distinguished the two tumor types, yielding an area under the curve value of 0.980. When 0.96 × 10^-3 mm²/s was used as the differential diagnosis threshold, the sensitivity, specificity, and accuracy of the two groups were 100%, 93.00%, and 96.96%, respectively. The ADCmin (r = -0.596), ADCmean (r =  - 0.590), nADC (r =  - 0.577), and Ki-67 proliferation index values had significantly negative correlations (all P < 0.05). Conventional MRI features and ADC values are beneficial in the noninvasive prediction of the WHO grade and tumor proliferation rate of oligodendroglioma.

Advances in The Application and Research of Magnetic Resonance Diffusion Kurtosis Imaging in The Musculoskeletal System

Magnetic resonance diffusion kurtosis imaging (DKI) is an emerging magnetic resonance imaging (MRI) technique that can reflect microstructural changes in tissue through non-Gaussian diffusion of water molecules. Compared to traditional diffusion weighted imaging (DWI), the DKI model has shown greater sensitivity for diagnosis of musculoskeletal diseases and can help formulate more reasonable treatment plans. Moreover, DKI is an important auxiliary examination for evaluation of the motor function of the musculoskeletal system. This article briefly introduces the basic principles of DKI and reviews the application and research of DKI in the evaluation of disorders of the musculoskeletal system (including bone tumors, soft tissue tumors, spinal lesions, chronic musculoskeletal diseases, musculoskeletal trauma, and developmental disorders) as well as the normal musculoskeletal tissues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.

Apparent Diffusion Coefficient in the Differentiation of Common Pediatric Brain Tumors in the Posterior Fossa: Different Region-of-Interest Selection Methods for Time Efficiency, Measurement Reproducibility, and Diagnostic Utility

OBJECTIVES

This study aimed to explore the diagnostic ability of apparent diffusion coefficient (ADC) values obtained from different region of interest (ROI) measurements in tumor parenchyma for differentiating posterior fossa tumors (PFTs) and the correlations between ADC values and Ki-67.

METHODS

Seventy-three pediatric patients with PFTs who underwent conventional diffusion-weighted imaging were recruited in this study. Five different ROIs were manually drawn by 2 radiologists (ROI-polygon, ROI-3 sections, ROI-3-5 ovals, ROI-more ovals, and ROI-whole). The interreader/intrareader repeatability, time required, diagnostic ability, and Ki-67 correlation analysis of the ADC values based on these ROI strategies were calculated.

RESULTS

Both interreader and intrareader reliabilities were excellent for ADC values among the different ROI strategies (intraclass correlation coefficient, 0.899-0.992). There were statistically significant differences in time consumption among the 5 ROI selection methods ( P < 0.001). The time required for the ROI-3-5 ovals was the shortest (32.23 ± 5.14 seconds), whereas the time required for the ROI-whole was the longest (204.52 ± 92.34 seconds). The diagnostic efficiency of the ADC values showed no significant differences among the different ROI measurements ( P > 0.05). The ADC value was negatively correlated with Ki-67 ( r = -0.745 to -0.798, all P < 0.0001).

CONCLUSIONS

The ROI-3-5 ovals method has the best interobserver repeatability, the shortest amount of time spent, and the best diagnostic ability. Thus, it is considered an effective measurement to produce ADC values in the evaluation of pediatric PFTs.

Role of Imaging in Initial Prognostication of Locally Advanced Soft Tissue Sarcomas

BACKGROUND

Although imaging is central in the initial staging of patients with soft tissue sarcomas (STS), it remains underused and few radiological features are currently used in practice for prognostication and to help guide the best therapeutic strategy. Yet, several prognostic qualitative and quantitative characteristics from magnetic resonance imaging (MRI) and positron emission tomography (PET) have been identified over these last decades.

OBJECTIVE

After an overview of the current validated prognostic features based on baseline imaging and their integration into prognostic tools, such as nomograms used by clinicians, the aim of this review is to summarize more complex and innovative MRI, PET, and radiomics features, and to highlight their role to predict indirectly (through histologic grade) or directly the patients' outcomes.

Methodological considerations on segmenting rhabdomyosarcoma with diffusion-weighted imaging-What can we do better?

PURPOSE

Diffusion-weighted MRI is a promising technique to monitor response to treatment in pediatric rhabdomyosarcoma. However, its validation in clinical practice remains challenging. This study aims to investigate how the tumor segmentation strategy can affect the apparent diffusion coefficient (ADC) measured in pediatric rhabdomyosarcoma.

MATERIALS AND METHODS

A literature review was performed in PubMed using search terms relating to MRI and sarcomas to identify commonly applied segmentation strategies. Seventy-six articles were included, and their presented segmentation methods were evaluated. Commonly reported segmentation strategies were then evaluated on diffusion-weighted imaging of five pediatric rhabdomyosarcoma patients to assess their impact on ADC.

RESULTS

We found that studies applied different segmentation strategies to define the shape of the region of interest (ROI)(outline 60%, circular ROI 27%), to define the segmentation volume (2D 44%, multislice 9%, 3D 21%), and to define the segmentation area (excludes edge 7%, excludes other region 19%, specific area 27%, whole tumor 48%). In addition, details of the segmentation strategy are often unreported. When implementing and comparing these strategies on in-house data, we found that excluding necrotic, cystic, and hemorrhagic areas from segmentations resulted in on average 5.6% lower mean ADC. Additionally, the slice location used in 2D segmentation methods could affect ADC by as much as 66%.

CONCLUSION

Diffusion-weighted MRI studies in pediatric sarcoma currently employ a variety of segmentation methods. Our study shows that different segmentation strategies can result in vastly different ADC measurements, highlighting the importance to further investigate and standardize segmentation.

Whole-tumor histogram analysis of diffusion-weighted imaging and dynamic contrast-enhanced MRI for soft tissue sarcoma: correlation with HIF-1alpha expression

OBJECTIVE

To investigate the correlation of histogram metrics from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with HIF-1alpha expression in soft tissue sarcoma (STS).

METHODS

We enrolled 71 patients with STS who underwent 3.0-T MRI, including conventional MRI, DWI, and DCE-MRI sequences. Location, maximum tumor diameter, envelope, T2-weighted tumor heterogeneity, peritumoral edema, peritumoral enhancement, necrosis, tail-like pattern, bone invasion, and vessel/nerve invasion and/or encasement were determined using conventional MRI images. The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), K^trans, K_ep, and V_e maps. Independent-samples t test and one-way ANOVA were used for testing the differences between normally distributed categorical data with HIF-1alpha expression. Pearson and Spearman correlations and multiple linear regression analyses were performed to determine the correlations between histogram metrics and HIF-1alpha expression. Survival curves were plotted using the Kaplan-Meier method.

RESULTS

Regarding conventional MRI features, only highly heterogeneous on T2-weighted images (55.6 ± 19.9% vs. 45.4 ± 20.5%, p = 0.041) and more than 50% necrotic area (57.3 ± 20.4% vs. 43.9 ± 19.7%, p = 0.002) were prone to indicate STS with higher HIF-1alpha expression. Histogram metrics obtained from ADC (mean, median, 10th, and 25th percentile values), K^trans (mean, median, 75th, and 90th percentile values), and K_ep (90th percentile values) were significantly correlated with HIF-1alpha expression. Multiple linear regression analysis demonstrated that more than 50% necrosis, ADC_skewness, K^trans_90th, and grade III were independently associated with HIF-1alpha expression.

CONCLUSION

DWI and DCE-MRI histogram parameters were significantly correlated with HIF-1alpha expression in STS.

KEY POINTS

• DWI and DCE-MRI histogram parameters are correlated with HIF-1alpha expression in STS. • More than 50% necrosis, ADC_skewness, K^trans_90th, and grade III were independently associated with HIF-1alpha expression in STS.

Diagnostic Performance of Dynamic Contrast-Enhanced MRI and 18F-FDG PET/CT for Evaluation of Soft Tissue Tumors and Correlation with Pathology Parameters

RATIONALE AND OBJECTIVES

To assess the diagnostic performance of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and fluorine-18-fluorodeoxyglucose (¹⁸F-FDG) positron-emission tomography/computed tomography (PET/CT) parameters in evaluating the biological behavior of soft tissue tumors.

MATERIALS AND METHODS

We retrospectively analyzed DCE-MRI and ¹⁸F-FDG PET/CT parameters in 78 patients with pathology-confirmed soft tissue tumors. A total of 78 patients had undergone DCE-MRI examination, while 24 patients with malignant soft tissue tumor had undergone ¹⁸F-FDG PET/CT examination. Microvessel density (MVD) and the Ki-67 labeling index (LI) were detected using immunohistochemistry. Differences in parameters (Ktrans, Kep, Ve, MVD, and Ki-67 LI) between benign and malignant tumors were compared. Differences in parameters (Ktrans, Kep, Ve, MVD, and SUV_max) between high- and low-proliferation malignant tumors (grouped by Ki-67 LI) were compared. Correlation of the DCE-MRI and ¹⁸F-FDG PET/CT parameters with MVD and Ki-67 LI was analyzed.

RESULTS

Only the Ktrans, Kep, MVD, and Ki-67 LI differed significantly between the benign and malignant soft tissue tumors (all p < 0.001). Only Kep (p = 0.033) and SUV_max (p = 0.001) differed significantly between high- and low-proliferation malignant soft tissue tumors. Ktrans, Kep, and SUV_max correlated positively with MVD (r = 0.805, 0.778, 0.730, respectively; all p < 0.001), and with Ki-67 LI (r = 0.721, 0.685, 0.655, respectively; all p < 0.001).

CONCLUSION

DCE-MRI and ¹⁸F-FDG PET/CT parameters indicate soft tissue tumor biological behavior and can be used to differentiate between benign and malignant soft tissue tumors and between high- and low-proliferation malignant soft tissue tumors.

Soft tissue sarcoma: intravoxel incoherent motion and diffusion kurtosis imaging parameters correlate with the histological grade and Ki-67 expression

BACKGROUND

Accurate prediction of the histological grade and Ki-67 expression of soft tissue sarcoma (STS) before surgery is essential for the subsequent diagnosis, treatment, and prognostic evaluation of patients.

PURPOSE

To evaluate intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in predicting the histological grade and Ki-67 expression of STS.

MATERIAL AND METHODS

A total of 40 patients underwent 3-T MRI, including conventional sequences; IVIM and DKI parameters were obtained. All patients were divided into a low-grade (grade 1 and grade 2) group and a high-grade (grade 3) group through pathological analysis. Ki-67 expression of each lesion was calculated. Chi-square test, independent sample t-test, Mann-Whitney U test, Pearson, Spearman, and receiver operating characteristic curve analysis were performed.

RESULTS

There were 17 patients in the low-grade group and 23 in the high-grade group. Ki-67 expression was in the range of 10%-80%. D value was inversely correlated with Ki-67 expression. MK value showed a moderate positive correlation with Ki-67 expression. Regarding histological grading, only the peritumoral enhancement was statistically different between low- and high-grade STS on conventional MRI (P=0.024). The high-grade group had significantly higher MK value and lower D and MD value than the low-grade group. MK value showed the best diagnostic performance. The combination of MK and MD yielded the highest specificity (88.24%), and the combination of D, MK, and MD yielded the best area under the curve value (0.841) and sensitivity (95.65%).

CONCLUSION

IVIM and DKI parameters were correlated with Ki-67 expression and could help differentiate between low- and high-grade STS.

Development and Validation of an MRI Radiomics-Based Signature to Predict Histological Grade in Patients with Invasive Breast Cancer

Background

Histological grade is an important factor in the overall prognosis of patients with invasive breast cancer. Therefore, the non-invasive assessment of histological grade in breast cancer patients is an increasing concern for clinicians. We aimed to establish an MRI-based radiomics model for preoperative prediction of invasive breast cancer histological grade.

Methods

We enrolled 901 patients with invasive breast cancer and pre-operative MRI. Patients were randomly divided into the training cohort (n=630) and validation cohort (n=271) with a ratio of 7:3. A radiomics signature was constructed by extracting radiomics features from MRI images and was developed according to multivariate logistic regression analysis. The diagnostic performance of the radiomics model was assessed using receiver operating characteristic (ROC) curve analysis.

Results

Of the 901 patients, 618 (68.6%) were histological grade 1 or 2 while 283 (31.4%) were histological grade 3. The area under the ROC curve (AUC) of the radiomics model for the prediction of the histological grade was 0.761 (95% CI 0.728–0.794) in the training cohort and 0.722 (95% CI 0.664–0.777) in the validation cohort. The decision curve analysis (DCA) demonstrated the radiomics model’s clinical application value.

Conclusion

This is a preliminary study suggesting that the development of an MRI-based radiomics model can predict the histological grade of invasive breast cancer.

Tumor cellularity beyond the visible in soft tissue sarcomas: Results of an ADC-based, single center, and preliminary radiomics study

Purpose

Soft tissue sarcomas represent approximately 1% of all malignancies, and diagnostic radiology plays a significant role in the overall management of this rare group of tumors. Recently, quantitative imaging and, in particular, radiomics demonstrated to provide significant novel information, for instance, in terms of prognosis and grading. The aim of this study was to evaluate the prognostic role of radiomic variables extracted from apparent diffusion coefficient (ADC) maps collected at diagnosis in patients with soft tissue sarcomas in terms of overall survival and metastatic spread as well as to assess the relationship between radiomics and the tumor grade.

Methods

Patients with histologically proven soft tissue sarcomas treated in our tertiary center from 2016 to 2019 who underwent an Magnetic Resonance (MR) scan at diagnosis including diffusion-weighted imaging were included in this retrospective institution review board–approved study. Each primary lesion was segmented using the b50 images; the volumetric region of interest was then applied on the ADC map. A total of 33 radiomic features were extracted, and highly correlating features were selected by factor analysis. In the case of feature/s showing statistically significant results, the diagnostic accuracy was computed. The Spearman correlation coefficient was used to evaluate the relationship between the tumor grade and radiomic features selected by factor analysis. All analyses were performed applying p&lt;0.05 as a significant level.

Results

A total of 36 patients matched the inclusion criteria (15 women; mean age 58.9 ± 15 years old). The most frequent histotype was myxofibrosarcoma (16.6%), and most of the patients were affected by high-grade lesions (77.7%). Seven patients had pulmonary metastases, and, altogether, eight were deceased. Only the feature Imc1 turned out to be a predictor of metastatic spread (p=0.045 after Bonferroni correction) with 76.7% accuracy. The value -0.16 showed 73.3% sensitivity and 71.4% specificity, and patients with metastases showed lower values (mean Imc1 of metastatic patients -0.31). None of the examined variables was a predictor of the overall outcome (p&gt;0.05, each). A moderate statistically significant correlation emerged only between Imc1 and the tumor grade (r=0.457, p=0.005).

Conclusions

In conclusion, the radiomic feature Imc1 acts as a predictor of metastatic spread in patients with soft tissue sarcomas and correlates with the tumor grade.

Myxomas and myxoid liposarcomas of the extremities: Our preliminary findings in conventional, perfusion, and diffusion magnetic resonance

Background

The differentiation between myxomas and myxoid liposarcomas (MLPS) often is a serious challenge for the radiologists. Magnetic resonance imaging (MRI) is the most useful imaging technique in characterization of the soft tissue tumors (STT).

Purpose

To evaluate in a sample of myxomas and MLPS of the extremities, what morphological findings in conventional MRI allow us to differentiate these two types of myxoid tumors, in addition to analyzing the validity of the apparent diffusion coefficient (ADC) values of diffusion-weighted MRI (DW-MRI).

Material and Methods

Magnetic resonance imaging studies in myxomas and MLPS of extremities searched in our PACS between 2015 and 2019. All studies had conventional MRI with T1, T2, and PD SPAIR sequences, while DW-MRI with ADC mapping and perfusion MRI with a T1 sequence repeated for 4 minutes after contrast injection were additional sequences only in some explorations. Two radiologists evaluated independently the MRI studies by examining the qualitative parameters. Apparent diffusion coefficient values were calculated using two methods-ADC global and ADC solid, and Receiver Operating Characteristic (ROC) curves were applied for analysis.

Results

The features were consistent with MLPS: size greater than 10 cm, heterogeneous signal on T1, and nodular enhancement, while the common findings for myxomas were a homogenously hypointense signal on T1 and diffuse peritumoral enhancement. The solid and global ADC values were higher in myxomas. We observed that the solid ADC value less than 2.06 x 10^-3mm² x s would support the diagnosis of MLPS against myxoma.

Conclusion

Overall, MRI with its different modalities improved the diagnostic accuracy when differentiating myxomas from MLPS of extremities.

Correlation between quantitative parameters of CEUS and Ki-67 labeling index in soft-tissue sarcoma

BACKGROUND

Apart from the immunohistochemical Ki-67 labeling index (LI), clinicians need a non-invasive and convenient way to predict the prognosis of patients with soft-tissue sarcoma (STS).

PURPOSE

To investigate the correlation between quantitative parameters of contrast-enhanced ultrasound (CEUS) and Ki-67 LI in STS.

MATERIAL AND METHODS

A total of 25 patients diagnosed with STS who underwent CEUS examination using SonoVue®, between January 2019 to November 2020, were included in the study. They were then divided into a high-proliferation group and low-proliferation group according to 30% Ki-67 positive tumor cells. The quantitative parameters in the semi-automatic time intensity curve analysis software, including arrival time, time to peak, peak intensity, rise time (RT), rise slope, 50% wash-out time, and 50% wash-out intensity, were extracted from the time intensity curve of CEUS by two independent observers. Statistical evaluation of the correlation and difference between CEUS quantitative parameters and Ki-67 LI between the two groups was performed. According to the area under the curve (AUC) analysis, optimal cutoff points of parameters with significant difference were determined.

RESULTS

CEUS RT of the high-proliferation group in STS was significantly higher than that of the low-proliferation group (ρ = 0.509, P = 0.01). The most reasonable cutoff to distinguish between low- and high-proliferation groups was 10.84 s. The sensitivity, specificity, and the AUC were 86.7%, 80%, and 0.80, respectively.

CONCLUSION

CEUS RT was correlated with Ki-67 LI of STS, which can be used as a minimally invasive auxiliary tool to predict the prognosis of STS in clinical practice.

Correlation of Apparent Diffusion Coefficient With Proliferation and Apoptotic Indexes in a Murine Model of Fibrosarcoma: Comparison of Four Methods for MRI Region of Interest Positioning

BACKGROUND

Diffusion-weighted imaging (DWI) has demonstrated great potential in predicting the expression of tumor cell proliferation and apoptosis indexes.

PURPOSE

To evaluate the impact of four region of interest (ROI) methods on interobserver variability and apparent diffusion coefficient (ADC) values and to examine the correlation of ADC values with Ki-67, Bcl-2, and P53 labeling indexes (LIs) in a murine model of fibrosarcoma.

STUDY TYPE

Prospective, animal model.

ANIMAL MODEL

A total of 22 female BALB/c mice bearing intramuscular fibrosarcoma xenografts.

FIELD STRENGTH/SEQUENCE

A 3.0 T/T1-weighted fast spin-echo (FSE), T2-weighted fast relaxation fast spin-echo, and DWI PROPELLER FSE sequences.

ASSESSMENT

Four radiologists measured ADC values using four ROI methods (oval, freehand, small-sample, and whole-volume). Immunohistochemical assessment of Ki-67, Bcl-2, and P53 LIs was performed.

STATISTICAL TESTS

Interclass correlation coefficient (ICC), one-way analysis of variance followed by LSD-t post hoc analysis, and Pearson correlation test were performed. The statistical threshold was defined as a P-value of <0.05.

RESULTS

All ROI methods for ADC measurements showed excellent interobserver agreement (ICC range, 0.832-0.986). The ADC values demonstrated significant differences among the four ROI methods. The ADC values for oval, freehand, small-sample, and whole-volume ROI methods showed a moderately negative correlation with Ki-67 (r = -0.623; r = -0.629; r = -0.642, and r = -0.431) and Bcl-2 (r = -0.590; r = -0.597; r = -0.659, and r = -0.425) LIs, but no correlation with P53 LI (r = 0.364, P = 0.104; r = 0.350, P = 0.120; r = 0.379, P = 0.091; r = 0.390, P = 0.080).

DATA CONCLUSION

The ADC value can be used to evaluate cell proliferation and apoptosis indexes in a murine model of fibrosarcoma, employing the small-sample ROI as a reliable method.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 3.

Soft Tissue Sarcomas: The Role of Quantitative MRI in Treatment Response Evaluation

BACKGROUND

Although curative surgery remains the cornerstone of the therapeutic strategy in patients with soft tissue sarcomas (STS), neoadjuvant radiotherapy and chemotherapy (NART and NACT, respectively) are increasingly used to improve operability, surgical margins and patient outcome. The best imaging modality for locoregional assessment of STS is MRI but these tumors are mostly evaluated in a qualitative manner.

OBJECTIVE

After an overview of the current standard of care regarding treatment for patients with locally advanced STS, this review aims to summarize the principles and limitations of (i) the current methods used to evaluate response to neoadjuvant treatment in clinical practice and clinical trials in STS (RECIST 1.1 and modified Choi criteria), (ii) quantitative MRI sequences (i.e., diffusion weighted imaging and dynamic contrast enhanced MRI), and (iii) texture analyses and (delta-) radiomics.

Malignant giant cell tumor of toe: A case report and review of literature

INTRODUCTION

A giant cell tumor of soft tissue (GCST) is a benign soft tissue tumor that often occurs subcutaneously in the extremities. Rare cases of malignant GCST have been reported, but its pathogenesis remains unclear.

PATIENTS CONCERNS

We report a case of a 68-year-old man who noticed a painless mass on his second toe one and a half years ago. He visited the Department of Dermatology at our hospital. Magnetic resonance imaging revealed a soft tissue tumor, surrounding the distal aspect of the second toe.

DIAGNOSIS

A biopsy of the tumor was performed by a dermatologist, and it revealed a malignant giant cell tumor of the toe.

INTERVENTIONS

He was referred to our department and underwent lay amputation for wide-margin resection.

OUTCOMES

No recurrence or metastasis was observed 5 years after treatment.

CONCLUSION

: Malignant GCST should be treated with wide-margin resection immediately after its diagnosis.

What morphological MRI features enable differentiation of low-grade from high-grade soft tissue sarcoma?

Objective:

To assess the diagnostic performance of morphological MRI features separately and in combination for distinguishing low- from high-grade soft tissue sarcoma (STS).

Methods and materials:

We retrospectively analysed pre-treatment MRI examinations with T1, T2 with and without fat suppression (FS) and contrast-enhanced T1 obtained in 64 patients with STS categorized histologically as low (n = 21) versus high grade (n = 43). Two musculoskeletal radiologists blinded to histology evaluated MRI features. Diagnostic performance was calculated for each reader and for MRI features showing significant association with histology (p < 0.05). Logistic regression analysis was performed to develop a diagnostic model to identify high-grade STS.

Results:

Among all evaluated MRI features, only six features had adequate interobserver reproducibility (kappa>0.5). Multivariate logistic regression analysis revealed a significant association with tumour grade for lesion heterogeneity on FS images, intratumoural enhancement≥51% of tumour volume and peritumoural enhancement for both readers (p < 0.05). For both readers, the presence of each of the three features yielded odds ratios for high grade versus low grade from 4.4 to 9.1 (p < 0.05). The sum of the positive features for each reader independent of reader expertise yielded areas under the curve (AUCs) > 0.8. The presence of ≥2 positive features indicated a high risk for high-grade sarcoma, whereas ≤1 positive feature indicated a low-to-moderate risk

Conclusion:

A diagnostic MRI score based on tumour heterogeneity, intratumoural and peritumoural enhancement enables identification of lesions that are likely to be high-grade as opposed to low-grade STS.

Advances in knowledge:

Tumour heterogeneity in Fat Suppression sequence, intratumoural and peritumoural enhancement is identified as signs of high-grade sarcoma.

Standard diffusion-weighted, intravoxel incoherent motion, and dynamic contrast-enhanced MRI of musculoskeletal tumours: correlations with Ki67 proliferation status

AIM

To determine whether quantitative parameters derived from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) correlate with the Ki67 proliferation status in musculoskeletal tumours.

MATERIALS AND METHODS

Twenty-eight patients with musculoskeletal tumours diagnosed via surgical specimen histological analysis who underwent standard DWI, IVIM, and DCE were reviewed retrospectively. The mean standard DWI (apparent diffusion coefficient [ADC]), IVIM (pure diffusion coefficient [D], pseudo-diffusion coefficient [D∗] and perfusion fraction [ƒ]), and DCE (volume transfer constant [K^trans], rate constant [K_ep], and extravascular extracellular volume fraction [V_e]) parameters were measured and correlated with the Ki67 index. The Ki67 value was categorised as high (>20%) or low (≤20%).

RESULTS

The ADC and D values correlated negatively with the Ki67 index (r=-0.711∼-0.699, p<0.001), whereas the K^trans and K_ep values correlated positively with the Ki67 index (r=0.389-0.434, p=0.021, 0.041). The ADC and D values were lower (p<0.001), whereas the K^trans and K_ep values were higher (p=0.011, 0.005) in musculoskeletal tumours with a high Ki67 status than in those in a low status. The ADC and D demonstrated the largest area under the receiver-operating characteristic curve (AUC = 0.953), which is statistically bigger than the AUC of K^trans and K_ep (0.784 and 0.802, respectively).

CONCLUSION

ADC, D, K^trans, and K_ep correlate with the Ki67 index. ADC and D are the strongest quantitative parameters for predicting Ki67 status.

Relationship Between Ultrasound Features and Ki-67 Labeling Index of Soft Tissue Sarcoma

Objectives

To explore the relationship between ultrasound (US) features and Ki-67 labeling index (LI) of soft tissue sarcoma (STS).

Methods

Forty-six patients with 47 STS lesions, between September 2014 and April 2020, were enrolled in the study. Point-biserial correlation analysis and Spearman’s correlation analysis were utilized to examining the relationship between the US features and the Ki-67 LI of STS. The differences of US features between high and low Ki-67 proliferation groups were statistically analyzed by independent t test, Wilcoxon rank-sum test, and Fisher’s exact test. The optimal cut-off points of US features revealing significant differences were estimated by the maximum Youden index.

Results

A moderate correlation between the vascular density grade and the Ki-67 LI (ρ = 0.409, P = 0.004) was found in this study. In addition, other ultrasound features were irrelevant to the Ki-67 LI. The cut-off for differentiating low- and high-proliferation groups was grade II according to the best Youden index. The area under receiver operating characteristic (ROC) curve was 0.74 (p = 0.011) with a sensitivity of 60.6% and specificity of 78.6%.

Conclusions

Only the vascular density grade of STS had a weak positive correlation with Ki-67 LI, and might be capable of predicting the proliferation of STS. Other ultrasonographic features of STS such as shape and tumor margin have no correlation with Ki-67 LI.

Preoperative histogram parameters of dynamic contrast-enhanced MRI as a potential imaging biomarker for assessing the expression of Ki-67 in prostate cancer

Purpose

To investigate whether preoperative histogram parameters of dynamic contrast‐enhanced MRI (DCE‐MRI) can assess the expression of Ki‐67 in prostate cancer (PCa).

Materials and methods

A consecutive series of 76 patients with pathology‐proven PCa who underwent routine DCE‐MRI scans were retrospectively recruited. Quantitative parameters including the volume transfer constant (K^trans), rate contrast (K_ep), extracellular‐extravascular volume fraction (V_e), and plasma volume (V_p) by outlining the three‐dimensional volume of interest (VOI) of all lesions were processed. Then, the histogram analyses of these quantitative parameters were performed. The Spearman rank correlation analysis was used to evaluate the correlation of these parameters and Ki‐67 expression of PCa. Receiver operating characteristic (ROC) curve analysis was adopted to evaluate the efficacy of these quantitative histogram parameters in identifying high Ki‐67 expression from low Ki‐67 expression of PCa.

Results

Eighty‐eight PCa lesions were enrolled in this study, including 31 lesions with high Ki‐67 expression and 57 lesions with low Ki‐67 expression. The median, mean, 75th percentile, and 90th percentile derived from K^trans and K_ep had a moderately positive correlation with Ki‐67 expression (r = 0.361–0.450, p < 0.05), in which both the median and mean of K^trans had the highest positive correlation (r = 0.450, p < 0.05). The diagnostic efficacy of the K^trans median, mean, 75th percentile, and 90th percentile, along with the K_ep‐based median and mean was assessed by the ROC curve. The area under the curve (AUC) of the mean for K^trans was the highest (0.826). When the cut‐off of the mean for K^trans was ≥0.47/min, its Youden index, sensitivity, and specificity were 0.625, 0.871, and 0.754, respectively. The AUC of the median of K_ep was the lowest (0.772).

Conclusion

The histogram of DCE‐MRI quantitative parameters is correlated with Ki‐67 expression, which has the potential to noninvasively assess the expression of Ki‐67 with patients of PCa.

Evaluation of the Predictive Potential of 18F-FDG PET and DWI Data Sets for Relevant Prognostic Parameters of Primary Soft-Tissue Sarcomas

BACKGROUND

To evaluate the potential of simultaneously acquired 18F-FDG PET- and MR-derived quantitative imaging data sets of primary soft-tissue sarcomas for the prediction of neoadjuvant treatment response, the metastatic status and tumor grade.

METHODS

A total of 52 patients with a high-risk soft-tissue sarcoma underwent a 18F-FDG PET/MR examination within one week before the start of neoadjuvant treatment. For each patient, the maximum tumor size, metabolic activity (SUVs), and diffusion-restriction (ADC values) of the tumor manifestations were determined. A Mann-Whitney-U test was used, and ROC analysis was performed to evaluate the potential to predict histopathological treatment response, the metastatic status or tumor grade. The results from the histopathological analysis served as reference standard.

RESULTS

Soft-tissue sarcomas with a histopathological treatment response revealed a significantly higher metabolic activity than tumors in the non-responder group. In addition, grade 3 tumors showed a significant higher 18F-FDG uptake than grade 2 tumors. Furthermore, no significant correlation between the different outcome variables and tumor size or calculated ADC-values could be identified.

CONCLUSION

Measurements of the metabolic activity of primary and untreated soft-tissue sarcomas could non-invasively deliver relevant information that may be used for treatment planning and risk-stratification of high-risk sarcoma patients in a pretherapeutic setting.

An update in musculoskeletal tumors: from quantitative imaging to radiomics

In the last two decades, relevant progress has been made in the diagnosis of musculoskeletal tumors due to the development of new imaging tools, such as diffusion-weighted imaging, diffusion kurtosis imaging, magnetic resonance spectroscopy, and diffusion tensor imaging. Another important role has been played by the development of artificial intelligence software based on complex algorithms, which employ computing power in the detection of specific tumor types. The aim of this article is to report the most advanced imaging techniques focusing on their advantages in clinical practice.

Diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging after radiation therapy for bone metastases in patients with hepatocellular carcinoma

The objectives of this study were to assess changes in apparent diffusion coefficient (ADC) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters after radiation therapy (RT) for bone metastases from hepatocellular carcinoma (HCC) and to evaluate their prognostic value. This prospective study was approved by the Institutional Review Board. Fourteen patients with HCC underwent RT (30 Gy in 10 fractions once daily) for bone metastases. The ADC and DCE-MRI parameters and the volume of the target lesions were measured before (baseline) and one month after RT (post-RT). The Wilcoxon signed-rank test was used to compare the parameters between the baseline and post-RT MRI. The parameters were compared between patients with or without disease progression in RT fields using the Mann–Whitney test. Intraclass correlation coefficients were used to evaluate the interobserver agreement. The medians of the ADC, rate constant [k_ep], and volume fraction of the extravascular extracellular matrix [v_e] in the baseline and post-RT MRI were 0.67 (range 0.61–0.72) and 0.75 (range 0.63–1.43) (× 10^–3 mm²/s) (P = 0.027), 836.33 (range 301.41–1082.32) and 335.80 (range 21.86–741.87) (× 10^–3/min) (P = 0.002), and 161.54 (range 128.38–410.13) and 273.99 (range 181.39–1216.95) (× 10^–3) (P = 0.027), respectively. The medians of the percent change in the ADC of post-RT MRI in patients with progressive disease and patients without progressive disease were − 1.35 (range − 6.16 to 6.79) and + 46.71 (range 7.71–112.81) (%) (P = 0.011), respectively. The interobserver agreements for all MRI parameters were excellent (intraclass correlation coefficients > 0.8). In conclusion, the ADC, k_ep, and v_e of bone metastases changed significantly after RT. The percentage change in the ADC was closely related to local tumor progression.

Dynamic contrast-enhanced magnetic resonance imaging for differentiating head and neck paraganglioma and schwannoma

BACKGROUND AND PURPOSE

Morphological assessment with conventional magnetic resonance imaging (MRI) sequences has limited specificity to distinguish between paragangliomas and schwannomas. Assessing the differences in microvascular properties through pharmacokinetic parameters of dynamic contrast-enhanced (DCE)-MRI can provide additional information to aid in this differentiation.

MATERIALS AND METHODS

A prospective study on MR characterization of neck masses was performed between January 2017 and March 2019 in our department, out of which 40 patients with head and neck paragangliomas (HNPGLs) (33 lesions) and schwannomas (15 lesions) were included in this analysis. MR perfusion using dynamic axial T1WI fat suppressed fast spoiled gradient recalled sequence with parallel imaging was performed in all the patients, in addition to single-shot turbo spin-echo axial diffusion weighted imaging (DWI) and routine MRI. ROI-based method was used to obtain signal-time curves, permeability measurements, and mean apparent diffusion coefficient (ADC) to differentiate paragangliomas from schwannomas. Statistical analysis was done to assess the significance and establish a cutoff to distinguish between the two entities. The available images of DOTANOC PET/CT (34 lesions) were analyzed retrospectively. Correlations between the perfusion, diffusion, and molecular PET/CT parameters were done.

RESULTS

Paragangliomas had a higher wash-in rate, wash-out rate, K_trans, K_ep , and V_p (p < 0.001); while schwannomas had a higher relative enhancement (p < 0.012), time to peak, time of onset, brevity of enhancement, and V_e (p < 0.001). Among the perfusion parameters, K_ep (area under curve (AUC) 0.994) and V_p (AUC 0.992) were found to have the highest diagnostic value. In diffusion-weighted imaging, paragangliomas had a lower mean ADC compared to schwannomas (p < 0.001). The SUV_max and SUV_mean were significantly associated with K_trans , K_ep , and V_p in paragangliomas.

CONCLUSION

DCE-MRI in addition to DWI-MRI can accurately distinguish HNPGL from schwannoma and may replace the need for any additional imaging and preoperative biopsy in most cases.

Imaging of Bone Sarcomas and Soft-Tissue Sarcomas

BACKGROUND

 In the diagnosis of bone and soft-tissue sarcomas, the continuous advancement of various imaging modalities has improved the detection of small lesions, surgical planning, assessment of chemotherapeutic effects, and, importantly, guidance for surgery or biopsy.

METHOD

 This review was composed based on a PubMed literature search for the terms "bone sarcoma," "bone cancer" and "soft tissue sarcoma," "imaging," "magnetic resonance imaging", "computed tomography", "ultrasound", "radiography", and "radiomics" covering the publication period 2005-2020.

RESULTS AND CONCLUSION

 As discussed in this review, radiography, ultrasound, CT, and MRI all play key roles in the imaging evaluation of bone and soft-tissue sarcomas. In daily practice, advanced MRI techniques complement standard MRI but remain underused, as they are considered time-consuming, technically challenging, and not reliable enough to replace biopsy and histology. PET/MRI and radiomics have shown promise regarding the imaging of sarcomas in the future.

KEY POINTS

  · Radiographs remain crucial in diagnostic imaging algorithms for sarcomas.. · US is an initial imaging study for the evaluation of superficial soft-tissue tumors.. · The role of CT continues to evolve as new techniques emerge.. · MRI allows the noninvasive evaluation of soft-tissue, osseous, and articular structures.. · Machine learning methods could improve personalized selection of therapy for patients with sarcoma..

CITATION FORMAT

· Igrec J, Fuchsjäger MH. Imaging of Bone and Soft-Tissue Sarcomas. Fortschr Röntgenstr 2021; 193: 1171 - 1182.

Conventional and advanced MR imaging insights of synovial sarcoma

OBJECTIVES

Synovial sarcomas commonly involve extremities. The purpose of this study was to systematically assess and describe the appearance of pathologically proven synovial sarcomas on conventional MR sequences, diffusion weighted imaging and dynamic contrast enhanced imaging.

METHODS

In this cross-sectional retrospective study, fifteen pre-operative MRIs were analyzed separately by two musculoskeletal radiologists and a fellow. MRI features of synovial sarcomas were evaluated in a systematic fashion on conventional and advanced MR sequences.

RESULTS

The tumors demonstrated heterogeneous appearance on conventional MR sequences. Peritumoral edema was absent in four of 15 (27%) lesions including grade 2 and grade 3 tumors. Average minimum ADC was 0.8 × 10-3 mm²/s and average mean ADC was 1.2 × 10-3 mm²/s. There was avid early arterial phase enhancement on contrast imaging. Average relative enhancement of the tumors was 5.7 times compared to the adjacent skeletal muscle.

CONCLUSION

Synovial sarcomas demonstrate avid early arterial phase post-contrast enhancement on contrast images, low ADC values, and heterogeneous appearance on conventional MRI sequences. Peritumoral edema may be absent in such tumors despite being high grade tumors.

Soft tissue sarcomas: IVIM and DKI correlate with the expression of HIF-1α on direct comparison of MRI and pathological slices

OBJECTIVE

To investigate the correlation of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters with the expression of HIF-1α in soft tissue sarcoma (STS).

METHODS

This prospective study was approved by the institutional ethics committee. Written informed consent was obtained from all patients. Forty patients with STS who underwent 3.0 T MRI, including IVIM and DKI, were included in the study. Standard apparent diffusion coefficient (ADC), true ADC (D_slow), pseudo ADC (D_fast), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) of each lesion were independently analyzed by two observers. An MRI-pathology control method was used to ensure correspondence between the MRI slices and the pathological sections. Spearman analysis, independent sample t test, Mann-Whitney U test, chi-squared test, and receiver operating characteristic (ROC) curve analysis were performed.

RESULTS

D_slow and MD values showed a negative correlation with HIF-1α expression (r = - 0.469, - 0.588). MK and f values showed a positive correlation with HIF-1α expression (r = 0.779, 0.572). D_slow, MD, MK, and f values showed significant differences between the high- and low-expression groups. The MK value showed the best diagnostic ability. The optimal cut-off MK value of 0.604 was associated with 78.3% sensitivity and 88.2% specificity (area under the curve, 0.867).

CONCLUSIONS

This preliminary study demonstrated the association of IVIM and DKI parameters with the expression of HIF-1α in STS.

KEY POINTS

• IVIM and DKI parameters are correlated with the expression of HIF-1α in STS. • The MRI-pathology control method can be used in clinical studies to ensure correspondence between MRI slices and pathology sections.

Sarcoma treatment in the era of molecular medicine

Sarcomas are heterogeneous and clinically challenging soft tissue and bone cancers. Although constituting only 1% of all human malignancies, sarcomas represent the second most common type of solid tumors in children and adolescents and comprise an important group of secondary malignancies. More than 100 histological subtypes have been characterized to date, and many more are being discovered due to molecular profiling. Owing to their mostly aggressive biological behavior, relative rarity, and occurrence at virtually every anatomical site, many sarcoma subtypes are in particular difficult-to-treat categories. Current multimodal treatment concepts combine surgery, polychemotherapy (with/without local hyperthermia), irradiation, immunotherapy, and/or targeted therapeutics. Recent scientific advancements have enabled a more precise molecular characterization of sarcoma subtypes and revealed novel therapeutic targets and prognostic/predictive biomarkers. This review aims at providing a comprehensive overview of the latest advances in the molecular biology of sarcomas and their effects on clinical oncology; it is meant for a broad readership ranging from novices to experts in the field of sarcoma.

Soft tissue sarcoma: can dynamic contrast-enhanced (DCE) MRI be used to predict the histological grade?

OBJECTIVE

To determine if dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters reflect histological grade of soft tissue sarcoma (STS) MATERIALS AND METHODS: The medical records of 50 patients diagnosed with pathologically confirmed STS were retrospectively reviewed. Each STS was assessed with conventional contrast-enhanced MRI and DCE-MRI using a 3.0-T MRI system. The conventional MRI characteristics of low-grade (grade 1) and high-grade (grade 2 and grade 3) tumors were analyzed. Semi-quantitative parameters, including iAUC and TTP, and quantitative parameters, including K^trans, K_ep, and V_e, were derived from DCE-MRI. The diagnostic performances and optimal thresholds of various combinations of DCE-MRI parameters for predicting histological grades of STS were investigated using receiver operator characteristic (ROC) curves.

RESULTS

On conventional MRI, high-grade STSs were significantly larger (≥ 5 cm) and more likely to show a heterogeneous signal intensity on T₂WI (> 75%), peritumoral hyperintensity on T₂WI, or tumor necrosis (> 50%) compared with low-grade STS. On DCE-MRI, iAUC, TTP, K^trans, and K_ep were significant predictors of STS histological grade. K^trans had a high diagnostic value for differentiating between high-grade and low-grade STSs. The combination of iAUC, TTP, and K^trans yielded a higher AUC value (0.841) than the other models.

CONCLUSION

High-grade STSs were usually larger than low-grade STSs, had unclear boundaries, a heterogeneous signal intensity on T2-weighted image (T₂WI), and extensive necrosis. On DCE-MRI, iAUC, TTP, K^trans, and K_ep could differentiate between high-grade and low-grade STSs. The combination of iAUC, TTP, and K^trans had a high diagnostic performance for differentiating between STS histological grades.

Added-value of advanced magnetic resonance imaging to conventional morphologic analysis for the differentiation between benign and malignant non-fatty soft-tissue tumors

OBJECTIVES

To evaluate the added value of DWI, qualitative proton MR spectroscopy (H-MRS) and dynamic contrast-enhanced perfusion (DCE-P) to conventional MRI in differentiating benign and malignant non-fatty soft tissue tumors (NFSTT).

METHODS

From November 2009 to August 2017, 288 patients with NFSTT that underwent conventional and advanced MRI were prospectively evaluated. The study was approved by the local ethics committee. All patients signed an informed consent. A musculoskeletal (R1) and a general (R2) radiologist classified all tumors as benign, malignant, or indeterminate according to morphologic MRI features. Then, DWI, H-MRS, and DCE-P data of indeterminate tumors were analyzed by two additional radiologists (R3 and R4). Advanced techniques were considered individually and in combination for tumor benign-malignant differentiation using histology as the gold standard.

RESULTS

There were 104 (36.1%) malignant and 184 (63.9%) benign tumors. Conventional MRI analysis classified 99 tumors for R1 and 135 for R2 as benign or malignant, an accuracy for the identification of malignancy of 87.9% for R1 and 83.7% for R2, respectively. There were 189 indeterminate tumors for R1. For these tumors, the combination of DWI and H-MRS yielded the best accuracy for malignancy identification (77.4%). DWI alone provided the best sensitivity (91.8%) while the combination of DCE-P, DWI, and H-MRS yielded the best specificity (100%). The reproducibility of the advanced imaging parameters was considered good to excellent (Kappa and ICC > 0.86). An advanced MRI evidence-based evaluation algorithm was proposed allowing to characterize 28.1 to 30.1% of indeterminate non-myxoid tumors.

CONCLUSION

The prioritized use of advanced MRI techniques allowed to decrease by about 30% the number of non-myxoid NFSTT deemed indeterminate after conventional MRI analysis alone.

KEY POINTS

• When morphological characterization of non-fatty soft tissue tumors is possible, the diagnostic performance is high and there is no need for advanced imaging techniques. • Following morphologic analysis, advanced MRI techniques reduced by about 30% the number of non-myxoid indeterminate tumors. • DWI is the keystone of advanced imaging techniques yielding the best sensitivity (91.8%). Optimal specificity (> 90%) is obtained by a combination of advanced techniques.

Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?

OBJECTIVE

The strongest adverse prognostic factor in myxoid/round cell liposarcomas (MRC-LPS) is the presence of a round cell component above 5% within the tumor bulk. Its identification is underestimated on biopsies and in the neoadjuvant setting. The aim was to improve the prediction of patients' prognosis through a radiomics approach.

METHODS

Thirty-five out of 89 patients with MRC-LPS managed at our sarcoma reference center from 2008 to 2017 were included in this IRB-approved retrospective study as they presented with a pre-treatment contrast-enhanced MRI (median age, 49 years old). Two radiologists reported usual conventional/semantic radiological variables. After signal intensity (SI) normalization, voxel size standardization of T2-WI, and whole tumor volume segmentation, 44 3D-radiomics features were extracted. Using least absolute shrinkage and selection operator penalized Cox regression on prefiltered features, a radiomics score based on 3 weighted radiomics features was generated. Four prognostic multivariate models for MRFS were compared using concordance index: (1) clinical model, (2) semantic radiological model, (3) radiomics model, and (4) radiomics + semantic radiological model.

RESULTS

Twelve patients showed a metastatic relapse. The radiomics score included FOS_Skewness, GLRLM_LRHGE, and SHAPE_Volume and correlated with MRFS (hazard ratio = 19.37, p = 0.0009) and visual heterogeneity on T2-WI (p < 0.0001). A high score indicated a poorer prognosis. After adjustment, the best predictive performances were obtained with model (4) (concordance index = 0.937) and the lowest with model (1) (concordance index = 0.637).

CONCLUSION

Adding selected radiomics features that quantify tumor heterogeneity and shape at baseline to a conventional radiological analysis improves prediction of MRC-LPS patients' prognosis.

KEY POINTS

• Fourteen radiomics features quantifying shape and heterogeneity of myxoid/round cell liposarcomas on T2-WI were associated with metastatic relapse in univariate analysis. • A radiomics score based on 3 selected and weighted radiomics features was a strong and independent prognostic factor for metastatic relapse-free survival. • The best prediction of metastatic relapse-free survival for myxoid/round cell liposarcomas was achieved by combining the radiomics score to relevant radiological features.