Multiparametric quantitative analysis of tumor perfusion and diffusion with 3T MRI: differentiation between benign and malignant soft tissue tumors

Perfusion-weighted imaging with dynamic contrast enhancement (PWI/DCE) morphologic, qualitative, semiquantitative, and radiomics features predicting undifferentiated pleomorphic sarcoma (UPS) treatment response

Undifferentiated pleomorphic sarcoma (UPS) is the largest subgroup of soft tissue sarcomas. This study determined the value of perfusion-weighted imaging with dynamic-contrast-enhancement (PWI/DCE) morphologic, qualitative, and semiquantitative features for predicting UPS pathology-assessed treatment effect (PATE). This retrospective study included 33 surgically excised extremity UPS patients with pre-surgical MRI. Volumetric tumor segmentation from PWI/DCE was obtained at Baseline (BL), Post-Chemotherapy (PC), and Post-Radiation Therapy (PRT). The surgical specimens' PATE separated cases into Responders (R) (≥ 90%, 16 patients), Partial-Responders (PR) (89 - 31%, 10 patients), and Non-Responders (NR) (≤ 30%, seven patients). Seven semiquantitative kinetic parameters and maps were extracted from time-intensity curves (TICs), and 107 radiomic features were derived. Statistical analyses compared R vs. PR/NR. At PRT, 79% of R displayed a "Capsular" morphology (P = 1.49 × 10-7), and 100% demonstrated a TIC-type II (P = 8.32 × 10-7). 80% of PR showed "Unipolar" morphology (P = 1.03 × 10-5), and 60% expressed a TIC-type V (P = 0.06). Semiquantitative wash-in rate (WiR) was able to separate R vs. PR/NR (P = 0.0078). The WiR radiomics displayed significant differences in the first_order_10 percentile (P = 0.0178) comparing R vs. PR/NR at PRT. The PWI/DCE TIC-type II curve, low WiR, and "Capsular" enhancement represent PRT patterns typically observed in successfully treated UPS and demonstrate potential for UPS treatment response assessment.

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.

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.

Diffuse-Type Tenosynovial Giant Cell Tumor: What Are the Important Findings on the Initial and Follow-Up MRI?

Tenosynovial giant cell tumor (TSGCT) is a rare soft tissue tumor that involves the synovial lining of joints, bursae, and tendon sheaths, primarily affecting young patients (usually in the fourth decade of life). The tumor comprises two subtypes: the localized type (L-TSGCT) and the diffuse type (D-TSGCT). Although these subtypes share histological and genetic similarities, they present a different prognosis. D-TSGCT tends to exhibit local aggressiveness and a higher recurrence rate compared to L-TSGCT. Magnetic resonance imaging (MRI) is the preferred diagnostic tool for both the initial diagnosis and for treatment planning. When interpreting the initial MRI of a suspected TSGCT, it is essential to consider: (i) the characteristic findings of TSGCT-evident as low to intermediate signal intensity on both T1- and T2-weighted images, with a blooming artifact on gradient-echo sequences due to hemosiderin deposition; (ii) the possibility of D-TSGCT-extensive involvement of the synovial membrane with infiltrative margin; and (iii) the resectability and extent-if resectable, synovectomy is performed; if not, a novel systemic therapy involving colony-stimulating factor 1 receptor inhibitors is administered. In the interpretation of follow-up MRIs of D-TSGCTs after treatment, it is crucial to consider both tumor recurrence and potential complications such as osteoarthritis after surgery as well as the treatment response after systemic treatment. Given its prevalence in young adult patents and significant impact on patients' quality of life, clinical trials exploring new agents targeting D-TSGCT are currently underway. Consequently, understanding the characteristic MRI findings of D-TSGCT before and after treatment is imperative.

Computed Tomography and Magnetic Resonance Imaging Findings Contribute to Differentiating Solid- and Nonsolid-Type Adenoid Cystic Carcinoma in Maxillary Sinus

PURPOSE

This study aimed to evaluate the imaging features of maxillary sinus adenoid cystic carcinoma (ACC) on computed tomography (CT) and magnetic resonance imaging (MRI) and to investigate the imaging differences between solid and nonsolid maxillary sinus ACC.

METHODS

We retrospectively reviewed 40 cases of histopathologically confirmed ACC of the maxillary sinus. All the patients underwent CT and MRI. Based on the histopathological characteristics, the patients were classified into 2 groups: ( a ) solid maxillary sinus ACC (n = 16) and ( b ) nonsolid maxillary sinus ACC (n = 24). Imaging features such as tumor size, morphology, internal structure, margin, type of bone destruction, signal intensity, enhancement changes, and perineural tumor spread on CT and MRI, were evaluated. The apparent diffusion coefficient (ADC) was measured. Comparisons of imaging features and ADC values were performed between the solid and nonsolid maxillary sinus ACC using χ 2 and nonparametric tests.

RESULTS

The internal structure, margin, type of bone destruction, and degree of enhancement significantly differed between solid and nonsolid maxillary sinus ACC (all P < 0.05). The ADC of the solid maxillary sinus ACC was considerably lower than that of the nonsolid maxillary sinus ( P < 0.05).

CONCLUSIONS

Computed tomography and MRI may aid in the differentiation of solid and nonsolid types of maxillary sinus ACC.

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.

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.

ACR Appropriateness Criteria® Soft Tissue Masses: 2022 Update

Imaging should be performed in patients with a suspected soft tissue mass that cannot be clinically confirmed as benign. Imaging provides essential information necessary for diagnosis, local staging, and biopsy planning. Although the modalities available for imaging of musculoskeletal masses have undergone progressive technological advancements in recent years, their overall purpose in the setting of a soft tissue mass remains unchanged. This document identifies the most common clinical scenarios related to soft tissue masses and the most appropriate imaging for their assessment on the basis of the current literature. It also provides general guidance for those scenarios that are not specifically addressed. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Diagnostic Performance of Diffusion MRI for differentiating Benign and Malignant Nonfatty Musculoskeletal Soft Tissue Tumors: A Systematic Review and Meta-analysis

Objective: To evaluate the diagnostic performance of standard diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for differentiating benign and malignant soft tissue tumors (STTs).

Materials and methods: A thorough search was carried out to identify suitable studies published up to September 2020. The quality of the studies involved was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled sensitivity (SEN), specificity (SPE), and summary receiver operating characteristic (SROC) curve were calculated using bivariate mixed effects models. A subgroup analysis was also performed to explore the heterogeneity.

Results: Eighteen studies investigating 1319 patients with musculoskeletal STTs (malignant, n=623; benign, n=696) were enrolled. Thirteen standard DWI studies using the apparent diffusion coefficient (ADC) showed that the pooled SEN and SPE of ADC were 0.80 (95% CI: 0.77-0.82) and 0.63 (95% CI: 0.60-0.67), respectively. The area under the curve (AUC) calculated from the SROC curve was 0.806. The subgroup analysis indicated that the percentage of myxoid malignant tumors, magnet strength, study design, and ROI placement were significant factors affecting heterogeneity. Four IVIM studies showed that the AUCs calculated from the SROC curves of the parameters ADC and D were 0.859 and 0.874, respectively. The AUCs for the IVIM parameters pseudo diffusion coefficient (D*) and perfusion fraction (f) calculated from the SROC curve were 0.736 and 0.573, respectively. Two DKI studies showed that the AUCs of the DKI parameter mean kurtosis (MK) were 0.97 and 0.89, respectively.

Conclusion: The DWI-derived ADC value and the IVIM DWI-derived D value might be accurate tools for discriminating musculoskeletal STTs, especially for non-myxoid SSTs, using more than two b values, with maximal b value ranging from 600 to 800 s/mm², additionally, a high-field strength (3.0 T) optimizes the diagnostic performance.

Update on MR Imaging of Soft Tissue Tumors of Head and Neck

This article reviews soft tissue tumors of the head and neck following the 2020 revision of WHO Classification of Soft Tissue and Bone Tumours. Common soft tissue tumors in the head and neck and tumors are discussed, along with newly added entities to the classification system. Salient clinical and imaging features that may allow for improved diagnostic accuracy or to narrow the imaging differential diagnosis are covered. Advanced imaging techniques are discussed, with a focus on diffusion-weighted and dynamic contrast imaging and their potential to help characterize soft tissue tumors and aid in distinguishing malignant from benign tumors.

Role of diffusion-weighted MRI in evaluation of pediatric musculoskeletal soft tissue masses

Background

In pediatric patients, soft tissue masses encompass a wide heterogeneous group of benign and malignant lesions. MRI is a powerful diagnostic tool in the workup of soft tissue tumors in children, and it helps in characterization of lesion and evaluation of the extent of the lesion. However, conventional MRI techniques are not specific in differentiating benign from malignant lesions. So to improve characterization of tumors, DWI was added to MRI techniques as it increases sensitivity and specificity by detecting the micro-diffusion changes of water into intra- and extracellular spaces. The aim of this work was to highlight the diagnostic value of DWI in detection and characterization of different musculoskeletal soft tissue masses in pediatrics.

Results

There was a statistically significant difference regarding the mean ADC value of benign and malignant masses (P value = 0.001*). The mean ADC value for all benign masses (n = 41) was 1.495 ± 0.55 SD × 10–3 mm2/s, while the mean ADC value for all malignant masses (n = 21) was 0.449 ± 0.27 SD × 10–3 mm2/s. The cutoff ADC value between benign and malignant masses was 0.88 × 10–3 mm2/s. This cutoff ADC value has sensitivity of 100.0%, specificity of 92.3%, PPV of 66.7%, NPV of 100.0% and diagnostic accuracy of 93.3%.

Conclusion

In pediatric patients, DWI is an innovative valuable noninvasive imaging technique for characterization of musculoskeletal soft tissue masses and discrimination between benign and malignant masses.

Different Attenuation Models of Diffusion-Weighted MR Imaging for the Differentiation of Benign and Malignant Musculoskeletal Tumors

BACKGROUND

Several functional imaging techniques, including monoexponential diffusion-weighted imaging (m-DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis (DK) imaging, have been used in differentiating benign and malignant musculoskeletal tumors. Combining all three techniques in the same study population may improve differentiation.

PURPOSE

To compare the diagnostic performance of m-DWI, IVIM, and DK models and their combinations in differentiating benign and malignant musculoskeletal tumors.

STUDY TYPE

Prospective.

POPULATION

Fifty patients with benign and malignant musculoskeletal tumors divided into nonmyxoid and nonchondroid and myxoid and/or chondroid subgroups.

FIELD STRENGTH/SEQUENCE

A 1.5 T/m-DWI, IVIM, and DK single-shot spin-echo echo-planar sequences.

ASSESSMENT

Minimum and volumetric values of apparent diffusion coefficient (ADC), pure molecular diffusion (D_ivim ), pseudodiffusion (D*), perfusion fraction (f), diffusion coefficient for kurtosis model (D_K ), and Kurtosis (K) were compared between all benign and malignant tumors. Subgroup analysis was also performed for nonmyxoid and nonchondroid and myxoid and/or chondroid tumors.

STATISTICAL TESTS

Independent samples t-test, Mann-Whitney U test, intraclass correlation coefficient, ROC analysis, and logistic regression analysis. A P value < 0.05 was considered statistically significant.

RESULTS

ADC_min , D_ivim-min , D*_vol , D_K-min, K_vol, and K_min values showed statistically significant differences between all benign and malignant tumors and nonmyxoid and nonchondroid tumor subgroup. K_min showed the highest diagnostic performance in differentiating benign and malignant tumors with AUCs of 0.760 for "all tumors" and 0.825 for the nonmyxoid and nonchondroid tumor subgroup. No significant differences were detected in m-DWI-, IVIM-, and DK-derived parameters for differentiating benign and malignant myxoid and/or chondroid tumors. Only three of 63 combinations of prediction models demonstrated a higher diagnostic performance than K_min ; however, improvements were not significantly different.

DATA CONCLUSION

ADC_min , D_ivim-min , D*_vol , D_K-min , K_vol , and K_min values can be used to differentiate benign and malignant musculoskeletal tumors. Our findings suggest that the added value of multiparametric approach in such differentiation is not significant.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.