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.

The Effect of chemo- and radiotherapy on tumor necrosis in soft tissue sarcoma- does it influence prognosis?

BACKGROUND

Soft tissue sarcomas (STSs) are a heterogeneous group of tumors. Wide surgical resection is standard, often combined with neoadjuvant chemotherapy, radiotherapy, or both. Studies have shown the predictive value of tumor necrosis in bone sarcoma (BS); however, the role of necrosis in STS after neoadjuvant therapies is still unclear. This study aimed to investigate the role of chemo- and radiotherapy in the formation of tumor necrosis and to evaluate the influence of tumor necrosis on overall survival and local recurrence-free survival. Data from BS patients and patients who did not receive neoadjuvant therapy were compared.

METHODS

A total of 779 patients with STS or BS were treated surgically. In all patients, tumor-specific factors such as type, size, or grading and the type of adjuvant therapy were documented. Local recurrence (LR), the diagnosis of metastatic disease, and survival during follow-up were evaluated.

RESULTS

A total of 565 patients with STS and 214 with BS were investigated. In STS, 24.1% G1 lesions, 34.1% G2 lesions, and 41.8% G3 lesions were observed. Two hundred twenty-four of the patients with STS and neoadjuvant therapy had either radiotherapy (RTx) (n = 80), chemotherapy (CTx) (n = 93), or both (n = 51). Three hundred forty-one had no neoadjuvant therapy at all. In STS, tumor necrosis after neoadjuvant treatment was significantly higher (53.5%) than in patients without neoadjuvant therapy (15.7%) (p < 0.001). Patients with combined neoadjuvant chemo-/radiotherapy had substantially higher tumor necrosis than those with radiotherapy alone (p = 0.032). There was no difference in tumor necrosis in patients with combined chemo-/radiotherapy and chemotherapy alone (p = 0.4). The mean overall survival for patients with STS was 34.7 months. Tumor necrosis did not influence survival in a subgroup of G2/3 patients. In STS with no neoadjuvant therapy and grading of G2/3, the correlation between necrosis and overall survival was significant (p = 0.0248). There was no significant correlation between local recurrence (LR) and necrosis.

CONCLUSION

STS shows a broad spectrum of necrosis even without neoadjuvant chemo- or radiotherapy. After CTx or/and RTx necrosis is enhanced and is significantly pronounced with a combination of both. There is a trend toward higher necrosis with CTx than with RTx. Grading substantially influences the necrosis rate, but necrosis in soft-tissue sarcoma following neoadjuvant therapy does not correlate with better survival or a lower local recurrence rate, as in bone sarcomas.

Artificial Intelligence in Oncological Hybrid Imaging

BACKGROUND

 Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes.

METHODS AND RESULTS

 The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations.

CONCLUSION

 AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation.

KEY POINTS

  · Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making..

Intratumoral Heterogeneity of Fibrosarcoma Xenograft Models: Whole-Tumor Histogram Analysis of DWI and IVIM

RATIONAL AND OBJECTIVE

To explore the correlations of histogram parameters from diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) with the heterogeneous features in a nude mouse model of fibrosarcoma.

MATERIALS AND METHODS

A total of 44 fibrosarcoma xenograft models were established by inoculating HT-1080 cells on the right thigh of mice and subjected tumors to DWI and IVIM imaging with 3.0 T MRI. Whole-tumor histogram parameters were calculated on apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f). Heterogeneous features, including necrosis rate, cell density, Ki-67 labeling index (LI), and microvascular density (MVD) were measured. Intraclass correlation coefficients (ICC), Pearson or Spearman correlation tests, and receiver operating characteristics (ROC) were performed.

RESULTS

The 90th percentile, skewness and kurtosis of ADC and D histograms showed correlations with necrosis rate, and the highest correlation coefficient was found for D90th (r = 0.485). ADC and D histogram parameters showed correlations with cell density and Ki-67 LI; D90th showed the highest correlation coefficient with cell density (r = -0.504); and Dmedian showed the most significant correlation with Ki-67 LI (r = -0.525). D*skewness, D*kurtosis, D*90th, fmean, and fmedian showed correlations with MVD. ADC90th, ADCskewness, ADCkurtosis, D90th, and Dskewness showed significant differences between the low necrosis and high necrosis groups, and the combination model showed the best diagnostic ability (AUC = 0.882), with 97% sensitivity, and 72.7% specificity.

CONCLUSION

Whole-tumor histogram parameters of DWI and IVIM were correlated with heterogeneous features in nude murine models of fibrosarcoma.

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.

Artificial Intelligence in Oncological Hybrid Imaging

BACKGROUND

Artificial intelligence (AI) applications have become increasingly relevant across a broad spectrum of settings in medical imaging. Due to the large amount of imaging data that is generated in oncological hybrid imaging, AI applications are desirable for lesion detection and characterization in primary staging, therapy monitoring, and recurrence detection. Given the rapid developments in machine learning (ML) and deep learning (DL) methods, the role of AI will have significant impact on the imaging workflow and will eventually improve clinical decision making and outcomes.

METHODS AND RESULTS

The first part of this narrative review discusses current research with an introduction to artificial intelligence in oncological hybrid imaging and key concepts in data science. The second part reviews relevant examples with a focus on applications in oncology as well as discussion of challenges and current limitations.

CONCLUSION

AI applications have the potential to leverage the diagnostic data stream with high efficiency and depth to facilitate automated lesion detection, characterization, and therapy monitoring to ultimately improve quality and efficiency throughout the medical imaging workflow. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based therapy guidance in oncology. However, significant challenges remain regarding application development, benchmarking, and clinical implementation.

KEY POINTS

· Hybrid imaging generates a large amount of multimodality medical imaging data with high complexity and depth.. · Advanced tools are required to enable fast and cost-efficient processing along the whole radiology value chain.. · AI applications promise to facilitate the assessment of oncological disease in hybrid imaging with high quality and efficiency for lesion detection, characterization, and response assessment. The goal is to generate reproducible, structured, quantitative diagnostic data for evidence-based oncological therapy guidance.. · Selected applications in three oncological entities (lung, prostate, and neuroendocrine tumors) demonstrate how AI algorithms may impact imaging-based tasks in hybrid imaging and potentially guide clinical decision making..

CITATION FORMAT

· Feuerecker B, Heimer M, Geyer T et al. Artificial Intelligence in Oncological Hybrid Imaging. Fortschr Röntgenstr 2023; 195: 105 - 114.

High-throughput screening of caterpillars as a platform to study host-microbe interactions and enteric immunity

Mammalian models of human disease are expensive and subject to ethical restrictions. Here, we present an independent platform for high-throughput screening, using larvae of the tobacco hornworm Manduca sexta, combining diagnostic imaging modalities for a comprehensive characterization of aberrant phenotypes. For validation, we use bacterial/chemical-induced gut inflammation to generate a colitis-like phenotype and identify significant alterations in morphology, tissue properties, and intermediary metabolism, which aggravate with disease progression and can be rescued by antimicrobial treatment. In independent experiments, activation of the highly conserved NADPH oxidase DUOX, a key mediator of gut inflammation, leads to similar, dose-dependent alterations, which can be attenuated by pharmacological interventions. Furthermore, the developed platform could differentiate pathogens from mutualistic gastrointestinal bacteria broadening the scope of applications also to microbiomics and host-pathogen interactions. Overall, larvae-based screening can complement mammals in preclinical studies to explore innate immunity and host-pathogen interactions, thus representing a substantial contribution to improve mammalian welfare.

Improved risk stratification by PET-based intratumor heterogeneity in children with high-risk neuroblastoma

PURPOSE

The substratification of high-risk neuroblastoma is challenging, and new predictive imaging biomarkers are warranted for better patient selection. The aim of the study was to evaluate the prognostic role of PET-based intratumor heterogeneity and its potential ability to improve risk stratification in neuroblastoma.

METHODS

Pretreatment 18F-FDG PET/CT scans from 112 consecutive children with newly diagnosed neuroblastoma were retrospectively analyzed. The primary tumor was segmented in the PET images. SUVs, volumetric parameters including metabolic tumor volume (MTV) and total lesion glycolysis (TLG), and texture features were extracted. After the exclusion of imaging features with poor and moderate reproducibility, the relationships between the imaging indices and clinicopathological factors, as well as event-free survival (EFS), were assessed.

RESULTS

The median follow-up duration was 33 months. Multivariate analysis showed that PET-based intratumor heterogeneity outperformed clinicopathological features, including age, stage, and MYCN, and remained the most robust independent predictor for EFS [training set, hazard ratio (HR): 6.4, 95% CI: 3.1-13.2, p < 0.001; test set, HR: 5.0, 95% CI: 1.8-13.6, p = 0.002]. Within the clinical high-risk group, patients with a high metabolic heterogeneity showed significantly poorer outcomes (HR: 3.3, 95% CI: 1.6-6.8, p = 0.002 in the training set; HR: 4.4, 95% CI: 1.5-12.9, p = 0.008 in the test set) compared to those with relatively homogeneous tumors. Furthermore, intratumor heterogeneity outran the volumetric indices (MTVs and TLGs) and yielded the best performance of distinguishing high-risk patients with different outcomes with a 3-year EFS of 6% vs. 47% (p = 0.001) in the training set and 9% vs. 51% (p = 0.004) in the test set.

CONCLUSION

PET-based intratumor heterogeneity was a strong independent prognostic factor in neuroblastoma. In the clinical high-risk group, intratumor heterogeneity further stratified patients with distinct outcomes.

Voxel-wise supervised analysis of tumors with multimodal engineered features to highlight interpretable biological patterns

BACKGROUND

Translation of predictive and prognostic image-based learning models to clinical applications is challenging due in part to their lack of interpretability. Some deep-learning-based methods provide information about the regions driving the model output. Yet, due to the high-level abstraction of deep features, these methods do not completely solve the interpretation challenge. In addition, low sample size cohorts can lead to instabilities and suboptimal convergence for models involving a large number of parameters such as convolutional neural networks.

PURPOSE

Here, we propose a method for designing radiomic models that combines the interpretability of handcrafted radiomics with a sub-regional analysis.

MATERIALS AND METHODS

Our approach relies on voxel-wise engineered radiomic features with average global aggregation and logistic regression. The method is illustrated using a small dataset of 51 soft tissue sarcoma (STS) patients where the task is to predict the risk of lung metastasis occurrence during the follow-up period.

RESULTS

Using positron emission tomography/computed tomography and two magnetic resonance imaging sequences separately to build two radiomic models, we show that our approach produces quantitative maps that highlight the signal that contributes to the decision within the tumor region of interest. In our STS example, the analysis of these maps identified two biological patterns that are consistent with STS grading systems and knowledge: necrosis development and glucose metabolism of the tumor.

CONCLUSIONS

We demonstrate how that method makes it possible to spatially and quantitatively interpret radiomic models amenable to sub-regions identification and biological interpretation for patient stratification.

Necrosis on pre-radiotherapy 18F-FDG PET/CT is a predictor for complete metabolic response in patients with non-small cell lung cancer

To investigate necrosis on pre-radiotherapy (RT) 18F-FDG PET/CT (PETNECROSİS) as a predictor of complete metabolic response (CMR) in patients with non-small cell lung cancer (NSCLC).We evaluated patients with inoperable stage I-III NSCLC who underwent pre- and post-radiotherapy 18F-FDG PET/CT. The relationship between CMR and PETNECROSIS, SUVmax, gross tumor volume calculated with 18F-FDG PET/CT (GTVPET-CT), tumor size, histology, metabolic tumor volume (MTV), and RT dose was assessed using logistic regression analysis. To evaluate necrosis on 18F FDG PET/CT, we drew a region of interest (ROI) in the area showing visually very low/or no fluorodeoxyglucose (FDG) uptake on PET images. If the SUVmax was lower than the blood pool SUVmax and showed significantly lower attenuation (10-30 Hounsfield units [HU]) from the surrounding tissue on non-intravenous contrast-enhanced low-dose correlative CT, we defined it as necrotic (PETNECROSİS).Fifty-three patients were included in this study. The mean age was 68.1 ± 9.8 years. Twenty-one patients had adenocarcinoma, and 32 had squamous cell carcinoma. All parameters were independent of histologic status. Multivariate logistic regression analysis showed that SUVmax ≤11.6 vs >11.6, (P = .003; OR, 7.670, 95CI%: 2.013-29.231) and PETNECROSİS absence/presence were independent predictors for CMR (P = .028, OR: 6.704, 95CI% 1.214-30.394).The necrosis on 18F FDG PET/CT and SUVmax > 11.6 could be an imaging marker for the complete metabolic response after definitive chemoradiotherapy or definitive RT alone in patients with NSCLC.

Clinical value of baseline 18F-FDG PET/CT in soft tissue sarcomas

Background

The use of ¹⁸F-FDG Positron emission tomography/Computed tomography (PET/CT) in the initial staging of many cancers is clearly established. Most soft tissue sarcoma (STS) has a high affinity for ¹⁸F-FDG, which is why ¹⁸F-FDG PET/CT has been proposed as a non-invasive method, useful in diagnosis and follow-up. The standardized uptake value values (SUV), the volume-based metabolic parameters MTV (metabolic tumor volume), and TLG (total lesion glycolysis) determine tumor viability and provide its total volume and the total activity of metabolically active tumor cells. The histological grade is the most important predictor of metastases and mortality associated with STS, and a significant relationship between the metabolic parameters of ¹⁸F-FDG PET/CT and the histological grade has been described.

Methods

A retrospective study was conducted on STS patients, who had histological grade according to the FNCLCC (Fédération Nationale des Centres de Lutte Contre Le Cancer) criteria, as well as a baseline PET/CT. SUV (SUV_max, SUV_mean, and SUV_peak), MTV, and TLG were quantified. A T-student test was performed to establish the relationship between the metabolic biomarkers and the histological grade. Their usefulness as predictors of the histological grade was verified using receiver operator characteristic (ROC) curves. A survival function study was performed using the Kaplan–Meier method. To assess the prognostic utility of the metabolic biomarkers we use the Log-Rank method.

Results

The SUV values were useful to discriminate high-grade STS. We found a significant relationship between the histological grade and the SUV values. SUV_max, SUV_peak, MTV, and TLG were predictors of overall survival (OS). There were no significant differences in the OS for the SUV_mean, or in the disease-free survival (DFS) for SUV_max, SUV_mean, SUV_peak, MTV, and TLG.

Conclusions

The SUV_max, SUV_mean, and SUV_peak values correlate with the HG and are useful to discriminate high-grade from low-grade STS. Patients with high SUV_max, SUV_peak, MTV, and TLG have a significantly lower OS.

Utility of 18F-FDG-PET/CT in management and prognostication of treatment naïve late-stage soft tissue sarcomas

OBJECTIVE

This study evaluated the utility of 18F-fluorodexoyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in staging, grading, and prognostication of Stage III and IV soft tissue sarcomas (STSs).

METHODS

Forty patients (Median age = 32.5 years; 25 men) with histologically proven STSs, prospectively underwent 18F-FDG-PET/CTs at baseline. Three-dimensional region of interests were drawn encompassing the lesions to calculate standardized uptake values (SUVs) and metabolic tumor volumes (MTVs). After segmentation, Haralick statistical texture analysis was performed. Follow-up was available for 35 patients. Survival at 6 months was 71.4% and at 1 year was 57.1%.

RESULTS

American Joint Committee on Cancer Stage III was seen in 23 and Stage IV in 17 patients. None of the baseline quantitative and semi-quantitative parameters could predict response or progression. Only reduction in SUVmax in interim PET/CT correlated with baseline SUVmax (Spearman's Rho = 0.533; P = 0.019). Textural parameters namely 'contrast' in CT (P = 0.039) and 'difference entropy' in PET/CT (P = 0.051) could differentiate intermediate from high-grade lesions, with corresponding area under curves being 0.736 (0.533-0.889) and 0.700 (0.518-0.882). M1 disease [Hazard ratio (HR): 3.184 (1.179-8.595); P = 0.022], absence of surgical treatment [HR 0.305 (0.106-0.873), P = 0.027 with surgery], lower MTV/total tumor volume (TTV) [HR: 0.975 (0.953-0.997; P = 0.028] and progressive disease in interim PET/CT [3.483 (0.898-13.515); P = 0.056] were predictors of lower survival in univariate analysis. Only M1 disease was found to be reaching significance in multivariate analysis [HR = 2.683 (0.949-7.580); P = 0.063]. Baseline PET/CT changed management in 12.5% of patients [compared to local-imaging and high-resolution CT chest]; with detection of extra-pulmonary metastases. Though, interim and end of treatment PET/CTs detected more metastatic lesions, management was not impacted.

CONCLUSION

18F-FDG-PET/CT allows for more accurate M-staging in late-stage STSs, which in turn influences the option of curative surgical resection and thus impacts patient prognosis. Lower baseline MTV/TTV and progression in interim PET/CT are also associated with lower survival. Textural analysis may have a role in noninvasive grading.

The role of 18F-FDG PET/CT in soft tissue sarcoma

INTRODUCTION

Soft tissue sarcomas (STS) are highly fluorine-18-fluorodeoxyglucose (F-FDG)-avid tumours. PET seems to be effective for the assessment of the extent of disease. However, the use of PET to stratify STS into different risk histotypes still remains controversial. Our aim was to evaluate F-FDG uptake in different STS types and to assess the prognostic value of the maximum standardized uptake value (SUVmax).

PATIENTS AND METHODS

We reviewed 50 adult patients with primary high-grade STS of the extremities with a preoperative PET. Overall survival and local recurrence were analysed.

RESULTS

The mean SUVmax was 12.9 (range: 2.2-33.4). All cases of myxoid liposarcoma and all cases of synovial sarcoma had SUVmax of less than 10.3. A better overall survival and local recurrence were observed in patients with SUVmax of less than 10.3 (P=0.005 and 0.046, respectively).

CONCLUSION

SUVmax seems to be specific among different STS histotypes. PET does not seem to be useful in myxoid liposarcoma as well as synovial sarcoma as these tumours seem to have a low uptake of glucose. SUVmax might also be included as a prognostic factor.

The Future of Radiation Oncology in Soft Tissue Sarcoma

Radiotherapy (RT) is an important component of the treatment of soft tissue sarcomas (STS) and has been traditionally incorporated with a homogenous approach despite the reality that STS displays a known heterogeneity in clinicopathologic features and treatment outcomes. In this article, we explore the principle components of personalized medicine, including genomics, radiomics, and treatment response, along with their impact on the future of radiation therapy for STS. We propose a shift in the treatment paradigm for STS from a one-size-fits-all technique to one that implements the tenets of personalized medicine and includes the framework for a potential clinical trial technique in this heterogeneous disease.

Future Perspective of the Application of Positron Emission Tomography-Computed Tomography-MR Imaging in Musculoskeletal Disorders

Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) is the imaging method of choice in sarcoma patients. PET may help in diagnosis, grading, staging, biopsy guidance, monitoring response to therapy, restaging for recurrence, and prognosis. 18F-FDG-PET/MRI combines the higher tissue contrast of MRI in the study of soft-tissue lesions and the peculiarities of PET imaging that allow the characterization of tissues. The use of 18F-FDG-PET/MRI in these patients has reduces the radiation dose, which is of great importance, particularly in children. Data support the routine use of 18F-FDG-PET either using CT or MRI in patients with sarcoma.

Probabilistic classification of tumour habitats in soft tissue sarcoma

The purpose of this work is to propose a method to characterize tumour heterogeneity on MRI, using probabilistic classification based on a reference tissue. The method uses maps of the apparent diffusion coefficient (ADC), T₂ relaxation, and a calculated map representing high-b-value diffusion-weighted MRI (denoted simDWI) to identify up to five habitats (i.e. sub-regions) of tumours. In this classification method, the parameter values (ADC, T₂ , and simDWI) from each tumour voxel are compared against the corresponding parameter probability distributions in a reference tissue. The probability that a tumour voxel belongs to a specific habitat is the joint probability for all parameters. The classification can be visualized using a custom colour scheme. The proposed method was applied to data from seven patients with biopsy-confirmed soft tissue sarcoma, at three time-points over the course of pre-operative radiotherapy. Fast-spin-echo images with two different echo times and diffusion MRI with three b-values were obtained and used as inputs to the method. Imaging findings were compared with pathology reports from pre-radiotherapy biopsy and post-surgical resection. Regions of hypercellularity, high-T₂ proteinaceous fluid, necrosis, collagenous stroma, and fibrosis were identified within soft tissue sarcoma. The classifications were qualitatively consistent with pathological observations. The percentage of necrosis on imaging correlated strongly with necrosis estimated from FDG-PET before radiotherapy (R²  = 0.97) and after radiotherapy (R²  = 0.96). The probabilistic classification method identifies realistic habitats and reflects the complex microenvironment of tumours, as demonstrated in soft tissue sarcoma.

18F-fluorodeoxyglucose positron emission tomography is correlated with the pathological necrosis and decreased microvessel density in lung adenocarcinomas

OBJECTIVE

We explored the relationship between preoperative ¹⁸F-FDG-PET parameters, tumor necrosis, and microvessel density (MVD) in patients with pulmonary adenocarcinomas.

METHODS

A total of 164 patients, who underwent surgical resection for lung adenocarcinoma, were reviewed retrospectively. The maximum standardized uptake value (SUV_max), peak SUV corrected for lean body mass (SUL_peak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) values were measured by preoperative ¹⁸F-FDG-PET. The extent of tumor necrosis was examined and CD31 expression was evaluated to count the MVD.

RESULTS

The SUV_max, SUL_peak, MTV, and TLG levels were significantly lower in patients exhibiting no necrosis compared to those with necrosis. When we divided the patients into two groups based on high vs. low PET parameter values, elevated SUV_max, SUL_peak, MTV, and TLG values were significantly more associated with partial or diffuse necrosis than were lower values (p < 0.001). A negative correlation was evident between the MVD and SUV_max, MVD and SUL_peak, MVD and MTV, and MVD and TLG. Tumor necrosis was correlated with a shorter overall survival (OS) (p = 0.007) and recur-free survival (RFS) (p < 0.001). However, multivariate analysis revealed that necrosis was not of prognostic significance. The SUV_max, MTV and TLG were associated with inferior OS or RFS rates in univariate analysis, however, not in multivariate analysis.

CONCLUSION

High-level FDG accumulation is correlated with tumor necrosis in lung adenocarcinoma.

In vivo, noninvasive functional measurements of bone sarcoma using diffuse optical spectroscopic imaging

Diffuse optical spectroscopic imaging (DOSI) is an emerging near-infrared imaging technique that noninvasively measures quantitative functional information in thick tissue. This study aimed to assess the feasibility of using DOSI to measure optical contrast from bone sarcomas. These tumors are rare and pose technical and practical challenges for DOSI measurements due to the varied anatomic locations and tissue depths of presentation. Six subjects were enrolled in the study. One subject was unable to be measured due to tissue contact sensitivity. For the five remaining subjects, the signal-to-noise ratio, imaging depth, optical properties, and quantitative tissue concentrations of oxyhemoglobin, deoxyhemoglobin, water, and lipids from tumor and contralateral normal tissues were assessed. Statistical differences between tumor and contralateral normal tissue were found in chromophore concentrations and optical properties for four subjects. Low signal-to-noise was encountered during several subject's measurements, suggesting increased detector sensitivity will help to optimize DOSI for this patient population going forward. This study demonstrates that DOSI is capable of measuring optical properties and obtaining functional information in bone sarcomas. In the future, DOSI may provide a means to stratify treatment groups and monitor chemotherapy response for this disease.

Prognostic value of 18F-FDG PET-CT-based functional parameters in patients with soft tissue sarcoma: A meta-analysis

BACKGROUND

Considering the clinical importance of high 5-year mortality, we performed a meta-analysis of maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) from F-FDG PET-CT for overall survival (OS) and progression-free survival (PFS) in patients with soft tissue sarcoma.

METHODS

The search and selection of eligible articles was conducted on PubMed and EMBASE. We applied hazard ratio (HR) and odd ratio (OR) to measure the correlation between SUVmax, MTV, and TLG with PFS and OS. The SUVmax was analyzed through subgroup in terms of histological grade and HR of posttreatment SUVmax was also assessed.

RESULTS

Eleven studies with 582 patients were included. The pooled HRs of pretreatment SUVmax were 2.40 (95% CI: 1.38-4.17) for OS and 2.20 (95% CI: 1.47-3.30) for PFS. The HRs in terms of OS were 3.20 (95% CI: 1.71-5.98) based on MTV and 5.20 (95% CI: 2.34-11.56) based on TLG. Meanwhile, the predict results of pretreatment SUVmax on OR remained significant and the HRs of posttreatment SUVmax were 2.25 (95% CI: 1.33-3.80) for OS and 2.87 (95% CI: 1.81-4.55) for PFS.

CONCLUSIONS

The pretreatment SUVmax, MTV, and TLG of F-FDG PET-CT showed significant prognostic value for OS and the PET-CT can be used in identifying high-risk patients about progression and survival. The analysis for posttreatment SUVmax suggested PET-CT as a promising equipment in monitoring therapy response.

The role of FDG PET/CT in patients treated with neoadjuvant chemotherapy for localized bone sarcomas

Purpose

The histological response to neoadjuvant chemotherapy is an important prognostic factor in patients with osteosarcoma (OS) and Ewing sarcoma (EWS). The aim of this study was to assess baseline primary tumour FDG uptake on PET/CT, and serum values of alkaline phosphatase (ALP) and lactate dehydrogenase (LDH), to establish whether these factors are correlated with tumour necrosis and prognosis.

Methods

Patients treated between 2009 and 2014 for localized EWS and OS, who underwent FDG PET/CT as part of their staging work-up, were included. The relationships between primary tumour SUVmax at baseline (SUV1), SUVmax after induction chemotherapy (SUV2), metabolic response calculated as [(SUV1 − SUV2)/SUV1)] × 100, LDH and ALP and tumour response/survival were analysed. A good response (GR) was defined as tumour necrosis >90 % in patients with OS, and grade II-III Picci necrosis (persitence of microscopic foci only or no viable tumor) in patients with Ewing sarcoma.

Results

The study included 77 patients, 45 with EWS and 32 with OS. A good histological response was achieved in 53 % of EWS patients, and 41 % of OS patients. The 3-year event-free survival (EFS) was 57 % in EWS patients and 48 % OS patients. The median SUV1 was 5.6 (range 0 – 17) in EWS patients and 7.9 (range 0 – 24) in OS patients (p = 0.006). In EWS patients the GR rate was 30 % in those with a high SUV1 (≥6) and 72 % in those with a lower SUV1 (p = 0.0004), and in OS patients the GR rate was 29 % in those with SUV1 ≥6 and 64 % in those with a lower SUV1 (p = 0.05). In the univariate analysis the 3-year EFS was significantly better in patients with a low ALP level (59 %) than in those with a high ALP level (22 %, p = 0.02) and in patients with a low LDH level (62 %) than in those with a high LDH level (37 %, p = 0.004). In EWS patients the 3-year EFS was 37 % in those with a high SUV1 and 75 % in those with a low SUV1 (p = 0.004), and in OS patients the 3-year EFS was 32 % in those with a high SUV1 and 66 % in those with a low SUV1 (p = 0.1). Histology, age and gender were not associated with survival. In the multivariate analysis, SUV1 was the only independent pretreatment prognostic factor to retain statistical significance (p = 0.017). SUV2 was assessed in 25 EWS patients: the median SUV2 was 1.9 (range 1 – 8). The GR rate was 20 % in patients with a high SUV2, and 67 % in those with a low SUV2 (p = 0.02). A good metabolic response (SUV reduction of ≥55 %) was associated with a 3-year EFS of 80 % and a poor metabolic response with a 3-year EFS of 20 % (p = 0.05). In the OS patients the median SUV2 was 2.7 (range 0 – 4.5). Neither SUV2 nor the metabolic response was associated with outcome in OS patients.

Conclusion

FDG PET/CT is a useful and noninvasive tool for identifying patients who are more likely to be resistant to chemotherapy. If this finding is confirmed in a larger series, SUV1, SUV2 and metabolic response could be proposed as factors for stratifying EWS patients to identify those with high-grade localized bone EWS who would benefit from risk-adapted induction chemotherapy.

Prognostic significance of (18)F-FDG PET at diagnosis in patients with soft tissue sarcoma and bone sarcoma; systematic review and meta-analysis

PURPOSE

The usefulness of (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) for the survival prognosis in soft tissue sarcoma (STS) and bone sarcoma (BS) is controversial. The objective of this systematic review was to provide an up-to-date and unprecedented summary of the prognostic value of (18)F-FDG PET at diagnosis in STS and BS.

METHODS

Studies evaluating pre-treatment (18)F-FDG PET for overall survival of STS and BS were systematically searched for in MEDLINE, EMBASE, and Web of Science. Comparative analyses of the pooled hazard ratios (HR) of overall survival were performed between patients with high and low maximum standardised uptake value (SUVmax). The quality of study designs was evaluated using the Newcastle-Ottawa scale (NOS) for quality assessment of cohort studies. P < 0.05 was defined as statistically significant.

RESULTS

A total of six studies comprising 514 patients with STS and BS were considered for the meta-analysis. The pooled HR for overall survival was 1.22 (95% confidence interval: 1.03-1.46), suggesting that high SUVmax predicts a significantly shorter overall survival period than low SUVmax (P = 0.03). Additional subgroup analyses using patients with STS alone showed that high SUVmax might predict poorer overall survival than low SUVmax (P = 0.004), although only two studies consisting of 96 patients were included. The overall quality of the included studies evaluated by the NOS assessment was adequate.

CONCLUSION

(18)F-FDG PET at diagnosis provides a very useful predictive tool for patients with STS and BS.

(18)F-FDG PET/MRI for therapy response assessment in sarcoma: comparison of PET and MR imaging results

BACKGROUND

(18)F-Fluorodeoxyglucose (FDG) positron emission tomography (PET) has proven to be of substantial benefit in imaging of sarcoma patients. We therefore investigated the feasibility and benefit of combined PET/magnetic resonance imaging (MRI).

METHODS

Twelve patients with sarcoma who underwent FDG PET/MRI for staging and response assessment after chemotherapy were included.

RESULTS

Based on contrast-enhanced MRI and application of Choi criteria, therapy response was classified as stable disease in 6/12 patients (50%) and as partial remission in 6/12 patients (50%).

CONCLUSION

In sarcoma patients, response assessment using Choi criteria based on contrast-enhanced MRI in comparison to FDG PET imaging only demonstrates slight correlation.

Value of FDG PET/CT in Patient Management and Outcome of Skeletal and Soft Tissue Sarcomas

Fluorodeoxyglucose (FDG)-PET/computed tomography (CT) has been increasingly used in bone and soft tissue sarcomas and provides advantages in the initial tumor staging, tumor grading, therapy assessment, and recurrence detection. FDG-PET/CT metabolic parameters are reliable predictors of survival in sarcomas and could be implemented in risk stratification models along with other prognostic factors in these patients.

Evaluation of imaging utilization prior to referral of musculoskeletal tumors: a prospective study

BACKGROUND

Imaging studies are essential when evaluating a patient with a musculoskeletal neoplasm, and they represent a potential waste of resources when used inappropriately. The objective of this study was to prospectively evaluate a consecutive series of patients for inappropriate utilization of imaging prior to referral to a tertiary care facility. Our hypothesis was that advanced imaging is overutilized prior to referral of musculoskeletal neoplasms to a tertiary care center.

METHODS

All new patients referred for evaluation of a musculoskeletal neoplasm were prospectively analyzed over a three-month time period. All pre-referral imaging studies were recorded, including radiographs, computed tomographic scans, magnetic resonance imaging scans, bone scans, and 18-fluorodeoxyglucose positron emission tomography scans. Studies were reviewed by two musculoskeletal radiologists and two orthopaedic oncologists and were defined with use of specific preselected criteria as inappropriate if they were not indicated for diagnosis or treatment, if they required repeating because of excessive time since the study was obtained, or if they had poor image quality or technique.

RESULTS

We evaluated 298 consecutive patients (550 imaging studies). The inappropriate utilization rate was 1.5% (three of 204) for radiographs, 36.5% (twenty-three of sixty-three) for computed tomographic scans, 26.7% (fifty-six of 210) for magnetic resonance imaging scans, 45.1% (twenty-three of fifty-one) bone scans, and 45.5% (ten of twenty-two) for positron emission tomography scans. The overall inappropriate use of advanced imaging (magnetic resonance imaging, computed tomography, bone scan, positron emission tomography) was 32.4% (112 of 346 images). With regard to inappropriate use of magnetic resonance imaging, there was no difference between orthopaedic surgeons (28.2%) and primary care physicians (26.5%).

CONCLUSIONS

Our data indicate a high prevalence (32.4%) of inappropriate advanced imaging of musculoskeletal tumors prior to referral. This represents a substantial cost to the patient and health-care system, a potential delay of referral, an increase in radiation exposure, and identification of other incidental findings.

Prognostic value of 18F-FDG PET/CT in patients with soft tissue sarcoma: comparisons between metabolic parameters

OBJECTIVES

To investigate the relationship between volume-based PET parameters and prognosis in patients with soft tissue sarcoma (STS).

METHODS

We retrospectively reviewed 55 patients with pathologically proven STS who underwent pretreatment with (18) F-Fluorodeoxyglucose ((18)F-FDG) PET/CT. The maximum standardized uptake value (SUVmax), average SUV (SUVavg), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of primary tumors were measured using a threshold SUV as liver activity for determining the boundary of tumors. Univariate and multivariate survival analyses for overall survival were performed according to the metabolic parameters and other clinical variables.

RESULTS

Cancer-related death occurred in 19 of 55 patients (35 %) during the follow-up period (29 ± 23 months). On univariate analysis, AJCC stage (stage IV vs. I-III, hazard ratio (HR) = 2.837, p = 0.028), necrosis (G2 vs. G0-G1, HR = 3.890, p = 0.004), SUVmax (1 unit - increase, HR = 1.146, p = 0.008), SUVavg (1 unit - increase, HR = 1.469, p = 0.032) and treatment modality (non-surgical therapy vs. surgery, HR = 4.467, p = 0.002) were significant predictors for overall survival. On multivariate analyses, SUVmax (HR = 1.274, p = 0.015), treatment modality (HR = 3.353, p = 0.019) and necrosis (HR = 5.985, p = 0.006) were identified as significant independent prognostic factors associated with decreased overall survival.

CONCLUSIONS

The SUVmax of the primary tumor is a significant independent metabolic prognostic factor for overall survival in patients with STS. Volume-based PET parameters may not add prognostic information outside of the SUVmax.

Standardization of selection criteria for percutaneous image-guided cryoablation of recurrent soft-tissue sarcomas

PURPOSE

Percutaneous image-guided cryoablation has not been validated for local management of recurrence of soft tissue sarcoma (STS) of the trunk or limbs. This study aims to identify selection criteria for cryoablation in order to standardize indications of this treatment.

PATIENTS AND METHODS

Between 2000 and 2010, 46 patients (57 tumors) presenting local recurrences of STS of the trunk or limbs and treated following standards of care were selected from our institutional database. Eligibility for cryoablation was assessed by two radiologists according to predefined criteria: maximal diameter size of the tumor ≤10cm, distance to skin >5mm, distance to neurovascular structures 3mm at least, absence of articular involvement and planned cryoablation covering the entire lesion volume. Characteristics and outcomes were compared.

RESULTS

There was nearly perfect agreement for all criteria (k coefficient ranging from 0.83 to 0.98) between both readers. A subgroup of 13patients was identified as eligible for cryoablation. Locations to the trunk, pelvic girdle or shoulder were significantly more present in the cryoablation group (P=0.002). In this group, tumors were mainly located deeply (P=0.002) with great axes ≤5cm (P=0.044). High local tumor aggressiveness (P=0.016) and differentiated myxoid liposarcoma or myxofibrosarcoma (P=0.007) were more frequent in the eligible group.

CONCLUSION

Based on these criteria, two groups of patients with local relapse of STS can be identified. These results may improve the standardization of selection of patients who could be candidates for cryoablation.