Prognostic value of metabolic tumor volume and total lesion glycolysis on preoperative 18F-FDG PET/CT in patients with localized primary gastrointestinal stromal tumors

Prognostic Value of the Metabolic Response on Serial 18F-FDG PET/CT in Pancreatic Cancer

Background/Aims

The prognostic value of serial 18F-fluorodeoxyglucose positron emission tomography/ computed tomography (18F-FDG PET/CT) for patients with borderline resectable or locally advanced pancreatic cancer who undergo conversion surgery or continue chemotherapy without surgery has not been well-established.

Methods

A retrospective analysis of patients with pancreatic ductal adenocarcinoma was conducted at Seoul National University Bundang Hospital between March 2013 and February 2022. Patients underwent PET/CT at baseline and subsequent radiologic evaluations following chemotherapy. Changes in the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, and total lesion glycolysis were analyzed. Based on their treatment regimens, patients were stratified into the conversion surgery group or nonconversion surgery group. Survival outcomes and various clinical factors were assessed.

Results

Among 121 patients, 52 underwent conversion surgery, and 69 continued to receive chemotherapy without surgery. A significant reduction in the SUVmax was correlated with prolonged recurrence-free survival and overall survival in the conversion surgery group. Confirmation of a pathologic response indicated a significant association between reductions in the SUVmax and positive outcomes. Reductions in the metabolic tumor volume and total lesion glycolysis were associated with improved progression-free survival and overall survival in the nonconversion surgery group.

Conclusions

Serial PET/CT scans demonstrated prognostic value in pancreatic ductal adenocarcinoma patients, revealing distinct correlations in the conversion surgery group and nonconversion surgery group.

Monitoring Glycolysis by Endogenous 31P CEST Magnetic Resonance Imaging

In this study, we present a novel approach to investigate glycolysis by means of the 3¹P CEST technique applied to phosphate-containing substrates at their endogenous concentration. The method relies on the assessment of the saturation transfer (ST) observed on the 3¹P signals of inorganic phosphate (Pi) or phosphocreatine (PCr) following the selective irradiation of phosphate groups of endogenous molecules exchanging with ATP, Pi, and indirectly with PCr in enzyme-catalyzed reactions. The concentrations of these substrates often fall below the threshold for direct detection. The 3¹P CEST technique amplifies their responses, making them detectable via the ST effect to the 3¹P resonance of the selected reference signal. The method was first validated in vitro on mouse breast adenocarcinoma cell pellets (TS/A), where the intracellular Pi signal was monitored to assess the ST effect associated with the saturation of phosphoester-containing molecules. The use of a glycolysis inhibitor and different experimental temperatures (37 °C or 4 °C) provided insights supporting the rationale behind the method. A comparison of 3¹P Z-spectra was carried out on murine breast cancer cell lines with different degrees of aggressiveness, showing the ability to assess metabolic differences. Finally, in vivo experiments on mice models of mammary adenocarcinoma demonstrated that 3¹P CEST can differentiate tumor and healthy tissue based on their metabolic characteristics.

18F-fluorodeoxyglucose positron emission tomography-computed tomography as a prognostic marker of imatinib-resistant gastrointestinal stromal tumors

PURPOSE

Unresectable or metastatic GISTs often develop resistance to imatinib, but the effectiveness of other drugs is limited. Thus, surgical treatment can be considered, especially for partial resistance. FDG-PET/CT is used for the diagnosis and evaluation of GISTs. We conducted this study to establish whether FDG-PET/CT findings could guide treatment decisions and predict the prognosis of patients with imatinib-resistant GISTs.

METHODS

We analyzed data retrospectively from 45 patients with imatinib-resistant GISTs that were assessed via FDG-PET/CT at our institution between 2003 and 2021. The patients were classified as having low (n = 18) or high (n = 27) SUVmax, with a cutoff value of 5.0.

RESULTS

The overall survival (OS) of the patients with low SUVmax after the diagnosis of imatinib resistance was significantly prolonged. Multivariate analysis identified SUVmax as an independent poor prognostic factor. In 23 patients with resected imatinib-resistant lesions, a close correlation was found between the SUVmax by preoperative FDG-PET/CT and the mitotic rate. A higher SUVmax was associated with a higher mitotic rate. Patients with a low SUVmax (n = 11) had significantly longer postoperative imatinib failure-free survival than those with a high SUVmax (n = 12).

CONCLUSIONS

FDG-PET/CT assessment and diagnosis might reveal the pathological grades of imatinib-resistant GISTs and act as a prognostic marker.

Head-to-Head Comparison of [68Ga]Ga-NOTA-RM26 and [18F]FDG PET/CT in Patients with Gastrointestinal Stromal Tumors: A Prospective Study

Gastrointestinal stromal tumors (GISTs) are the most common stromal tumors in the gastrointestinal tract. This study was designed to evaluate a gastrin-releasing peptide receptor antagonist PET tracer, [68Ga]Ga-NOTA-RM26, and compare it with [18F]FDG PET/CT in the assessment of patients with GISTs. Methods: With institutional review board approval and informed consent, 30 patients with suspected or proven GISTs based on abdominal CT or gastroscopy were recruited. All patients underwent [68Ga]Ga-NOTA-RM26 and [18F]FDG PET/CT scans. Pathology and other patient information were collected. Results: No radiopharmaceutical-related adverse events were observed in the patients. In total, 18 lesions in 16 patients were diagnosed as GIST, 3 patients were diagnosed with schwannoma, and 4 patients were diagnosed with leiomyoma. In 18 GISTs, the mean SUVmax of [68Ga]Ga-NOTA-RM26 PET was significantly higher than that of [18F]FDG PET (17.07 ± 19.57 vs. 2.28 ± 1.65; P < 0.01), and [68Ga]Ga-NOTA-RM26 PET/CT had a higher tumor detection rate than did [18F]FDG PET/CT (88.9% vs. 50%; P < 0.01). The uptake of [68Ga]Ga-NOTA-RM26 in GISTs was significantly higher than that in 2 other benign tumors (leiomyoma or schwannoma) (17.07 ± 19.57 vs. 4.23 ± 1.77; P = 0.014). With the SUVmax cutoff value of 6.0, the sensitivity of 68Ga-NOTA-RM26 PET/CT in diagnosing GISTs is 72% and the specificity is 85.7%. Conclusion: Compared with [18F]FDG PET/CT, [68Ga]Ga-NOTA-RM26 PET/CT is a promising and effective imaging modality for the detection of GISTs.

18F-Fluorodeoxyglucose Uptake in PDGFRA-Mutant Gastrointestinal Stromal Tumors

Importance

The D842V platelet-derived growth factor receptor α (PDGFRA) mutation identifies a molecular subgroup of gastrointestinal stromal tumors (GISTs), primarily resistant to standard tyrosine kinase inhibitors and with an overall more indolent behavior. Although functional imaging with 18F-fluorodeoxyglucose-labeled positron emission tomography ([18F]FDG-PET) plays a proven role in GISTs, especially in early assessment of tumor response, less is known about [18F]FDG uptake according to the GIST molecular subtypes.

Objective

To evaluate the degree of [18F]FDG uptake in PDGFRA-mutant GISTs and better define the role of functional imaging in this rare and peculiar subset of GISTs.

Design, Setting, and Participants

This multi-institutional retrospective cohort study involving 7 GIST reference centers in Italy included patients with PDGFRA-mutant GIST who underwent [18F]FDG-PET from January 1, 2000, to December 31, 2023. Data on the maximum standardized uptake value (SUVmax) of primary tumor or metastatic disease were collected.

Exposure

PDGFRA-mutant GIST and [18F]FDG-PET.

Main Outcome and Measure

The primary outcome was the degree of [18F]FDG uptake of PDGFRA-mutant GISTs, with a focus on the D842V-mutant subgroup. Secondary objectives were to assess the association between the degree of [18F]FDG uptake and main clinicopathologic features.

Results

A total of 71 patients with PDGFRA-mutant GISTs were included in the analysis: 37 (52.1%) in the D842V subgroup (group A) and 34 (47.9%) in the non-D842V subgroup (group B). Additionally, 70 patients with KIT exon 11-mutant GIST served as a control group (group C). For all 141 participants, the median age at diagnosis was 59 (range, 26-89) years, and 81 patients (57.4%) were male. Overall, the median SUVmax was 4.4 (IQR, 0-10.1), while the median SUVmax for group A was 0 (IQR, 0-3.2); for group B, 3.6 (IQR, 0-5.1); and for group C, 10.1 (IQR, 5.1-13.9). The median SUVmax of PDGFRA-mutant GISTs was significantly lower than the median value of KIT exon 11-mutant GISTs (0 [IQR, 0-4.3] vs 10.1 [IQR, 5.1-14.0]; P < .001). Median [18F]FDG uptake was significantly lower in the D842V subgroup compared with the non-D842V subgroup (0 [IQR, 0-3.2] vs 3.6 [IQR, 0-5.1]; P = .02). Moreover, the triad of gastric primary tumor, tumor size greater than 10 cm, and SUVmax of 5.75 or less was associated with identification of PDGFRA-mutant GISTs.

Conclusions and Relevance

In this cohort study of patients with PDGFRA-mutant GISTs, the D842V-mutant GISTs were associated with an overall lower [18F]FDG uptake compared with other GIST subgroups. Therefore, the role of functional imaging with [18F]FDG-PET in this subset of GISTs may be limited and should be further explored for its potential prognostic and predictive value.

Glycolysis in gastrointestinal stromal tumor: a brief overview

Gastrointestinal stromal tumor (GIST) is the most prevalent mesenchymal tumor of the digestive tract. Its growth is primarily influenced by mutations in KIT or PDGFRA. Surgery is the primary treatment option for GIST; however, KIT inhibitors, such as imatinib, are used for inoperable cases. Resistance to imatinib is an upcoming challenge, especially because the effectiveness of alternative drugs is limited. Enhancement of the glycolysis pathway in cancer cells has been identified as a key feature in cancer. This unique metabolic activity has implications on tumor growth, prognosis, and resistance to therapy, even in GIST. Members of the glucose transporter (GLUT) family (particularly GLUT-1) play a significant role in GIST progression and response to treatment. Diagnostic imaging using 18F-fluorodeoxyglucose positron emission tomography/computed tomography, which enables visualization of glucose metabolism, can aid in GIST diagnosis and risk assessment. The interplay between glycolysis and GIST can lead to the development of various therapeutic strategies, especially those involving glycolysis-related molecules, such as hexokinase and lactate dehydrogenase. However, further research is required to understand the full spectrum of glycolysis in GIST and its therapeutic potential. Herein, we present an exhaustive overview and analysis of the role of glycolysis in GIST, especially as a therapeutic target.

Predictive performance of [18F]F-fibroblast activation protein inhibitor (FAPI)-42 positron emission tomography/computed tomography (PET/CT) in evaluating response of recurrent or metastatic gastrointestinal stromal tumors: complementary or alternative to [18F]fluorodeoxyglucose (FDG) PET/CT?

Background

Accurately and promptly predicting the response of gastrointestinal stromal tumors (GISTs) to targeted therapy is essential for optimizing treatment strategies. However, some fractions of recurrent or metastatic GISTs present as non-FDG-avid lesions, limiting the value of [18F]fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG PET/CT) in treatment evaluation. This study evaluated the efficacy of [18F]F-fibroblast activation protein inhibitor (FAPI)-42 [18F]FAPI-42) PET/CT for assessing the treatment response in recurrent or metastatic GISTs, in comparison to [18F]FDG PET/CT and explores a model integrating PET/CT imaging and clinical parameters to optimize the clinical use of these diagnostic tools.

Methods

Our retrospective analysis included 27 patients with recurrent or metastatic GISTs who underwent [18F]FAPI-42 PET/CT and [18F]FDG PET/CT at baseline before switching targeted therapy. Treatment response status was divided into a progression group (PG) and a non-progression group (NPG) based on the Response Criteria in Solid Tumors (RECIST) 1.1, according to the contrast-enhanced computed tomography (CT) scan at six months. [18F]FAPI-42 and [18F]FDG PET/CT parameters including the mean standardized uptake value (SUVmean), the standard uptake value corrected for lean body mass (SULpeak), the maximum standardized uptake value (SUVmax), tumor-to-blood pool SUV ratio (TBR), tumor-to-liver SUV ratio (TLR), metabolic tumor volume (MTV)/FAPI-positive tumor volume (GTV-FAPI), total lesion glycolysis (TLG)/FAPI-positive total lesion accumulation (TLF) were correlated with the response status to identify indicative of treatment response. The predictive performance of them was quantified by generating receiver operating characteristic curves (ROC), calibration curves, and cross-validation.

Results

A total of 110 lesions were identified in 27 patients. Compared with PG, NPG was associated with lower levels of TBR and SUVmean in FDG PET/CT (TBR-FDG, SUVmean-FDG; P=0.033 and P=0.038, respectively), with higher SULpeak and TLF in FAPI PET/CT (SULpeak-FAPI, TLF-FAPI; P=0.10 and P=0.049, respectively). The predictive power of a composite-parameter model, including TBR-FDG, SULpeak-FAPI, gene mutation, and type of targeted therapy [area under the curve (AUC) =0.865], was superior to the few-parameter models incorporating TBR-FDG (AUC =0.637, P<0.001), SULpeak-FAPI (AUC =0.665, P<0.001) or both (AUC =0.721, P<0.001).

Conclusions

Both [18F]FAPI-42 PET/CT and [18F]FDG PET/CT have value in predicting the treatment response of recurrent or metastatic GISTs. And [18F]FAPI-42 PET/CT offers synergistic value when used in combination with [18F]FDG PET/CT. Notably, the nomogram generated from the model incorporating [18F]FAPI-42 PET/CT, [18F]FDG PET/CT parameters, gene mutation, and type of targeted therapy could yield more precise predictions of the response of recurrent metastatic GISTs.

Prognosis Prediction of Diffuse Large B-Cell Lymphoma in 18F-FDG PET Images Based on Multi-Deep-Learning Models

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based methods. In this paper, a new flexible ensemble deep learning model is proposed for the prognosis prediction of the DLBCL in 18F-FDG PET images. This study proposes the multi-R-signature construction through selected pre-trained deep learning models for predicting progression-free survival (PFS) and overall survival (OS). The proposed method is trained and validated on two datasets from different imaging centers. Through analyzing and comparing the results, the prediction models, including Age, Ann abor stage, Bulky disease, SUVmax, TMTV, and multi-R-signature, achieve the almost best PFS prediction performance (C-index: 0.770, 95% CI: 0.705-0.834, with feature adding fusion method and C-index: 0.764, 95% CI: 0.695-0.832, with feature concatenate fusion method) and OS prediction (C-index: 0.770 (0.692-0.848) and 0.771 (0.694-0.849)) on the validation dataset. The developed multiparametric model could achieve accurate survival risk stratification of DLBCL patients. The outcomes of this study will be helpful for the early identification of high-risk DLBCL patients with refractory relapses and for guiding individualized treatment strategies.

The impact of contour maps on estimating the risk of gastrointestinal stromal tumor recurrence: indications for adjuvant therapy: an analysis of the Kinki GIST registry

INTRODUCTION

Contour maps enable risk classification of GIST recurrence in individual patients within 10 postoperative years. Although contour maps have been referred to in Japanese guidelines, their usefulness and role in determining indications for adjuvant therapy is still unclear in Japanese patients. The aims of this study are to investigate the validity of contour maps in Japanese patients with GIST and explore the new strategy for adjuvant therapy.

MATERIALS AND METHODS

A total of 1426 Japanese GIST patients who were registered to the registry by the Kinki GIST Study Group between 2003 and 2012 were analyzed. Patients who had R0 surgery without perioperative therapy were included in this study. The accuracy of contour maps was validated.

RESULTS

Overall, 994 patients have concluded this study. Using contour maps, we validated the patients. The 5-year recurrence-free survival rates of patients within the GIST classification groups of 0-10%, 10-20%, 20-40%, 40-60%, 60-80%, 80-90%, and 90-100% were 98.1%, 96.6%, 92.3%, 48.0%, 37.3%, 41.0% and 42.4%, respectively. We confirmed that this classification by contour maps was well reflected recurrence prediction. Further, in the high-risk group stratified by the modified National Institutes of Health consensus criteria (m-NIHC), the 10-year RFS rate was remarkably changed at a cutoff of 40% (0-40% group vs. 40-100% group: 88.7% vs. 50.3%, p < 0.001).

CONCLUSION

Contour maps are effective in predicting individual recurrence rates. And it may be useful for the decision of individual strategy for high-risk patients combined with m-NIHC.

Predictive value of intratumoral-metabolic heterogeneity derived from 18F-FDG PET/CT in distinguishing microsatellite instability status of colorectal carcinoma

Purpose/background

Microsatellite instability (MSI) status is a significant biomarker for the response to immune checkpoint inhibitors, response to 5-fluorouracil-based adjuvant chemotherapy, and prognosis in colorectal carcinoma (CRC). This study investigated the predictive value of intratumoral-metabolic heterogeneity (IMH) and conventional metabolic parameters derived from 18F-FDG PET/CT for MSI in patients with stage I-III CRC.

Methods

This study was a retrospective analysis of 152 CRC patients with pathologically proven MSI who underwent 18F-FDG PET/CT examination from January 2016 to May 2022. Intratumoral-metabolic heterogeneity (including heterogeneity index [HI] and heterogeneity factor [HF]) and conventional metabolic parameters (standardized uptake value [SUV], metabolic tumor volume [MTV], and total lesion glycolysis [TLG]) of the primary lesions were determined. MTV and SUVmean were calculated on the basis of the percentage threshold of SUVs at 30%-70%. TLG, HI, and HF were obtained on the basis of the above corresponding thresholds. MSI was determined by immunohistochemical evaluation. Differences in clinicopathologic and various metabolic parameters between MSI-High (MSI-H) and microsatellite stability (MSS) groups were assessed. Potential risk factors for MSI were assessed by logistic regression analyses and used for construction of the mathematical model. Area under the curve (AUC) were used to evaluate the predictive ability of factors for MSI.

Results

This study included 88 patients with CRC in stages I-III, including 19 (21.6%) patients with MSI-H and 69 (78.4%) patients with MSS. Poor differentiation, mucinous component, and various metabolic parameters including MTV30%, MTV40%, MTV50%, and MTV60%, as well as HI50%, HI60%, HI70%, and HF in the MSI-H group were significantly higher than those in the MSS group (all P < 0.05). In multivariate logistic regression analyses, post-standardized HI60% by Z-score (P = 0.037, OR: 2.107) and mucinous component (P < 0.001, OR:11.394) were independently correlated with MSI. AUC of HI60% and our model of the HI60% + mucinous component was 0.685 and 0.850, respectively (P = 0.019), and the AUC of HI30% in predicting the mucinous component was 0.663.

Conclusions

Intratumoral-metabolic heterogeneity derived from 18F-FDG PET/CT was higher in MSI-H CRC and predicted MSI in stage I-III CRC patients preoperatively. HI60% and mucinous component were independent risk factors for MSI. These findings provide new methods to predict the MSI and mucinous component for patients with CRC.

Malignant diagnosis and prognostic analysis of 89 GIST patients using preoperative FDG-PET

There is no preoperative imaging accurately diagnose malignancy of gastrointestinal stromal tumor (GIST). To evaluate the usefulness of preoperative [¹⁸F]2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) in the malignant diagnosis and prognostic analysis of GIST. Eighty-nine consecutive patients with GIST who underwent curative surgery were reviewed retrospectively. PET scan was performed within 2-3 weeks before surgery and maximum standardized uptake values (SUVmax) were assessed for GIST. The relationship between prognostic factors and prognosis of GIST and SUVmax were evaluated. Tumor size, mitotic count, and Ki-67 index showed significant positive correlations with the SUVmax. When the cutoff value was set as SUVmax 5.68, the accuracy was 86.5% for the high-risk group, 76.4% for the recurrence group, and 73.0% for the death group. The group with SUVmax ≥ 5.68 demonstrated a significantly lower 10-year relapse-free survival than the group with SUVmax < 5.68 (55.2% vs. 98.2%, P < 0.001), while the group with SUVmax ≥ 5.68 demonstrated a significantly lower 10-year overall survival than the group with SUVmax < 5.68 (68.0% vs. 97.6%, P < 0.001). In GISTs, FDG-PET is a very useful imaging marker for the diagnosis of malignant GISTs, such as those in high-risk and poor-prognosis groups.

Development and Validation of 18F-FDG PET/CT-Based Models for Predicting Successful Complete Cytoreduction During Primary Cytoreductive Surgery for Advanced Ovarian cancer

PURPOSE

The aim of this study was to develop an 18F-FDG PET/CT-based model to predict complete cytoreduction during primary cytoreductive surgery (CRS) for ovarian cancer (OC).

PATIENTS AND METHODS

We retrospectively identified patients with stage III-IV OC who underwent primary CRS between June 2013 and February 2020 at 2 tertiary centers. Patients from each hospital were assigned to training and test sets. The abdominal cavity was divided into 3 sections, and data for the PET/CT-derived parameters were collected through image analysis. Various prediction models were constructed by combining clinicopathologic characteristics and PET/CT-derived parameters. The performance of the model with the highest area under the receiver operating characteristic curve (AUC) was externally validated.

RESULTS

The training and test sets included 159 and 166 patients, respectively. The median age of patients in the test set was 55 years; 72.3% of them had stage III tumors, and 65.4% underwent complete cytoreduction. Metabolic tumor volume, total lesion glycolysis, and the number of metastatic lesions above the upper margin of the renal vein (area A) were selected among the PET/CT parameters. The best predictive multivariable model consisted of CA-125 (<750 or ≥750 IU/mL), number of metastatic lesions (<2 or ≥2), and metabolic tumor volume of area A, predicting complete cytoreduction with an AUC of 0.768. The model was validated using a test set. Its predictive performance yielded an AUC of 0.771.

CONCLUSIONS

We successfully developed and validated a preoperative model to predict complete cytoreduction in advanced OC. This model can facilitate patient selection for primary CRS in clinical practice.

Repeatability of metabolic tumor burden and lesion glycolysis between clinical readers

The Metabolic Tumor Volume (MTV) and Tumor Lesion Glycolysis (TLG) has been shown to be independent prognostic predictors for clinical outcome in Diffuse Large B-cell Lymphoma (DLBCL). However, definitions of these measurements have not been standardized, leading to many sources of variation, operator evaluation continues to be one major source. In this study, we propose a reader reproducibility study to evaluate computation of TMV (& TLG) metrics based on differences in lesion delineation. In the first approach, reader manually corrected regional boundaries after automated detection performed across the lesions in a body scan (Reader M using a manual process, or manual). The other reader used a semi-automated method of lesion identification, without any boundary modification (Reader A using a semi- automated process, or auto). Parameters for active lesion were kept the same, derived from standard uptake values (SUVs) over a 41% threshold. We systematically contrasted MTV & TLG differences between expert readers (Reader M & A). We find that MTVs computed by Readers M and A were both concordant between them (concordant correlation coefficient of 0.96) and independently prognostic with a P-value of 0.0001 and 0.0002 respectively for overall survival after treatment. Additionally, we find TLG for these reader approaches showed concordance (CCC of 0.96) and was prognostic for over -all survival (p ≤ 0.0001 for both). In conclusion, the semi-automated approach (Reader A) provides acceptable quantification & prognosis of tumor burden (MTV) and TLG in comparison to expert reader assisted measurement (Reader M) on PET/CT scans.

Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal neoplasms. Tyrosine kinase inhibitor (TKI) therapy is currently part of routine clinical practice for unresectable and metastatic disease. It is important to assess the efficacy of TKI treatment at an early stage to optimize therapy strategies and eliminate futile ineffective treatment, side effects and unnecessary costs. This systematic review provides an overview of the imaging features obtained from contrast-enhanced (CE)-CT and 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT to predict and monitor TKI treatment response in GIST patients. PubMed, Web of Science, the Cochrane Library and Embase were systematically screened. Articles were considered eligible if quantitative outcome measures (area under the curve (AUC), correlations, sensitivity, specificity, accuracy) were used to evaluate the efficacy of imaging features for predicting and monitoring treatment response to various TKI treatments. The methodological quality of all articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies, v2 (QUADAS-2) tool and modified versions of the Radiomics Quality Score (RQS). A total of 90 articles were included, of which 66 articles used baseline [18F]FDG-PET and CE-CT imaging features for response prediction. Generally, the presence of heterogeneous enhancement on baseline CE-CT imaging was considered predictive for high-risk GISTs, related to underlying neovascularization and necrosis of the tumor. The remaining articles discussed therapy monitoring. Clinically established imaging features, including changes in tumor size and density, were considered unfavorable monitoring criteria, leading to under- and overestimation of response. Furthermore, changes in glucose metabolism, as reflected by [18F]FDG-PET imaging features, preceded changes in tumor size and were more strongly correlated with tumor response. Although CE-CT and [18F]FDG-PET can aid in the prediction and monitoring in GIST patients, further research on cost-effectiveness is recommended.

Value of 18F-FDG PET/CT for differentiating diagnosis between malignant and benign primary gastric gastrointestinal mesenchymal tumors: a single-center retrospective study

BACKGROUND

Malignant primary gastric gastrointestinal stromal tumors (gGISTs) without treatment with imatinib are prone to bleeding and peritoneum implantation during operation. Therefore, preoperative assessment of the malignant potential of gGIST is essential. The use of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) combined with computed tomography (PET/CT) as a non-invasive tool for diagnosis, staging and prognosis evaluation in oncology, may also be useful for gGISTs. In the present study, we analyzed the value of 18F-FDG PET-CT in assessing the malignant potential of gGISTs before treatment.

METHODS

Patients who were diagnosed with gGIST by pathology and underwent 18F-FDG PET/CT at the same time were collected. The clinicopathological features of 26 patients with gGISTs were retrospectively analyzed at last. The gGIST risk classification was graded according to the US National Institutes of Health (NIH) GIST risk classification criteria [2008]. Lesions were classified as malignant group (moderate- or high-risk category) and benign group (low- or very low-risk category) according to pathology. The relationship between the maximal standard uptake value (SUVmax) and GIST risk category, tumor diameter, Ki-67 index, and mitotic count was analyzed. The cut-off level of SUVmax for the diagnosis of malignant gGIST with the highest sensitivity was calculated based on the receiver-operating characteristic (ROC) curve.

RESULTS

The SUVmax, tumor diameter, Ki-67 index, and mitotic count of the 26 gGIST patients were 5.90±4.49, 7.40±4.92 cm, 7.62%±11.76%, (5.96±3.19)/50 high-power field (HPF), respectively. SUVmax was significantly correlated with GIST risk category, Ki-67 index, and mitotic count (r=0.855, 0.860, and 0.690, all P<0.01) but not with tumor diameter (r=0.383, P=0.054). The SUVmax of gGIST was 7.00±4.57 in the malignant group (moderate or high NIH risk category in 20 patients), which was significantly different from that (2.25±0.77) in the benign group (low or extremely low NIH risk category in 6 patients) (t=4.566, P<0.01). ROC curve analysis showed that a SUVmax cut-off of 2.60 was most sensitive for predicting malignant gGIST. When the area under the curve was 0.967, the sensitivity was 100% and the specificity was 83.3%.

CONCLUSIONS

SUVmax may be used as a complementary indicator for predicting the malignant potential of gGISTs before treatment.

Application of ultrasonography in predicting the biological risk of gastrointestinal stromal tumors

OBJECTIVES

To explore and establish a reliable and noninvasive ultrasound model for predicting the biological risk of gastrointestinal stromal tumors (GISTs).

MATERIALS AND METHODS

We retrospectively reviewed 266 patients with pathologically-confirmed GISTs and 191 patients were included. Data on patient sex, age, tumor location, biological risk classification, internal echo, echo homogeneity, boundary, shape, blood flow signals, presence of necrotic cystic degeneration, long diameter, and short/long (S/L) diameter ratio were collected. All patients were divided into low-, moderate-, and high-risk groups according to the modified NIH classification criteria. All indicators were analyzed by univariate analysis. The indicators with inter-group differences were used to establish regression and decision tree models to predict the biological risk of GISTs.

RESULTS

There were statistically significant differences in long diameter, S/L ratio, internal echo level, echo homogeneity, boundary, shape, necrotic cystic degeneration, and blood flow signals among the low-, moderate-, and high-risk groups (all p < .05). The logistic regression model based on the echo homogeneity, shape, necrotic cystic degeneration and blood flow signals had an accuracy rate of 76.96% for predicting the biological risk, which was higher than the 72.77% of the decision tree model (based on the long diameter, the location of tumor origin, echo homogeneity, shape, and internal echo) (p = .008). In the low-risk and high-risk groups, the predicting accuracy rates of the regression model reached 87.34 and 81.82%, respectively.

CONCLUSIONS

Transabdominal ultrasound is highly valuable in predicting the biological risk of GISTs. The logistic regression model has greater predictive value than the decision tree model.

Clinical Perspectives for 18F-FDG PET Imaging in Pediatric Oncology: Μetabolic Tumor Volume and Radiomics

Pediatric cancer, although rare, requires the most optimized treatment approach to obtain high survival rates and minimize serious long-term side effects in early adulthood. 18F-FDG PET/CT is most helpful and widely used in staging, recurrence detection, and response assessment in pediatric oncology. The well-known 18F-FDG PET metabolic indices of metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG) have already revealed an independent significant prognostic value for survival in oncologic patients, although the corresponding cut-off values remain study-dependent and not validated for use in clinical practice. Advanced tumor “radiomic” analysis sheds new light into these indices. Numerous patterns of texture 18F-FDG uptake features can be extracted from segmented PET tumor images due to new powerful computational systems supporting complex “deep learning” algorithms. This high number of “quantitative” tumor imaging data, although not decrypted in their majority and once standardized for the different imaging systems and segmentation methods, could be used for the development of new “clinical” models for specific cancer types and, more interestingly, for specific age groups. In addition, data from novel techniques of tumor genome analysis could reveal new genes as biomarkers for prognosis and/or targeted therapies in childhood malignancies. Therefore, this ever-growing information of “radiogenomics”, in which the underlying tumor “genetic profile” could be expressed in the tumor-imaging signature of “radiomics”, possibly represents the next model for precision medicine in pediatric cancer management. This paper reviews 18F-FDG PET image segmentation methods as applied to pediatric sarcomas and lymphomas and summarizes reported findings on the values of metabolic and radiomic features in the assessment of these pediatric tumors.