Prognostic value of SUVmax in breast cancer and comparative analyses of molecular subtypes: A systematic review and meta-analysis

Quantitative PSMA-PET parameters in localized prostate cancer: prognostic and potential predictive value

BACKGROUND

PSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA.

METHODS

This is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC).

RESULTS

67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients.

CONCLUSION

Our data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential. Trial registration Due to the retrospective nature of this research, no registration was carried out.

Baseline and early 18F-FDG PET/CT evaluations as predictors of progression-free survival in metastatic breast cancer patients treated with targeted anti-CDK therapy

BACKGROUND

Exploring the value of baseline and early 18F-FDG PET/CT evaluations in prediction PFS in ER+/HER2- metastatic breast cancer patients treated with a cyclin-dependent kinase inhibitor in combination with an endocrine therapy.

METHODS

Sixty-six consecutive breast cancer patients who underwent a pre-therapeutic 18F-FDG PET/CT and a second PET/CT within the first 6 months of treatment were retrospectively included. Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) and Dmax, which represents tumour dissemination and is defined as the distance between the two most distant lesions, were computed. The variation in these parameters between baseline and early evaluation PET as well as therapeutic evaluation using PERCIST were assessed as prognosticators of PFS at 18 months.

RESULTS

The median follow-up was equal to 22.5 months. Thirty progressions occurred (45.4%). The average time to event was 17.8 ± 10.4 months. At baseline, Dmax was the only predictive metabolic parameter. Patients with a baseline Dmax ≤ 18.10 cm had a significantly better 18 m-PFS survival than the others: 69.2% (7.7%) versus 36.7% (8.8%), p = 0.017. There was no association between PERCIST evaluation and 18 m-PFS status (p = 0.149) and there was no difference in 18 m-PFS status between patients classified as complete, partial metabolic responders or having stable metabolic disease.

CONCLUSION

Disease spread at baseline PET, as assessed by Dmax, is predictive of an event occurring within 18 months. In the absence of early metabolic progression, which occurs in 15% of patients, treatment should be continued regardless of the quality of the initial response to treatment.

A PET-Surrogate Signature for the Interrogation of the Metabolic Status of Breast Cancers

Metabolic alterations in cancers can be exploited for diagnostic, prognostic, and therapeutic purposes. This is exemplified by 18F-fluorodeoxyglucose (FDG)-positron emission tomography (FDG-PET), an imaging tool that relies on enhanced glucose uptake by tumors for diagnosis and staging. By performing transcriptomic analysis of breast cancer (BC) samples from patients stratified by FDG-PET, a 54-gene signature (PETsign) is identified that recapitulates FDG uptake. PETsign is independently prognostic of clinical outcome in luminal BCs, the most common and heterogeneous BC molecular subtype, which requires improved stratification criteria to guide therapeutic decision-making. The prognostic power of PETsign is stable across independent BC cohorts and disease stages including the earliest BC stage, arguing that PETsign is an ab initio metabolic signature. Transcriptomic and metabolomic analysis of BC cells reveals that PETsign predicts enhanced glycolytic dependence and reduced reliance on fatty acid oxidation. Moreover, coamplification of PETsign genes occurs frequently in BC arguing for their causal role in pathogenesis. CXCL8 and EGFR signaling pathways feature strongly in PETsign, and their activation in BC cells causes a shift toward a glycolytic phenotype. Thus, PETsign serves as a molecular surrogate for FDG-PET that could inform clinical management strategies for BC patients.

Clinicopathological and molecular predictors of [18F]FDG-PET disease detection in HER2-positive early breast cancer: RESPONSE, a substudy of the randomized PHERGain trial

BACKGROUND

The PHERGain study (NCT03161353) is assessing early metabolic responses to neoadjuvant treatment with trastuzumab-pertuzumab and chemotherapy de-escalation using a [18Fluorine]fluorodeoxyglucose-positron emission tomography ([18F]FDG-PET) and a pathological complete response-adapted strategy in HER2-positive (HER2+) early breast cancer (EBC). Herein, we present RESPONSE, a PHERGain substudy, where clinicopathological and molecular predictors of [18F]FDG-PET disease detection were evaluated.

METHODS

A total of 500 patients with HER2 + EBC screened in the PHERGain trial with a tumor size > 1.5 cm by magnetic resonance imaging (MRI) were included in the RESPONSE substudy. PET[-] criteria entailed the absence of  ≥ 1 breast lesion with maximum standardized uptake value (SUVmax) ≥ 1.5 × SUVmean liver + 2 standard deviation. Among 75 PET[-] patients screened, 21 with SUVmax levels < 2.5 were randomly selected and matched with 21 PET[+] patients with SUVmax levels ≥ 2.5 based on patient characteristics associated with [18F]FDG-PET status. The association between baseline SUVmax and [18F]FDG-PET status ([-] or [+]) with clinicopathological characteristics was assessed. In addition, evaluation of stromal tumor-infiltrating lymphocytes (sTILs) and gene expression analysis using PAM50 and Vantage 3D™ Cancer Metabolism Panel were specifically compared in a matched cohort of excluded and enrolled patients based on the [18F]FDG-PET eligibility criteria.

RESULTS

Median SUVmax at baseline was 7.2 (range, 1-39.3). Among all analyzed patients, a higher SUVmax was associated with a higher tumor stage, larger tumor size, lymph node involvement, hormone receptor-negative status, higher HER2 protein expression, increased Ki67 proliferation index, and higher histological grade (p < 0.05). [18F]FDG-PET [-] criteria patients had smaller tumor size (p = 0.014) along with the absence of lymph node involvement and lower histological grade than [18F]FDG-PET [+] patients (p < 0.01). Although no difference in the levels of sTILs was found among 42 matched [18F]FDG-PET [-]/[+] criteria patients (p = 0.73), [18F]FDG-PET [-] criteria patients showed a decreased risk of recurrence (ROR) and a lower proportion of PAM50 HER2-enriched subtype than [18F]FDG-PET[+] patients (p < 0.05). Differences in the expression of genes involved in cancer metabolism were observed between [18F]FDG-PET [-] and [18F]FDG-PET[+] criteria patients.

CONCLUSIONS

These results highlight the clinical, biological, and metabolic heterogeneity of HER2+ breast cancer, which may facilitate the selection of HER2+ EBC patients likely to benefit from [18F]FDG-PET imaging as a tool to guide therapy.

TRIAL REGISTRATION

Clinicaltrials.gov; NCT03161353; registration date: May 15, 2017.

Baseline [18F]FDG PET/CT and MRI first-order breast tumor features do not improve pathological complete response prediction to neoadjuvant chemotherapy

PURPOSE

To verify the ability of pretreatment [18F]FDG PET/CT and T1-weighed dynamic contrast-enhanced MRI to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients.

METHODS

This retrospective study includes patients with BC of no special type submitted to baseline [18F]FDG PET/CT, NAC and surgery. [18F]FDG PET-based features reflecting intensity and heterogeneity of tracer uptake were extracted from the primary BC and suspicious axillary lymph nodes (ALN), for comparative analysis related to NAC response (pCR vs. non-pCR). Multivariate logistic regression was performed for response prediction combining the breast tumor-extracted PET-based features and clinicopathological features. A subanalysis was performed in a patients' subsample by adding breast tumor-extracted first-order MRI-based features to the multivariate logistic regression.

RESULTS

A total of 170 tumors from 168 patients were included. pCR was observed in 60/170 tumors (20/107 luminal B-like, 25/45 triple-negative and 15/18 HER2-enriched surrogate molecular subtypes). Higher intensity and higher heterogeneity of [18F]FDG uptake in the primary BC were associated with NAC response in HER2-negative tumors (immunohistochemistry score 0, 1 + or 2 + non-amplified by in situ hybridization). Also, higher intensity of tracer uptake was observed in ALN in the pCR group among HER2-negative tumors. No [18F]FDG PET-based features were associated with pCR in the other subgroup analyses. A subsample of 103 tumors was also submitted to extraction of MRI-based features. When combined with clinicopathological features, neither [18F]FDG PET nor MRI-based features had additional value for pCR prediction. The only significant predictors were estrogen receptor status, HER2 expression and grade.

CONCLUSION

Pretreatment [18F]FDG PET-based features from primary BC and ALN are not associated with response to NAC, except in HER2-negative tumors. As compared with pathological features, no breast tumor-extracted PET or MRI-based feature improved response prediction.

Prognostic Value of Serum Neutrophil to Lymphocyte Ratio and SUVmax in Stage I and II Colon Cancer

OBJECTIVE

This study aimed to evaluate the correlation between maximal standardized uptake value (SUVmax) of primary colon cancer and serum neutrophil-to-lymphocyte ratio (NLR), and to assess the prognostic value of SUVmax and serum NLR in stage I and II colon cancer patients.

METHODS

In this retrospective study a total of 128 patients with pathologically confirmed stage I and II colon cancer diagnosed between January 2014 and December 2017 were included. All patients underwent F-18 Fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) and differential white blood cell (WBC) counts before surgery. The correlations between SUVmax and NLR were assessed. The prognostic value of SUVmax and NLR for predicting recurrence-free survival (RFS) was investigated.

RESULTS

The mean NLR was 2.2 ± 1.2, and the mean SUVmax of primary tumor was 15.2 ± 7.9. There was significant correlation between NLR and SUVmax (rho=0.2, p=0.02). Mean follow-up period was 59.8 ± 19.2 months and 12 patients experienced a recurrence. In univariable analysis, NLR (p=0.0084, HR=5.0223, 95% CI=1.5117-16.6853), C-reactive protein (CRP) (p=0.021, HR=4.1115, 95% CI=1.2380-13.6551), carbohydrate antigen 19-9 (CA19-9) (p=0.0134, HR=4.2683, 95% CI=1.3519-13.4766), and Kirsten ras sarcoma viral oncogene (KRAS) mutation (p=0.0338, HR=3.4703, 95% CI=1.0998-10.9499) were significant prognostic factors for the recurrence. In multivariable analysis, NLR (p=0.0256, HR=4.1155, 95% CI=1.1887-14.2490) and CA19-9 (p=0.0257, HR=4.139, 95% CI=1.1880-14.4200) were independent prognostic factors for the recurrence.

CONCLUSIONS

Significant correlation was observed between SUVmax of primary colon cancer and serum NLR. Furthermore, in the multivariable analysis conducted on early colon cancer cases, NLR and CA19-9 were found to be independently associated with RFS. This suggested that NLR could be used as a supplementary tool for identifying patients at high risk of recurrence in early colon cancer. However, SUVmax was not associated with prognosis, suggesting that it cannot be used for predicting prognosis in early colon cancer.

Pretreatment 18F-FDG uptake heterogeneity may predict treatment outcome of combined Trastuzumab and Pertuzumab therapy in patients with metastatic HER2 positive breast cancer

OBJECTIVE

Intra-tumoral heterogeneity of 18F-fluorodeoxyglucose (18F-FDG) uptake has been proven to be a surrogate marker for predicting treatment outcome in various tumors. However, the value of intra-tumoral heterogeneity in metastatic Human epidermal growth factor receptor 2(HER2) positive breast cancer (MHBC) remains unknown. The aim of this study was to evaluate 18F-FDG uptake heterogeneity to predict the treatment outcome of the dual target therapy with Trastuzumab and Pertuzumab(TP) in MHBC.

METHODS

Thirty-two patients with MHBC who underwent 18F-FDG positron emission tomography/computed tomography (PET/CT) scan before TP were enrolled retrospectively. The region of interesting (ROI) of the lesions were drawn, and maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), total lesion glycolysis (TLG), metabolic tumor volume (MTV) and heterogeneity index (HI) were recorded. Correlation between PET/CT parameters and the treatment outcome was analyzed by Spearman Rank Test. The ability to predict prognosis were determined by time-dependent survival receiver operating characteristic (ROC) analysis. And the survival analyses were then estimated by Kaplan-Meier method and compared by log-rank test.

RESULTS

The survival analysis showed that HI50% calculated by delineating the lesion with 50%SUVmax as threshold was a significant predictor of patients with MHBC treated by the treatment with TP. Patients with HI50% (≥ 1.571) had a significantly worse prognosis of progression free survival (PFS) (6.87 vs. Not Reach, p = 0.001). The area under curve (AUC), the sensitivity and the specificity were 0.88, 100% and 63.6% for PFS, respectively.

CONCLUSION

18F-FDG uptake heterogeneity may be useful for predicting the prognosis of MHBC patients treated by TP.

Prediction of pathological response after neoadjuvant chemotherapy using baseline FDG PET heterogeneity features in breast cancer

Complete pathological response to neoadjuvant systemic treatment (NAST) in some subtypes of breast cancer (BC) has been used as a surrogate of long-term outcome. The possibility of predicting BC pathological response to NAST based on the baseline 18F-Fluorodeoxyglucose positron emission tomography (FDG PET), without the need of an interim study, is a focus of recent discussion. This review summarises the characteristics and results of the available studies regarding the potential impact of heterogeneity features of the primary tumour burden on baseline FDG PET in predicting pathological response to NAST in BC patients. Literature search was conducted on PubMed database and relevant data from each selected study were collected. A total of 13 studies were eligible for inclusion, all of them published over the last 5 years. Eight out of 13 analysed studies indicated an association between FDG PET-based tumour uptake heterogeneity features and prediction of response to NAST. When features associated with predicting response to NAST were derived, these varied between studies. Therefore, definitive reproducible findings across series were difficult to establish. This lack of consensus may reflect the heterogeneity and low number of included series. The clinical relevance of this topic justifies further investigation about the predictive role of baseline FDG PET.

Principal component analysis of texture features derived from FDG PET images of melanoma lesions

Background

The clinical utility of radiomics is hampered by a high correlation between the large number of features analysed which may result in the “bouncing beta” phenomenon which could in part explain why in a similar patient population texture features identified and/or cut-off values of prognostic significance differ from one study to another. Principal component analysis (PCA) is a technique for reducing the dimensionality of large datasets containing highly correlated variables, such as texture feature datasets derived from FDG PET images, increasing data interpretability whilst at the same time minimizing information loss by creating new uncorrelated variables that successively maximize variance. Here, we report on PCA of a texture feature dataset derived from 123 malignant melanoma lesions with a significant range in lesion size using the freely available LIFEx software.

Results

Thirty-eight features were derived from all lesions. All features were standardized. The statistical assumptions for carrying out PCA analysis were met. Seven principal components with an eigenvalue > 1 were identified. Based on the “elbow sign” of the Scree plot, only the first five were retained. The contribution to the total variance of these components derived using Varimax rotation was, respectively, 30.6%, 23.6%, 16.1%, 7.4% and 4.1%. The components provided summarized information on the locoregional FDG distribution with an emphasis on high FDG uptake regions, contrast in FDG uptake values (steepness), tumour volume, locoregional FDG distribution with an emphasis on low FDG uptake regions and on the rapidity of changes in SUV intensity between different regions.

Conclusions

PCA allowed to reduce the dataset of 38 features to a set of 5 uncorrelated new variables explaining approximately 82% of the total variance contained within the dataset. These principal components may prove more useful for multiple regression analysis considering the relatively low numbers of patients usually included in clinical trials on FDG PET texture analysis. Studies assessing the superior differential diagnostic, predictive or prognostic value of principal components derived using PCA as opposed to the initial texture features in clinical relevant settings are warranted.

The Diagnostic Performance of Maximum Uptake Value and Apparent Diffusion Coefficient in Differentiating Benign and Malignant Ovarian or Adnexal Masses: A Meta-Analysis

Objective

The purpose of this meta-analysis was to provide evidence for using maximum uptake value (SUVmax) and apparent diffusion coefficient (ADC) to quantitatively differentiate benign and malignant ovarian or adnexal masses, and to indirectly compare their diagnostic performance.

Material and Methods

The association between SUVmax, ADC and ovarian or adnexal benign and malignant masses was searched in PubMed, Cochrane Library, and Embase databases until October 1, 2021. Two authors independently extracted the data. Studies included in the analysis were required to provide data for the construction of a 2 × 2 contingency table to evaluate the diagnostic performance of SUVmax or ADC in differentiating benign and malignant ovarian or adnexal masses. The quality of the enrolled studies was evaluated by Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) instrument, and the meta-analysis was conducted using Stata software version 14.0. Forest plots were generated according to the sensitivity and specificity of SUVmax and ADC, and meta-regression analysis was further used to assess heterogeneity between studies.

Results

A total of 14 studies were finally included in this meta-analysis by gradually excluding duplicate literatures, conference abstracts, guidelines, reviews, case reports, animal studies and so on. The pooled sensitivity and specificity of SUVmax for quantitative differentiation of benign and malignant ovarian or adnexal masses were 0.88 and 0.89, respectively, and the pooled sensitivity and specificity for ADC were 0.87 and 0.80, respectively.

Conclusion

Quantitative SUVmax and ADC values have good diagnostic performance in differentiating benign and malignant ovarian or adnexal masses, and SUVmax has higher accuracy than ADC. Future prospective studies with large sample sizes are needed for the analysis of the role of SUVmax and ADC in the differentiation of benign and malignant ovarian or adnexal masses.