Significance of Metabolic Tumor Volume at Baseline and Reduction of Mean Standardized Uptake Value in 18F-FDG-PET/CT Imaging for Predicting Pathological Complete Response in Breast Cancers Treated with Preoperative Chemotherapy

Impact of different reconstruction algorithms and setting parameters on radiomics features of PSMA PET images: A preliminary study

PURPOSE

Radiomics analysis of oncologic positron emission tomography (PET) images is an area of significant activity and potential. The reproducibility of radiomics features is an important consideration for routine clinical use. This preliminary study investigates the robustness of radiomics features in PSMA-PET images across penalized-likelihood (Q.Clear) and standard ordered subset expectation maximization (OSEM) reconstruction algorithms and their setting parameters in phantom and prostate cancer (PCa) patients.

METHOD

A NEMA image quality (IQ) phantom and 8 PCa patients were selected for phantom and patient analyses, respectively. PET images were reconstructed using Q.Clear (reconstruction β-value: 100-700, at intervals of 100 for both NEMA IQ phantom and patients) and OSEM (duration: 15sec, 30sec, 1 min, 2 min, 3 min, 4 min and 5 min for NEMA phantom and duration: 30 s, 1 min and 2 min for patients) reconstruction methods. Subsequently, 129 radiomic features were extracted from the reconstructed images. The coefficient of variation (COV) of each feature across reconstruction methods and their parameters was calculated to determine feature robustness.

RESULTS

The extracted radiomics features showed a different range of variability, depending on the reconstruction algorithms and setting parameters. Specifically, 23.0 % and 53.5 % of features were found as robust against β-value variations in Q.Clear and different durations in OSEM reconstruction algorithms, respectively. Taking into account the two algorithms and their parameters, eleven features (8.5 %) showed COV ≤ 5 % and eighteen (14 %) showed 5 % 20 %. The mean COVs of the extracted radiomics features were significantly different between the two reconstruction methods (p < 0.05) except for the phantom morphological features.

CONCLUSIONS

All radiomics features were affected by reconstruction methods and parameters, but features with small or very small variations are considered better candidates for reproducible quantification of either tumor or metastatic tissues in clinical trials. There is a need for standardization before the implementation of PET radiomics in clinical practice.

Innovations in Positron Emission Tomography and State of the Art in the Evaluation of Breast Cancer Treatment Response

The advent of hybrid Positron Emission Tomography/Computed Tomography (PET/CT) and PET/Magnetic Resonance Imaging (MRI) scanners resulted in an increased clinical relevance of nuclear medicine in oncology. The use of [18F]-Fluorodeoxyglucose ([18F]FDG) has also made it possible to study tumors (including breast cancer) from not only a dimensional perspective but also from a metabolic point of view. In particular, the use of [18F]FDG PET allowed early confirmation of the efficacy or failure of therapy. The purpose of this review was to assess the literature concerning the response to various therapies for different subtypes of breast cancer through PET. We start by summarizing studies that investigate the validation of PET/CT for the assessment of the response to therapy in breast cancer; then, we present studies that compare PET imaging (including PET devices dedicated to the breast) with CT and MRI, focusing on the identification of the most useful parameters obtainable from PET/CT. We also focus on novel non-FDG radiotracers, as they allow for the acquisition of information on specific aspects of the new therapies.

Clinical Utility of Pre-Therapeutic [18F]FDG PET/CT Imaging for Predicting Outcomes in Breast Cancer

BACKGROUND

[18F]FDG PET/CT is used for staging and could also provide information associated with clinical outcomes. The objective of this study was to determine the clinical utility of biomarkers measured using [18F]FDG PET/CT to predict the absence of pathological complete response (no-pCR) and recurrence.

METHODS

In this retrospective study, we included patients with non-special-type breast carcinoma who underwent [18F]FDG PET/CT before neoadjuvant chemotherapy between 2011 and 2019. Clinicopathological data were collected. Tumor SUVmax and total metabolic tumor volume (TMTV) were measured from PET images. The association between biomarkers and no-pCR was studied using logistic regression. The cut-off value was determined using the area under the ROC Curve. To predict 3-year recurrence-free survival (RFS), we used a multivariable Cox model, and the cut-off value was determined using time-dependent ROC and predictiveness curves.

RESULTS

Two hundred and eighty-six patients were included in the analysis. One hundred and twelve patients had a pCR (39.2%). The pCR rate was significantly higher in patients with a high nuclear grade (p < 0.01), HER2+ and TNBC subtypes (p < 0.01), high Ki67 (p < 0.01), and low TMTV (p < 0.01). A high TMTV value (>9.0 cm3) was significantly associated with no-pCR in the whole cohort (OR = 2.4, 95% CI: 1.3-4.2, p < 0.01). After a median follow-up of 4.5 years, 65 patients experienced recurrence and 39 patients died. High TMTV (>13.5 cm3) was associated with shorter RFS (HR = 4.0, 95% CI: 1.9-8.4, p < 0.01).

CONCLUSION

High TMTV in pre-therapeutic imaging is associated with no-pCR and recurrence. It can help in identifying high-risk patients and be considered as an intensified or alternative adjuvant therapy for closely monitoring patients.

Novel computational biology modeling system can accurately forecast response to neoadjuvant therapy in early breast cancer

BACKGROUND

Generalizable population-based studies are unable to account for individual tumor heterogeneity that contributes to variability in a patient's response to physician-chosen therapy. Although molecular characterization of tumors has advanced precision medicine, in early-stage and locally advanced breast cancer patients, predicting a patient's response to neoadjuvant therapy (NAT) remains a gap in current clinical practice. Here, we perform a study in an independent cohort of early-stage and locally advanced breast cancer patients to forecast tumor response to NAT and assess the stability of a previously validated biophysical simulation platform.

METHODS

A single-blinded study was performed using a retrospective database from a single institution (9/2014-12/2020). Patients included: ≥ 18 years with breast cancer who completed NAT, with pre-treatment dynamic contrast enhanced magnetic resonance imaging. Demographics, chemotherapy, baseline (pre-treatment) MRI and pathologic data were input into the TumorScope Predict (TS) biophysical simulation platform to generate predictions. Primary outcomes included predictions of pathological complete response (pCR) versus residual disease (RD) and final volume for each tumor. For validation, post-NAT predicted pCR and tumor volumes were compared to actual pathological assessment and MRI-assessed volumes. Predicted pCR was pre-defined as residual tumor volume ≤ 0.01 cm³ (≥ 99.9% reduction).

RESULTS

The cohort consisted of eighty patients; 36 Caucasian and 40 African American. Most tumors were high-grade (54.4% grade 3) invasive ductal carcinomas (90.0%). Receptor subtypes included hormone receptor positive (HR+)/human epidermal growth factor receptor 2 positive (HER2+, 30%), HR+/HER2- (35%), HR-/HER2+ (12.5%) and triple negative breast cancer (TNBC, 22.5%). Simulated tumor volume was significantly correlated with post-treatment radiographic MRI calculated volumes (r = 0.53, p = 1.3 × 10^-7, mean absolute error of 6.57%). TS prediction of pCR compared favorably to pathological assessment (pCR: TS n = 28; Path n = 27; RD: TS n = 52; Path n = 53), for an overall accuracy of 91.2% (95% CI: 82.8% - 96.4%; Clopper-Pearson interval). Five-year risk of recurrence demonstrated similar prognostic performance between TS predictions (Hazard ratio (HR): - 1.99; 95% CI [- 3.96, - 0.02]; p = 0.043) and clinically assessed pCR (HR: - 1.76; 95% CI [- 3.75, 0.23]; p = 0.054).

CONCLUSION

We demonstrated TS ability to simulate and model tumor in vivo conditions in silico and forecast volume response to NAT across breast tumor subtypes.

The predictive and prognostic role of metabolic and volume-based parameters of positron emission tomography/computed tomography as non-invasive dynamic biological markers in early breast cancer treated with preoperative systemic therapy

Introduction

The role of fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in early breast cancer treated with preoperative systemic therapy (PST) is not yet established in clinical practice. PET parameters have aroused great interest in the recent years, as non-invasive dynamic biological markers for predicting response to PST.

Methods

In this retrospective study, we included 141 patients with stage II-III breast cancer who underwent surgery after PST. Using ROC analysis, we set optimal cutoff of FDG-PET/CT parameters predictive for pathological complete response (pCR). We investigated the correlation between FDG-PET/CT parameters and pCR, median disease-free survival (DFS), and median overall survival (mOS).

Results

At multivariable analysis, baseline SUVmax (high vs low: OR 9.00, CI 1.85 - 61.9, p=0.012) and Delta SUVmax (high vs low: OR 9.64, CI 1.84, 69.2, p=0.012) were significantly associated with pCR rates. Interestingly, we found that a combined analysis of the metabolic parameter Delta SUVmax with the volume-based parameter Delta MTV, may help to identify patients with pCR, especially in the subgroup of hormone receptor positive breast cancer. Delta SUVmax was also an independent predictive marker for both mDFS (high vs low: HR 0.17, 95%CI 0.05-0.58, p=0.004) and mOS (high vs. low: HR 0.19, 95%CI 0.04-0.95, p=0.029).

Discussion

Our results suggest that Delta SUVmax may predict survival of early BC patients treated with PST.

Prognostic Value of Neutrophil-to-Lymphocyte Ratio and Early Standardized Uptake Value Reduction in Patients With Breast Cancer Receiving Neoadjuvant Chemotherapy

PURPOSE

We investigated the treatment response and prognosis using the neutrophil-to-lymphocyte ratio (NLR) and standardized uptake value (SUV) of ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) in neoadjuvant settings.

METHODS

Baseline NLR and maximum SUV (SUV_max) were retrospectively analyzed in 273 females with breast cancer who received neoadjuvant chemotherapy followed by surgery. Of these, 101 patients underwent ¹⁸F-FDG PET after 3-4 neoadjuvant chemotherapy cycles, which allowed the measurement of ΔSUV_max, an early reduction in SUV_max. NLR and early SUV_max reduction (ΔSUV_max) were classified as low and high, respectively, relative to the median values.

RESULTS

The mean NLR was lower, and the mean ΔSUV_max was higher in patients with pathologic complete response (pCR) than in those with residual tumors. The ΔSUV_max was an independent variable associated with pCR. Furthermore, the high NLR group had poor recurrence-free survival (RFS) and overall survival. Among patients with ΔSUV_max data, high NLR (adjusted hazard ratio, 2.82; 95% confidence intervals [CI], 1.26-6.28; P = 0.016) and low ΔSUV_max (adjusted hazard ratio, 2.39; 95% CI, 1.07-5.34; P = 0.037) were independent prognostic factors for poor RFS. The categorization of the patients into four groups according to the combination of NLR and ΔSUV_max showed that patients with high NLR and low ΔSUV_max had significantly poorer RFS.

CONCLUSION

Baseline NLR and ΔSUV_max were significantly associated with the prognosis of patients with breast cancer who received neoadjuvant chemotherapy. These results suggest that metabolic non-responders with defective immune systems have worse survival outcomes.

Prognostic value of metabolic signature on 18F-FDG uptake in breast cancer patients after radiotherapy

Radiotherapy (RT) is a major modality of postoperative treatment in breast cancer. The maximal standardized value (SUVmax) is ¹⁸FDG-PET/CT derived parameter that reported to be a valuable prognostic factor in cancer patients. Herein, we aimed to identify a prognostic gene signature associated with glucose uptake for breast cancer patients after RT by leveraging the mRNA expression profiling on public datasets. The glucose uptake signature was constructed using the single sample gene set enrichment analysis (ssGSEA) algorithm and evaluated in GSE21217 where SUVmax value was measured by PET-CT directly. The prognostic value was validated in three post-RT breast cancer cohorts (GSE103744, NKI, and FUSCC databases). The patients were stratified into glucose uptake signature score-high and low groups. Patients with a higher score had worse survival than those with a lower score. Mechanistically, the glucose uptake signature was calculated in each cell type of a single-cell RNA-seq database from five breast cancer patients. Glucose uptake signature score was significantly elevated in the malignant epithelial cells compared with normal ones. The immunosuppression markers including PDCD1, TIGIT, LAG3, and HAVCR2 were significantly upregulated in the T cells bearing a high glucose uptake signature score. Collectively, our results demonstrated the potential prognostic value of a glucose uptake signature in the post-RT breast cancer patients.

Total metabolic tumor volume and spleen metabolism on baseline [18F]-FDG PET/CT as independent prognostic biomarkers of recurrence in resected breast cancer

PURPOSE

We evaluated whether biomarkers on baseline [¹⁸F]-FDG PET/CT are associated with recurrence after surgery in patients with invasive breast cancer of no special type (NST).

METHODS

In this retrospective single-center study, we included consecutive patients with non-metastatic breast cancer of NST who underwent [¹⁸F]-FDG PET/CT before treatment, including surgery, between 2011 and 2016. Clinicopathological data were collected. Tumor SUVmax, total metabolic tumor volume (TMTV), and spleen- and bone marrow-to-liver SUVmax ratios (SLR, BLR) were measured from the PET images. Cut-off values were determined using predictiveness curves to predict 5-year recurrence-free survival (5y-RFS). A multivariable prediction model was developed using Cox regression. The association with stromal tumor-infiltrating lymphocytes (TILs) levels (low if <50%) was studied by logistic regression.

RESULTS

Three hundred and three women were eligible, including 93 (31%) with triple-negative breast carcinoma. After a median follow-up of 6.2 years, 56 and 35 patients experienced recurrence and death, respectively. The 5y-RFS rate was 86%. In multivariable analyses, high TMTV (>20 cm3) and high SLR (>0.76) were associated with shorter 5y-RFS (HR 2.4, 95%CI 1.3-4.5, and HR 1.9, 95%CI 1.0-3.6). In logistic regression, high SLR was the only independent factor associated with low stromal TILs (OR 2.8, 95%CI 1.4-5.7).

CONCLUSION

High total metabolic tumor volume and high spleen glucose metabolism on baseline [¹⁸F]-FDG PET/CT were associated with poor 5y-RFS after surgical resection in patients with breast cancer of NST. Spleen metabolism was inversely correlated with stromal TILs and might be a surrogate for an immunosuppressive tumor microenvironment.

Breast cancer preoperative 18FDG-PET, overall survival prognostic separation compared with the lymph node ratio

PURPOSE

To evaluate the overall survival prognostic value of preoperative ¹⁸F-fluorodeoxyglucose positron emission tomography (PET) in breast cancer, as compared with the lymph node ratio (LNR).

METHODS

Data were abstracted at a median follow-up 14.7 years from a retrospective cohort of 104 patients who underwent PET imaging before curative surgery. PET-Axillary|Sternal was classified as PET-positive if hypermetabolism was visualized in ipsilateral nodal axillary and/or sternal region, else as PET-negative. The differences of 15 years restricted mean survival time ∆_RMST according to PET and LNR were computed from Kaplan-Meier overall survival. The effect of PET and other patients' characteristics was analyzed through rankit normalization, which provides with Cox regression the Royston-Sauerbrei D measure of separation to compare the characteristics (0 indicating no prognostic value). Multivariate analysis of the normalized characteristics used stepwise selection with the Akaike information criterion.

RESULTS

In Kaplan-Meier analysis, LNR > 0.20 versus ≤ 0.20 showed ∆_RMST = 3.4 years, P = 0.003. PET-Axillary|Sternal positivity versus PET-negative showed a ∆_RMST = 2.6 years, P = 0.008. In Cox univariate analyses, LNR appeared as topmost prognostic separator, D = 1.50, P < 0.001. PET ranked below but was also highly significant, D = 1.02, P = 0.009. In multivariate analyses, LNR and PET-Axillary|Sternal were colinear and mutually exclusive. PET-Axillary|Sternal improved as prognosticator in a model excluding lymph nodes, yielding a normalized hazard ratio of 2.44, P = 0.062.

CONCLUSION

Pathological lymph node assessment remains the gold standard of prognosis. However, PET appears as a valuable surrogate in univariate analysis at 15-year follow-up. There was a trend towards significance in multivariate analysis that warrants further investigation.

Positron Emission Tomography for Response Evaluation in Microenvironment-Targeted Anti-Cancer Therapy

Therapeutic response is evaluated using the diameter of tumors and quantitative parameters of 2-[¹⁸F] fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET). Tumor response to molecular-targeted drugs and immune checkpoint inhibitors is different from conventional chemotherapy in terms of temporal metabolic alteration and morphological change after the therapy. Cancer stem cells, immunologically competent cells, and metabolism of cancer are considered targets of novel therapy. Accumulation of FDG reflects the glucose metabolism of cancer cells as well as immune cells in the tumor microenvironment, which differs among patients according to the individual immune function; however, FDG-PET could evaluate the viability of the tumor as a whole. On the other hand, specific imaging and cell tracking of cancer cell or immunological cell subsets does not elucidate tumor response in a complexed interaction in the tumor microenvironment. Considering tumor heterogeneity and individual variation in therapeutic response, a radiomics approach with quantitative features of multimodal images and deep learning algorithm with reference to pathologic and genetic data has the potential to improve response assessment for emerging cancer therapy.

Usefulness of Hybrid PET/MRI in Clinical Evaluation of Head and Neck Cancer Patients

(1) Background: The novel hybrid of positron emission tomography/magnetic resonance (PET/MR) examination has been introduced to clinical practice. The aim of our study was to evaluate PET/MR usefulness in preoperative staging of head and neck cancer (HNC) patients (pts); (2) Methods: Thirty eight pts underwent both computed tomography (CT) and PET/MR examination, of whom 21 pts underwent surgical treatment as first-line therapy and were further included in the present study. Postsurgical tissue material was subjected to routine histopathological (HP) examination with additional evaluation of p16, human papillomavirus (HPV), Epstein-Barr virus (EBV) and Ki67 status. Agreement of clinical and pathological T staging, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of CT and PET/MR in metastatic lymph nodes detection were defined. The verification of dependences between standardized uptake value (SUV value), tumor geometrical parameters, number of metastatic lymph nodes in PET/MR and CT, biochemical parameters, Ki67 index, p16, HPV and EBV status was made with statistical analysis of obtained results; (3) Results: PET/MR is characterized by better agreement in T staging, higher specificity, sensitivity, PPV and NPV of lymph nodes evaluation than CT imaging. Significant correlations were observed between SUVmax and maximal tumor diameter from PET/MR, between SUVmean and CT tumor volume, PET/MR tumor volume, maximal tumor diameter assessed in PET/MR. Other correlations were weak and insignificant; (4) Conclusions: Hybrid PET/MR imaging is useful in preoperative staging of HNC. Further studies are needed.

Examining the evolving utility of 18FDG-PET/CT in breast cancer recurrence

Many studies have demonstrated the utility of ¹⁸fluorodeoxyglucose-positron emission tomography/computed tomography (¹⁸FDG-PET/CT) scan in evaluating breast cancer recurrence in subsets of patients based on age, histological subtype and cancer stage to guide response to conventional chemoradiation guidelines during treatment of metastatic breast cancer disease. This literature review focuses on the breakthrough of ¹⁸FDG-PET/CT imaging within the paradigm of breast cancer oncology centered toward improving risk stratification and prognostication of disease relapse based on cancer molecular phenotypes, tumor markers, early metabolic activity and response to neoadjuvant chemotherapy (NAC). The authors consider the rapid shift toward biomarker based molecular tracers to quantify treatment response and pathologic complete response with more recent imaging modalities such as dedicated breast positron emission tomography (dbPET), and the advantages afforded by this multisystem approach.