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

Splenic Elemental Composition of Breast Cancer-Suffering Rats Supplemented with Pomegranate Seed Oil and Bitter Melon Extract

The aim of this study was to investigate how dietary modifications with pomegranate seed oil (PSO) and bitter melon aqueous extract (BME) affect mineral content in the spleen of rats both under normal physiological conditions and with coexisting mammary tumorigenesis. The diet of Sprague-Dawley female rats was supplemented either with PSO or with BME, or with a combination for 21 weeks. A chemical carcinogen (7,12-dimethylbenz[a]anthracene) was applied intragastrically to induce mammary tumors. In the spleen of rats, the selected elements were determined with a quadrupole mass spectrometer with inductively coupled plasma ionization (ICP-MS). ANOVA was used to evaluate differences in elemental composition among experimental groups. Multivariate statistical methods were used to discover whether some subtle dependencies exist between experimental factors and thus influence the element content. Experimental factors affected the splenic levels of macroelements, except for potassium. Both diet modification and the cancerogenic process resulted in significant changes in the content of Fe, Se, Co, Cr, Ni, Al, Sr, Pb, Cd, B, and Tl in rat spleen. Chemometric analysis revealed the greatest impact of the ongoing carcinogenic process on the mineral composition of the spleen. The obtained results may contribute to a better understanding of peripheral immune organ functioning, especially during the neoplastic process, and thus may help develop anticancer prevention and treatment strategies.

A chest CT-based nomogram for predicting survival in acute myeloid leukemia

BACKGROUND

The identification of survival predictors is crucial for early intervention to improve outcome in acute myeloid leukemia (AML). This study aim to identify chest computed tomography (CT)-derived features to predict prognosis for acute myeloid leukemia (AML).

METHODS

952 patients with pathologically-confirmed AML were retrospectively enrolled between 2010 and 2020. CT-derived features (including body composition and subcutaneous fat features), were obtained from the initial chest CT images and were used to build models to predict the prognosis. A CT-derived MSF nomogram was constructed using multivariate Cox regression incorporating CT-based features. The performance of the prediction models was assessed with discrimination, calibration, decision curves and improvements.

RESULTS

Three CT-derived features, including myosarcopenia, spleen_CTV, and SF_CTV (MSF) were identified as the independent predictors for prognosis in AML (P < 0.01). A CT-MSF nomogram showed a performance with AUCs of 0.717, 0.794, 0.796 and 0.792 for predicting the 1-, 2-, 3-, and 5-year overall survival (OS) probabilities in the validation cohort, which were significantly higher than the ELN risk model. Moreover, a new MSN stratification system (MSF nomogram plus ELN risk model) could stratify patients into new high, intermediate and low risk group. Patients with high MSN risk may benefit from intensive treatment (P = 0.0011).

CONCLUSIONS

In summary, the chest CT-MSF nomogram, integrating myosarcopenia, spleen_CTV, and SF_CTV features, could be used to predict prognosis of AML.

Hyperpolarized [1-13C]-pyruvate MRS evaluates immune potential and predicts response to radiotherapy in cervical cancer

BACKGROUND

Monitoring pyruvate metabolism in the spleen is important for assessing immune activity and achieving successful radiotherapy for cervical cancer due to the significance of the abscopal effect. We aimed to explore the feasibility of utilizing hyperpolarized (HP) [1-13C]-pyruvate magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to evaluate pyruvate metabolism in the human spleen, with the aim of identifying potential candidates for radiotherapy in cervical cancer.

METHODS

This prospective study recruited six female patients with cervical cancer (median age 55 years; range 39-60) evaluated using HP [1-13C]-pyruvate MRI/MRS at baseline and 2 weeks after radiotherapy. Proton (1H) diffusion-weighted MRI was performed in parallel to estimate splenic cellularity. The primary outcome was defined as tumor response to radiotherapy. The Student t-test was used for comparing 13C data between the groups.

RESULTS

The splenic HP [1-13C]-lactate-to-total carbon (tC) ratio was 5.6-fold lower in the responders than in the non-responders at baseline (p = 0.009). The splenic [1-13C]-lactate-to-tC ratio revealed a 1.7-fold increase (p = 0.415) and the splenic [1-13C]-alanine-to-tC ratio revealed a 1.8-fold increase after radiotherapy (p = 0.482). The blood leukocyte differential count revealed an increased proportion of neutrophils two weeks following treatment, indicating enhanced immune activity (p = 0.013). The splenic apparent diffusion coefficient values between the groups were not significantly different.

CONCLUSIONS

This exploratory study revealed the feasibility of HP [1-13C]-pyruvate MRS of the spleen for evaluating baseline immune potential, which was associated with clinical outcomes of cervical cancer after radiotherapy.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04951921 , registered 7 July 2021.

RELEVANCE STATEMENT

This prospective study revealed the feasibility of using HP 13C MRI/MRS for assessing pyruvate metabolism of the spleen to evaluate the patients' immune potential that is associated with radiotherapeutic clinical outcomes in cervical cancer.

KEY POINTS

• Effective radiotherapy induces abscopal effect via altering immune metabolism. • Hyperpolarized 13C MRS evaluates patients' immune potential non-invasively. • Pyruvate-to-lactate conversion in the spleen is elevated following radiotherapy.

Improved automated tumor segmentation in whole-body 3D scans using multi-directional 2D projection-based priors

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end-to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

Elevated splenic 18F-fluorodeoxyglucose positron emission tomography/computed tomography activity is associated with 5-year risk of recurrence in non-metastatic invasive ductal carcinoma of the breast

OBJECTIVE

To construct prediction models including baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters of tumoural lesions and non-tumour lymphoid tissue for recurrence-free survival within 5 years (5y-RFS) after imaging examination in patients with invasive ductal carcinomas (IDCs) of the breast.

METHODS

The study included 101 consecutive female patients. Univariable and multivariable Cox regression were used to identify clinicopathological and metabolic parameters associated with risk of recurrence. Four prediction models based on the results of multivariable analysis were constructed and visualized as nomograms. Performance of each nomogram was evaluated using the concordance index (C-index), integrated discrimination improvement, decision curve analysis (DCA), and calibration curve.

RESULTS

N3 status, total metabolic tumour volume, the maximum standardized uptake value of spleen, and spleen-to-liver ratio were significant predictors of 5y-RFS. The nomogram including all significant predictors demonstrated superior predictive performance for 5y-RFS, with a C-index of 0.907 (95% CI, 0.833-0.981), greatest net benefit on DCA, good accuracy on calibration curves, and excellent risk stratification on Kaplan-Meier curves.

CONCLUSIONS

The model that included metabolic parameters of the spleen had the best performance for predicting 5y-RFS in patients with IDCs of the breast. This model may guide personalized treatment decisions and inform patients and clinicians about prognosis.

ADVANCES IN KNOWLEDGE

This research identifies 18F-FDG PET/CT metabolic parameters of non-tumour lymphoid tissue as predictors of recurrence in breast cancer.

18F-FDG PET/CT-based deep learning radiomics predicts 5-years disease-free survival after failure to achieve pathologic complete response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

This study aimed to assess whether a combined model incorporating radiomic and depth features extracted from PET/CT can predict disease-free survival (DFS) in patients who failed to achieve pathologic complete response (pCR) after neoadjuvant chemotherapy.

RESULTS

This study retrospectively included one hundred and five non-pCR patients. After a median follow-up of 71 months, 15 and 7 patients experienced recurrence and death, respectively. The primary tumor volume underwent feature extraction, yielding a total of 3644 radiomic features and 4096 depth features. The modeling procedure employed Cox regression for feature selection and utilized Cox proportional-hazards models to make predictions on DFS. Time-dependent receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were utilized to evaluate and compare the predictive performance of different models. 2 clinical features (RCB, cT), 4 radiomic features, and 7 depth features were significant predictors of DFS and were included to develop models. The integrated model incorporating RCB, cT, and radiomic and depth features extracted from PET/CT images exhibited the highest accuracy for predicting 5-year DFS in the training (AUC 0.943) and the validation cohort (AUC 0.938).

CONCLUSION

The integrated model combining radiomic and depth features extracted from PET/CT images can accurately predict 5-year DFS in non-pCR patients. It can help identify patients with a high risk of recurrence and strengthen adjuvant therapy to improve survival.

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.

Advances in PET/CT Imaging for Breast Cancer

One out of eight women will be affected by breast cancer during her lifetime. Imaging plays a key role in breast cancer detection and management, providing physicians with information about tumor location, heterogeneity, and dissemination. In this review, we describe the latest advances in PET/CT imaging of breast cancer, including novel applications of 18F-FDG PET/CT and the development and testing of new agents for primary and metastatic breast tumor imaging and therapy. Ultimately, these radiopharmaceuticals may guide personalized approaches to optimize treatment based on the patient's specific tumor profile, and may become a new standard of care. In addition, they may enhance the assessment of treatment efficacy and lead to improved outcomes for patients with a breast cancer diagnosis.

Relationship of FDG Uptake of the Reticuloendothelial System with Tumor Immune Microenvironment and Prognosis in Patients with Gastric Cancer

2-deoxy-2-[18F]fluoro-D-glucose (FDG) uptake of the reticuloendothelial system, including the bone marrow (BM) and spleen, on positron emission tomography/computed tomography (PET/CT) has been shown to be a significant prognostic factor in diverse malignancies. However, the relationship between FDG uptake of the BM and spleen and histopathological findings, including the tumor immune microenvironment, has not been fully evaluated. This study aimed to investigate the relationship of FDG uptake in the BM and spleen with histopathological findings and recurrence-free survival (RFS) in patients with gastric cancer. Seventy patients with gastric cancer who underwent pre-operative FDG PET/CT and subsequent curative surgery were retrospectively enrolled. On image analysis, the BM-to-liver uptake ratio (BLR) and spleen-to-liver uptake ratio (SLR) were measured from PET/CT images, and on immunohistochemical analysis, the densities of immune cell infiltration in the tumor tissue were graded. The BLR and SLR showed significant positive correlations with the grades of CD163 cell and CD8 cell infiltration in the tumor tissue, respectively (p < 0.05). In multivariate survival analysis, both BLR and SLR were significant predictors of RFS (p < 0.05). FDG uptake in the BM and spleen might be potential imaging biomarkers for evaluating tumor immune microenvironment conditions and predicting RFS in patients with gastric cancer.

Advances in PET/CT Imaging for Breast Cancer Patients and Beyond

Breast cancer is the most common cancer in women around the world and the fifth leading cause of cancer-related death [...].

Predicting treatment outcomes using 18F-FDG PET biomarkers in patients with non-small-cell lung cancer receiving chemoimmunotherapy

Background

Predictive markers for treatment response and survival outcome have not been identified in patients with advanced non-small-cell lung cancer (NSCLC) receiving chemoimmunotherapy. We aimed to evaluate whether imaging biomarkers of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) and routinely assessed clinico-laboratory values were associated with clinical outcomes in patients with advanced NSCLC receiving pembrolizumab plus platinum-doublet chemotherapy as a first-line treatment.

Methods

We retrospectively enrolled 52 patients with advanced NSCLC who underwent baseline ¹⁸F-FDG PET/CT before treatment initiation. PET/CT parameters and clinico-laboratory variables, constituting the prognostic immunotherapy scoring system, were collected. Optimal cut-off values for PET/CT parameters were determined using the maximized log-rank test for progression-free survival (PFS). A multivariate prediction model was developed based on Cox models for PFS, and a scoring system was established based on hazard ratios of the predictive factors.

Results

During the median follow-up period of 16.7 months (95% confidence interval: 15.7-17.7 months), 43 (82.7%) and 31 (59.6%) patients experienced disease progression and death, respectively. Objective response was observed in 23 (44.2%) patients. In the multivariate analysis, maximum standardized uptake value, metabolic tumour volume_2.5, total lesion glycolysis_2.5, and bone marrow-to-liver uptake ratio from the PET/CT variables and neutrophil-to-lymphocyte ratio (NLR) from the clinico-laboratory variables were independently associated with PFS. The scoring system based on these independent predictive variables significantly predicted the treatment response, PFS, and overall survival.

Conclusion

PET/CT variables and NLR were useful biomarkers for predicting outcomes of patients with NSCLC receiving pembrolizumab and chemotherapy as a first-line treatment, suggesting their potential as effective markers for combined PD-1 blockade and chemotherapy.

First-Line Pembrolizumab Mono- or Combination Therapy of Non-Small Cell Lung Cancer: Baseline Metabolic Biomarkers Predict Outcomes

Simple Summary

Positron-emission tomography/computed tomography (PET/CT) is used for staging of non-small cell lung cancer (NSCLC) and can help to estimate prognosis in patients treated with immune checkpoint inhibitor (ICI) therapy. Most available data in that field were derived from cohorts treated in higher therapy lines using ICI monotherapy with different drugs. Currently, however, most advanced NSCLC patients receive first-line ICI treatment, often in combination with cytotoxic chemotherapy. We evaluated prognostic PET/CT biomarkers in 85 patients receiving first-line ICI, 70 (82%) of them as a chemotherapy–ICI combination. We found that patients with a higher metabolically active tumor volume (MTV) had a significantly poorer survival and lower radiological response rate. In patients with high MTV, a concomitantly low bone marrow to liver ratio indicated a better prognosis. Our results demonstrate that PET/CT-derived biomarkers can aid therapeutic decision-making in ICI-treated NSCLC.

Abstract

Quantitative biomarkers derived from positron-emission tomography/computed tomography (PET/CT) have been suggested as prognostic variables in immune-checkpoint inhibitor (ICI) treated non-small cell lung cancer (NSCLC). As such, data for first-line ICI therapy and especially for chemotherapy–ICI combinations are still scarce, we retrospectively evaluated baseline ¹⁸F-FDG-PET/CT of 85 consecutive patients receiving first-line pembrolizumab with chemotherapy (n = 70) or as monotherapy (n = 15). Maximum and mean standardized uptake value, total metabolic tumor volume (MTV), total lesion glycolysis, bone marrow-/and spleen to liver ratio (BLR/SLR) were calculated. Kaplan–Meier analyses and Cox regression models were used to assess progression-free/overall survival (PFS/OS) and their determinant variables. Median follow-up was 12 months (M; 95% confidence interval 10–14). Multivariate selection for PFS/OS revealed MTV as most relevant PET/CT biomarker (p < 0.001). Median PFS/OS were significantly longer in patients with MTV ≤ 70 mL vs. >70 mL (PFS: 10 M (4–16) vs. 4 M (3–5), p = 0.001; OS: not reached vs. 10 M (5–15), p = 0.004). Disease control rate was 81% vs. 53% for MTV ≤/> 70 mL (p = 0.007). BLR ≤ 1.06 vs. >1.06 was associated with better outcomes (PFS: 8 M (4–13) vs. 4 M (3–6), p = 0.034; OS: 19 M (12-/) vs. 6 M (4–12), p = 0.005). In patients with MTV > 70 mL, concomitant BLR ≤ 1.06 indicated a better prognosis. Higher MTV is associated with inferior PFS/OS in first-line ICI-treated NSCLC, with BLR allowing additional risk stratification.

Prognostic value of inflammatory response biomarkers using peripheral blood and [18F]-FDG PET/CT in advanced NSCLC patients treated with first-line chemo- or immunotherapy

OBJECTIVES

We aimed to compare the prognostic value of inflammatory biomarkers extracted from pretreatment peripheral blood and [18F]-FDG PET for estimating outcomes in non-small cell lung cancer (NSCLC) patients treated with first-line immunotherapy (IT) or chemotherapy (CT).

MATERIALS AND METHODS

In this retrospective multicenter study, we evaluated 111 patients with advanced NSCLC who underwent baseline [18F]-FDG PET/CT before IT or CT between 2016 and 2019. Several blood inflammatory indices were evaluated: derived neutrophil-to-lymphocyte ratio (dNLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP) and systemic immune-inflammation index (SII). FDG-PET inflammatory parameters were extracted from lymphoid tissues (BLR and SLR: bone marrow or spleen-to-Liver SUVmax ratios). Association with survival and relationships between parameters were evaluated using Cox prediction models and Spearman's correlation respectively.

RESULTS

Overall, 90 patients were included (IT:CT) (51:39pts). Median PFS was 8.6:6.6 months and median OS was not reached:21.2 months. In the IT cohort, high dNLR (>3), high SII (≥1,270) and high SLR (0.77) were independent statistically significant prognostic factors for one-year progression-free survival (1y-PFS) and two-year overall survival (2y-OS) on multivariable analysis. In the CT cohort, high BLR (≥0.80) and high dNLR (>3) were associated with shorter 1y-PFS (HR 2.2, 95% CI 1.0-4.9) and 2y-OS (HR 3.4, 95CI 1.1-10.3) respectively, on multivariable analysis. Finally, BLR significantly but moderately correlated with most blood-based inflammatory indices (CRP, PLR and SII) while SLR was only associated with CRP (p < 0.01 for all).

CONCLUSION

In advanced NSCLC patients undergoing first-line IT or CT, pretreatment blood and inflammatory factors evaluating the spleen or bone marrow on [18F]-FDG PET/CT provided prognostic information for 1y-PFS and 2y-OS. These biomarkers should be further evaluated for potential clinical application.