Biological correlates of tumor perfusion and its heterogeneity in newly diagnosed breast cancer using dynamic first-pass 18F-FDG PET/CT

Value of Dynamic 18F-FDG PET/CT in Predicting the Success of Neoadjuvant Chemotherapy in Patients with Locally Advanced Breast Cancer: A Prospective Study

Objectives

This prospective study was planned to compare the predictive value of dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in locally advanced breast cancer patients (LABC) receiving neoadjuvant chemotherapy (NAC).

Methods

Twenty seven patients with LABC [median age: 47, (26-66)] underwent a dynamic 18F-FDG PET study at baseline, and after 2-3 cycles of (NAC) were included (interim). Maximum standardized uptake value (SUVmax) values and SUV ratios for the 2nd, 5th, 10th, and 30th minutes and dynamic curve slope (SL) values and SL ratios were measured using 18F-FDG dynamic data. In addition, the values of SUVmean (2minSUVmean), SULpeak (2minSULpeak), metabolic volume (2minVol), and total lesion glycolysis (2minTLG) were measured for the first 2 min. Percent changes between baseline and interim studies were calculated and compared with the pathological results as the pathological complete response (PCR) or the pathological non-complete response (non-PCR). Receiver operating characteristic curves were obtained to calculate the area under the curve to predict PCR. Optimal threshold values were calculated to discriminate between PCR and non-PCR groups.

Results

Baseline study SUV 30 (p=0.044), SUV 30/2 (p=0.041), SUV 30/5 (p=0.049), SUV 30/10 (p=0.021), SL 30/2 (p=0.029) and SL 30/5 (p=0.027) values were statistically significant different between PCR and non-PCR groups. The percentage changes of 2minVol between PCR and non-PCR groups were statistically significant. For the threshold value of -67.6% change in 2minVol, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 87.2%, 77.8%, 63.6%, 93.3%, and 80.7%, respectively (area under the curve: 0.826, p=0.009).

Conclusion

Semiquantitative parameters for dynamic 18F-FDG PET can predict PCR. % changes in 2minVol can identify non-responding patients better than other parameters.

18F-FDG PET/CT radiomics signature and clinical parameters predict progression-free survival in breast cancer patients: A preliminary study

Introduction

This study aimed to investigate the feasibility of predicting progression-free survival (PFS) in breast cancer patients using pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) radiomics signature and clinical parameters.

Methods

Breast cancer patients who underwent 18F-FDG PET/CT imaging before treatment from January 2012 to December 2020 were eligible for study inclusion. Eighty-seven patients were randomly divided into training (n = 61) and internal test sets (n = 26) and an additional 25 patients were used as the external validation set. Clinical parameters, including age, tumor size, molecularsubtype, clinical TNM stage, and laboratory findings were collected. Radiomics features were extracted from preoperative PET/CT images. Least absolute shrinkage and selection operators were applied to shrink feature size and build a predictive radiomics signature. Univariate and multivariate Cox proportional hazards models and Kaplan-Meier analysis were used to assess the association of rad-score and clinical parameter with PFS. Nomograms were constructed to visualize survival prediction. C-index and calibration curve were used to evaluate nomogram performance.

Results

Eleven radiomics features were selected to generate rad-score. The clinical model comprised three parameters: clinical M stage, CA125, and pathological N stage. Rad-score and clinical-model were significantly associated with PFS in the training set (P< 0.01) but not the test set. The integrated clinical-radiomics (ICR) model was significantly associated with PFS in both the training and test sets (P< 0.01). The ICR model nomogram had a significantly higher C-index than the clinical model and rad-score in the training and test sets. The C-index of the ICR model in the external validation set was 0.754 (95% confidence interval, 0.726–0.812). PFS significantly differed between the low- and high-risk groups stratified by the nomogram (P = 0.009). The calibration curve indicated the ICR model provided the greatest clinical benefit.

Conclusion

The ICR model, which combined clinical parameters and preoperative 18F-FDG PET/CT imaging, was able to independently predict PFS in breast cancer patients and was superior to the clinical model alone and rad-score alone.

The influence of receptor expression and clinical subtypes on baseline [18F]FDG uptake in breast cancer: systematic review and meta-analysis

BACKGROUND

To quantify the relationship between [18F]FDG uptake of the primary tumour measured by PET-imaging with immunohistochemical (IHC) expression of ER, PR, HER2, Ki-67, and clinical subtypes based on these markers in breast cancer patients.

METHODS

PubMed and Embase were searched for studies that compared SUVmax between breast cancer patients negative and positive for IHC expression of ER, PR, HER2, Ki-67, and clinical subtypes based on these markers. Two reviewers independently screened the studies and extracted the data. Standardized mean differences (SMD) and 95% confidence intervals (CIs) were estimated by using DerSimonian-Laird random-effects models. P values less than or equal to 5% indicated statistically significant results.

RESULTS

Fifty studies were included in the final analysis. SUVmax is significantly higher in ER-negative (31 studies, SMD 0.66, 0.56-0.77, P < 0.0001), PR-negative (30 studies, SMD 0.56; 0.40-0.71, P < 0.0001), HER2-positive (32 studies, SMD - 0.29, - 0.49 to - 0.10, P = 0.0043) or Ki-67-positive (19 studies, SMD - 0.77; - 0.93 to - 0.61, P < 0.0001) primary tumours compared to their counterparts. The majority of clinical subtypes were either luminal A (LA), luminal B (LB), HER2-positive or triple negative breast cancer (TNBC). LA is associated with significantly lower SUVmax compared to LB (11 studies, SMD - 0.49, - 0.68 to - 0.31, P = 0.0001), HER2-positive (15 studies, SMD - 0.91, - 1.21 to - 0.61, P < 0.0001) and TNBC (17 studies, SMD - 1.21, - 1.57 to - 0.85, P < 0.0001); and LB showed significantly lower uptake compared to TNBC (10 studies, SMD - 0.77, - 1.05 to - 0.49, P = 0.0002). Differences in SUVmax between LB and HER2-positive (9 studies, SMD - 0.32, - 0.88 to 0.24, P = 0.2244), and HER2-positive and TNBC (17 studies, SMD - 0.29, - 0.61 to 0.02, P = 0.0667) are not significant.

CONCLUSION

Primary tumour SUVmax is significantly higher in ER-negative, PR-negative, HER2-positive and Ki-67-positive breast cancer patients. Luminal tumours have the lowest and TNBC tumours the highest SUVmax. HER2 overexpression has an intermediate effect.

Radiomics in Oncological PET Imaging: A Systematic Review—Part 1, Supradiaphragmatic Cancers

Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia and assess its quality, we performed a literature search in the PubMed database up to 18 February 2022. Inclusion criteria were: studies based on human data; at least one specified tumor type; supradiaphragmatic malignancy; performing radiomics on PET imaging. Exclusion criteria were: studies only based on phantom or animal data; technical articles without a clinically oriented question; fewer than 30 patients in the training cohort. A review database containing PMID, year of publication, cancer type, and quality criteria (number of patients, retrospective or prospective nature, independent validation cohort) was constructed. A total of 220 studies met the inclusion criteria. Among them, 119 (54.1%) studies included more than 100 patients, 21 studies (9.5%) were based on prospectively acquired data, and 91 (41.4%) used an independent validation set. Most studies focused on prognostic and treatment response objectives. Because the textural parameters and methods employed are very different from one article to another, it is complicated to aggregate and compare articles. New contributions and radiomics guidelines tend to help improving quality of the reported studies over the years.

Cancer Angiogenesis and Opportunity of Influence on Tumor by Changing Vascularization

Based on the study of recent scientific literature devoted to neovascularization and angiogenesis in malignant neoplasms, it was concluded that there are many publications on each of the problems of tumor angiogenesis and vascularization. The formation of blood vessels in a tumor and certain aspects of the prognostic value of the severity of vascularization in almost all forms of cancer are considered. Special attention is paid to the peculiarities of angiogenesis in tumors of the female reproductive system. A large number of vessels in the tumor often indicates a poor prognosis. The influence of various factors on the initiation of angiogenesis and the process itself, as well as the possibility of suppressing such signals to slow down the formation of blood vessels and thus the development of the tumor are widely studied. The results of pharmacological suppression of tumor vessel formation demonstrate a good clinical outcome but one accompanied by a large number of severe adverse side effects. Such a significant amount of studies on each of the problems of tumor vascularization indicates the increasing importance of this area of oncology. At the same time, only a very small number of works are devoted to the study of the differences in angiogenesis and number of vessels between different parts of the tumor, as well as between the primary tumor node and its metastases. The refinement of the results is still to be done. It was noted that the expression of proangiogenic factors in metastases is usually higher than in the source of metastasis, and the expression in lymphogenous metastases is higher than in hematogenous ones.

Tumors Are Evolutionary Island-Like Ecosystems

Integration of ecological and evolutionary features has begun to understand the interplay of tumor heterogeneity, microenvironment, and metastatic potential. Developing a theoretical framework is intrinsic to deciphering tumors' tremendous spatial and longitudinal genetic variation patterns in patients. Here, we propose that tumors can be considered evolutionary island-like ecosystems, that is, isolated systems that undergo evolutionary and spatiotemporal dynamic processes that shape tumor microenvironments and drive the migration of cancer cells. We examine attributes of insular systems and causes of insularity, such as physical distance and connectivity. These properties modulate migration rates of cancer cells through processes causing spatial and temporal isolation of the organs and tissues functioning as a supply of cancer cells for new colonizations. We discuss hypotheses, predictions, and limitations of tumors as islands analogy. We present emerging evidence of tumor insularity in different cancer types and discuss their relevance to the islands model. We suggest that the engagement of tumor insularity into conceptual and mathematical models holds promise to illuminate cancer evolution, tumor heterogeneity, and metastatic potential of cells.

Scoring system for gallbladder polyps based on the cross-sectional area and patient characteristics

BACKGROUND

Current management guidelines for gallbladder polyps (GBPs) focus on a diameter more than 1 cm as an indication for cholecystectomy. Since most GBPs are not malignant, unnecessary cholecystectomies can lead to unnecessary complications and costs. We developed a score to identify true polyps focusing on their cross-sectional area (CSA).

METHODS

We retrospectively analyzed the demographic, clinical, laboratory, and sonographic characteristics of 522 patients with GBPs who had undergone cholecystectomy at our hospital between January 2010 and July 2020 (reference group). We used univariate analysis to compare these parameters between 88 true polyps and 434 pseudopolyps and multivariate logistic regression analysis to identify parameters to include in our scoring model. Receiver operating characteristics and area under the curve were used to identify cut-off values. The model was tested on a validation group of 98 patients.

RESULTS

In the multivariate analysis, a CSA >123 mm², positive blood flow signal, age >55.5 years, alanine aminotransferase (ALT) levels > 50 U/L, and an ALT/aspartate aminotransferase ratio > 0.77 were significantly associated with true polyps (odds ratio 6.528, 2.377, 2.617, 2.445, and -0.372, respectively). A prediction model based on cut-off values was used to distinguish a low-risk and high-risk GBP group; true polyps accounted for 6.54% and 58.72%, respectively (p < 0.001). In the low-risk and high-risk validation groups, true polyps comprised 12.35% and 82.35%, respectively (p < 0.001).

CONCLUSIONS

Our scoring system shows high accuracy and specificity in identifying true polyps and helps determine the need for surgical resection.

A multicompartment model for intratumor tissue-specific analysis of DCE-MRI using non-negative matrix factorization

PURPOSE

A pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data is subject to inaccuracy and instability partly owing to the partial volume effect (PVE). We proposed a new multicompartment model for a tissue-specific pharmacokinetic analysis in DCE-MRI data to solve the PVE problem and to provide better kinetic parameter maps.

METHODS

We introduced an independent parameter named fractional volumes of tissue compartments in each DCE-MRI pixel to construct a new linear separable multicompartment model, which simultaneously estimates the pixel-wise time-concentration curves and fractional volumes without the need of the pure-pixel assumption. This simplified convex optimization model was solved using a special type of non-negative matrix factorization (NMF) algorithm called the minimum-volume constraint NMF (MVC-NMF).

RESULTS

To test the model, synthetic datasets were established based on the general pharmacokinetic parameters. On well-designed synthetic data, the proposed model reached lower bias and lower root mean square fitting error compared to the state-of-the-art algorithm in different noise levels. In addition, the real dataset from QIN-BREAST-DCE-MRI was analyzed, and we observed an improved pharmacokinetic parameter estimation to distinguish the treatment response to chemotherapy applied to breast cancer.

CONCLUSION

Our model improved the accuracy and stability of the tissue-specific estimation of the fractional volumes and kinetic parameters in DCE-MRI data, and improved the robustness to noise, providing more accurate kinetics for more precise prognosis and therapeutic response evaluation using DCE-MRI.

A Systematic Review of PET Textural Analysis and Radiomics in Cancer

Background: Although many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies. Methods: PubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted. Results: A total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20–1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1–286). Conclusions: PET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.

PET Imaging of Tumor Perfusion: A Potential Cancer Biomarker?

Perfusion, as measured by imaging, is considered a standard of care biomarker for the evaluation of many tumors. Measurements of tumor perfusion may be used in a number of ways, including improving the visual detection of lesions, differentiating malignant from benign findings, assessing aggressiveness of tumors, identifying ischemia and by extension hypoxia within tumors, and assessing treatment response. While most clinical perfusion imaging is currently performed with CT or MR, a number of methods for PET imaging of tumor perfusion have been described. The inert PET radiotracer ¹⁵O-water PET represents the recognized gold standard for absolute quantification of tissue perfusion in both normal tissue and a variety of pathological conditions including cancer. Other cancer PET perfusion imaging strategies include the use of radiotracers with high first-pass uptake, analogous to those used in cardiac perfusion PET. This strategy produces more visually pleasing high-contrast images that provide relative rather than absolute perfusion quantification. Lastly, multiple timepoint imaging of PET tracers such as ¹⁸F-FDG, are not specifically optimized for perfusion, but have advantages related to availability, convenience, and reimbursement. Multiple obstacles have thus far blocked the routine use of PET imaging for tumor perfusion, including tracer production and distribution, image processing, patient body coverage, clinical validation, regulatory approval and reimbursement, and finally feasible clinical workflows. Fortunately, these obstacles are being overcome, especially within larger imaging centers, opening the door for PET imaging of tumor perfusion to become standard clinical practice. In the foreseeable future, it is possible that whole-body PET perfusion imaging with ¹⁵O-water will be able to be performed in a single imaging session concurrent with standard PET imaging techniques such as ¹⁸F-FDG-PET. This approach could establish an efficient clinical workflow. The resultant ability to measure absolute tumor blood flow in combination with glycolysis will provide important complementary information to inform prognosis and clinical decisions.

Overexpression of METTL3 associated with the metabolic status on 18F-FDG PET/CT in patients with Esophageal Carcinoma

Background: To investigate the expression of methyltransferase 3 (METTL3) and its relationship with ¹⁸F-FDG uptake in patients with esophageal carcinoma (ESCA). Materials and methods: This study analyzed the expression of METTL3 in ESCA and its relationship with clinicopathological features by The Cancer Genome Atlas (TCGA) database. Immunohistochemical staining was performed on 57 tumor tissues of ESCA patients who underwent PET/CT scan before surgery to evaluate the expression of METTL3, glucose transporter 1 (GLUT1), and hexokinase 2 (HK2) in tumor tissues and peritumoral tissues. Analyze the relationship between SUVmax with METTL3, HK2, and GLUT1 expression. Results: The expression of METTL3, GLUT1, and HK2 was significantly increased in ESCA tissues compared with normal tissues (p < 0.001). The expression of METTL3 was correlated with tumor size and histological differentiation (p < 0.05), and there was no significant difference between age, sex, pathological types, tumor staging, or lymph node metastasis (p > 0.05). The SUVmax was significantly higher in tumors with high METTL3 expression (17.822±6.249) compared to low METTL3 expression (9.573±5.082) (p < 0.001). There was a positive correlation between the SUVmax and METTL3 expression in ESCA (r² = 0.647, p < 0.001). Multivariate analysis confirmed the association between SUVmax and METTL3 expression (p < 0.05). GLUT1 and HK2 expression in ESCA was positively correlated with ¹⁸F-FDG uptake and METTL3 status (p < 0.001). Conclusions: The high expression of METTL3 is related to the high SUVmax in ESCA, and METTL3 may increase ¹⁸F-FDG uptake by regulating GLUT1 and HK2.