Prognostic Value of Dual-Time-Point 18F-Fluorodeoxyglucose PET/CT in Metastatic Breast Cancer: An Exploratory Study of Quantitative Measures

Naghavi-Behzad, Mohammad; Petersen, Charlotte Bjerg; Vogsen, Marianne; Braad, Poul-Erik; Gerke, Oke

doi:10.3390/diagnostics10060398

Cited by 5 publications

(6 citation statements)

References 19 publications

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“…Tumor aggressiveness evaluated using SUVmax and whole-body tumor volume evaluated using MTV or TLG may be effective predictors for treatment efficacy and prognosis; the volume-based parameters derived from PET are especially useful in MBC. In line with this finding, TLG or MTV were strongly correlated with the OS of patients with MBC rather than SUVmax (12,16,17). Interestingly, the prognostic values of quantitative metabolic parameters for MBC differed depending on metastatic sites (18).…”

Section: Discussionsupporting

confidence: 58%

Total Lesion Glycolysis Levels as Predictive Indicators in Patients With Metastatic and Recurrent Breast Cancer Undergoing Endocrine Therapy With or Without CDK4/6 Inhibitor

et al. 2022

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Background/Aim: Endocrine therapy (ET) with or without CDK4/6 inhibitors is the primary treatment choice for patients with estrogen receptor (ER)-positive and HER2-negative subtype of metastatic breast cancer (MBC). We examined the metabolic parameters identified using 18 Ffluorodeoxyglucose-positron emission tomography (FDG-PET) in terms of sensitivity, since no predictive factors exist. Patients and Methods: We included 136 patients with MBC treated with ET alone (n=107) or combined with CDK4/6 inhibitor (n=29) and examined using FDG-PET before treatment began. The highest maximum value of the standard uptake value (SUVmax), whole-body metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were calculated. Results: Progression-free survival (PFS) was significantly longer in patients with low levels of MTV, TLG, and SUVmax than those with higher levels (median PFS 49.5 vs. 20.7 months, p=0.001 for MTV, 49.5 vs. 20.7 months, p=0.0016 for TLG, 37.0 vs. 20.7 months, p=0.012 for SUVmax). Multivariable analysis revealed that TLG (hazard ratio=6.383, 95% confidence interval=1.167-34.913, p=0.033) was independently and significantly associated with PFS. The relationship between TLG levels and PFS was significant in patients treated with ET with (p=0.0054) and without (p=0.0188) CDK4/6 inhibitor. Conclusion: TLG at baseline was a significant predictor for sensitivity to ET alone or combined with CDK4/6 inhibitor. These data may be useful to identify patients that would benefit from ET.Cyclin-dependent kinase 4/6 (CDK4/6) inhibitor plus endocrine therapy (ET) is recommended as the first-line therapy for patients with estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC), except for those with visceral crisis (1, 2). From 2017 to 2018, 9.3% and 64.3% of patients with ER-positive/ HER2-negative MBC were treated with ET alone and the combination of ET with CDK4/6 inhibitor, respectively, as first-line therapy (3). However, predictive factors for ET with or without CDK4/6 inhibitor have yet to be identified. Clinically useful biomarkers that can be used in daily practice as alternatives to ER or HER2 status to select agents that would serve as effective treatments are urgently needed.Clinicopathological factors including tumor grade, ER, progesterone receptor (PgR), HER2, and Ki67 are considered as prognostic factors; however, only ER is a significant predictive factor for ET (4). In the phase III FALCON study, which compared first-line treatment with anastrozole and fulvestrant for patients with MBC, longer progression-free survival (PFS) was demonstrated in the fulvestrant arm. Interestingly, in the subgroup analysis, improved PFS was consistently recognized in the non-visceral diseases, but not visceral diseases [hazard ratio (HR)=0.59, 95% confidence interval (95%CI)=0.42-0.84, median PFS 13.8 vs. 22.3 months for non-visceral diseases; HR=0.99, 95%CI=0.74-4813

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Section: Discussionsupporting

confidence: 58%

Total Lesion Glycolysis Levels as Predictive Indicators in Patients With Metastatic and Recurrent Breast Cancer Undergoing Endocrine Therapy With or Without CDK4/6 Inhibitor

et al. 2022

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“…The "T" description provides only information about the primary tumor size, and the "N" description provides only information about whether lymph node metastasis is present, so it does not truly reflect the tumor burden on the whole body (26). The volume parameter MTV, obtained by FDG PET/CT, perfectly provided this information about tumor burden, which was recognized as important and found to be significantly associated with the prognosis of cancer patients (8)(9)(10)(11)(12)(13)(14). In the multivariate Cox analysis of model 1, MTVwb was shown to be an independent prognostic indicator in NSCLC patients with synchronous solitary bone metastasis, even after adjusting for other prognostic factors including cTN stage.…”

Section: Discussionmentioning

confidence: 99%

“…Whether NSCLC patients with synchronous solitary bone metastasis can be analyzed and evaluated by cTN stage (thoracic tumor staging) and volume parameters has not yet been investigated. Volume parameters have been found to be strongly associated with overall survival (OS) in patients with different types of malignant tumors, including NSCLC (8)(9)(10)(11)(12)(13)(14). Therefore, we speculated that cTN stage and MTV parameters were independent prognostic factors of NSCLC patients with synchronous solitary bone metastasis and that they could be used to stratify these patients and identify the differences in prognosis and the risk of death among such patients.…”

Section: Introductionmentioning

confidence: 99%

Prognostic value of thoracic tumor staging and volume parameters in non-small cell lung cancer patients with synchronous solitary bone metastasis

Deng¹,

Li²,

Zhang³

et al. 2022

J Thorac Dis

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Background: Non-small cell lung cancer (NSCLC) patients with synchronous solitary metastasis are a heterogeneous population. The analysis and evaluation of NSCLC patients with synchronous solitary bone metastases by cTN stage (thoracic tumor staging) and volume parameters have not yet been studied. The purpose of this study is to estimate the prognostic value of cTN stage and volume parameters obtained by fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in NSCLC patients with synchronous solitary bone metastasis. Methods: A total of 157 NSCLC patients with synchronous solitary bone metastasis were retrospectively analyzed. Patients' cTN stage, metabolic tumor volume (MTV) parameters, and clinical data were collected.Kaplan-Meier survival analysis and a Cox regression model were performed to determine the association between each factor and overall survival (OS). Finally, time-dependent receiver operating characteristic (TDROC) curve analysis was used to assess the predictive capacity of the independent prognostic factors.Results: Kaplan-Meier survival analysis showed significant differences between subgroups in terms of cTN stage. The median OS of group I was 44 months, and the 5-year survival rate was 39.6%. In the multivariate Cox regression analysis, cTN stage, MTV of the whole body (MTVwb), and MTV of thorax (MTVtho)were significantly associated with patient OS, even after adjusting for other clinical factors. However, MTV of bone (MTVbon) was not found to be an independent prognostic factor. TDROC curve analysis showed that cTN stage, MTVwb, and MTVtho had good predictive capacity for NSCLC patients with synchronous solitary bone metastasis. Compared with cTN stage and MTVtho, MTVwb had obviously better predictive specificity and sensitivity for the 5-year survival rate [5-year area under the curve (AUC) of MTVwb =0.844 vs. cTN stage (P=0.035) vs. MTVtho (P=0.052)]. The best cutoff value of MTVwb was 33.05. Conclusions:The results of this study confirmed that cTN stage, MTVwb, and MTVtho were independent prognostic factors of NSCLC patients with synchronous solitary bone metastases. These factors can be used for risk stratification of these patients. TDROC curve analysis indicated that cTN stage, MTVtho, and MTVwb had good performance for survival prediction.

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“…The regression task is used to match input data with continuous output data, that is, to predict survival. Unsupervised learning utilizes the internal structure of the data without specifying labels, and is often used for clusterization [13].…”

Section: Neural Network Architecture For Histological Image Analysismentioning

confidence: 99%

“…A neural network with a significant number of layers is called a deep learning network. Usually, the available cases are divided into training and test sets or training, validation and test sets [13].…”

Section: Neural Network Architecture For Histological Image Analysismentioning

confidence: 99%

Empowering Renal Cancer Management with AI and Digital Pathology: Pathology, Diagnostics and Prognosis

Ivanova,

Fayzullin,

Grinin

et al. 2023

Biomedicines

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Renal cell carcinoma is a significant health burden worldwide, necessitating accurate and efficient diagnostic methods to guide treatment decisions. Traditional pathology practices have limitations, including interobserver variability and time-consuming evaluations. In recent years, digital pathology tools emerged as a promising solution to enhance the diagnosis and management of renal cancer. This review aims to provide a comprehensive overview of the current state and potential of digital pathology in the context of renal cell carcinoma. Through advanced image analysis algorithms, artificial intelligence (AI) technologies facilitate quantification of cellular and molecular markers, leading to improved accuracy and reproducibility in renal cancer diagnosis. Digital pathology platforms empower remote collaboration between pathologists and help with the creation of comprehensive databases for further research and machine learning applications. The integration of digital pathology tools with other diagnostic modalities, such as radiology and genomics, enables a novel multimodal characterization of different types of renal cell carcinoma. With continuous advancements and refinement, AI technologies are expected to play an integral role in diagnostics and clinical decision-making, improving patient outcomes. In this article, we explored the digital pathology instruments available for clear cell, papillary and chromophobe renal cancers from pathologist and data analyst perspectives.

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Prognostic Value of Dual-Time-Point 18F-Fluorodeoxyglucose PET/CT in Metastatic Breast Cancer: An Exploratory Study of Quantitative Measures

Cited by 5 publications

References 19 publications

Total Lesion Glycolysis Levels as Predictive Indicators in Patients With Metastatic and Recurrent Breast Cancer Undergoing Endocrine Therapy With or Without CDK4/6 Inhibitor

Total Lesion Glycolysis Levels as Predictive Indicators in Patients With Metastatic and Recurrent Breast Cancer Undergoing Endocrine Therapy With or Without CDK4/6 Inhibitor

Prognostic value of thoracic tumor staging and volume parameters in non-small cell lung cancer patients with synchronous solitary bone metastasis

Empowering Renal Cancer Management with AI and Digital Pathology: Pathology, Diagnostics and Prognosis

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