Organ-specific accuracy of [18F]FDG-PET/CT in identifying immune-related adverse events in patients with high-risk melanoma treated with adjuvant immune checkpoint inhibitor.

PURPOSE: This study aimed to determine the organ-specific accuracy of [18F]FDG-PET/CT in identifying immune-related adverse events (irAEs) in patients with high-risk (stage III/IV) surgically resected melanoma treated with an adjuvant immune checkpoint inhibitor (ICI) and determine the incidence of irAEs within the first year after starting treatment. MATERIALS AND METHODS: This registry-based study included individuals who had undergone surgical removal of melanoma and were undergoing adjuvant ICI treatment (either nivolumab or pembrolizumab). The study specifically enrolled patients who had undergone both a baseline and at least one subsequent follow-up [18F]FDG-PET/CT scan. Follow-up scans were performed every third month in the first year after surgery to screen for disease recurrence. We retrospectively compared the follow-up scans with baseline scans to identify irAEs. Clinical information on irAEs was obtained from medical records and served as a reference standard for determining the accuracy of [18F]FDG-PET/CT. RESULTS: A total of 123 patients with 363 [18F]FDG-PET/CT scans were included, and 65 patients (52.8%) developed irAEs. In decreasing order, the organ-specific incidences of irAEs were: skin 26/65 (40%), muscle and joints 21/65 (32.3%), intestines 13/65 (20%), thyroid gland 12/65 (18.5%), lungs 4/65 (6.2%), and heart 2/65 (3.1%). The sensitivities and specificities of [18F]FDG-PET/CT for diagnosing irAEs were: skin 19% (95% CI: 7-39%) and 95% (88-98%), muscles and joints 71% (48-89%) and 83% (75-90%), intestines 100% (75-100%) and 85% (77-91%); thyroid gland 92% (62-99%) and 95% (89-98%), lungs 75% (19-99%) and 90% (83-95%), and heart 50% (13-99%) and 97% (92-99%), respectively. CONCLUSION: [18F]FDG-PET/CT generally had moderate to high sensitivities (except for skin and heart) and specificities in diagnosing irAEs in patients receiving adjuvant ICI; this could be suggested to be systematically assessed and reported in scan reports.

Gastrin-releasing peptide receptor as a theranostic target in breast cancer: a systematic scoping review.

The gastrin-releasing peptide receptor (GRPR) is known to be overexpressed in breast cancer, making it a promising target for both imaging and therapy within a theranostic framework. Various radioligands targeting GRPR have undergone investigation in preclinical and clinical studies related to breast cancer. This systematic scoping review aimed to assess the current evidence on GRPR-targeted radioligands for diagnostic and therapeutic applications in breast cancer. The methodology followed the PRISMA-ScR protocol. The literature search was conducted in September 2023 and encompassed MEDLINE, Embase, Cochrane, and Scopus databases. We included original peer-reviewed studies focused on breast cancer patients or in vivo breast cancer models. Two reviewers performed the study selection process independently. Data were extracted, synthesized, and categorized into preclinical and clinical studies, further subdivided based on radioligand properties. A total of 35 original studies were included in the review, with three of them evaluating therapeutic outcomes. The results indicated that GRPR-radioantagonists are superior to GRPR-agonists, exhibiting preferable in vivo stability, rapid, specific tumor targeting, and enhanced retention. Both preclinical and clinical evaluations demonstrated renal excretion and high uptake in normal GRPR-expressing tissue, primarily the pancreas. A significant positive correlation was observed between GRPR and estrogen-receptor expression. In the clinical setting, GRPR-radioligands effectively detected primary tumors and, to a lesser extent, lymph node metastases. Moreover, GRPR-targeted radioantagonists successfully identified distant metastases originating from various sites in advanced metastatic disease, strongly correlated with positive estrogen receptor expression. Preclinical therapeutic evaluation of GRPR-radioligands labeled with lutetium-177 showed promising tumor responses, and none of the studies reported any observed or measured side effects, indicating a safe profile. In conclusion, the evidence presented in this review indicates a preference for GRPR-targeted antagonists over agonists, owing to their superior kinetics and promising diagnostic potential. Clinical assessments suggested diagnostic value for GRPR-targeted theranostics in breast cancer patients, particularly those with high estrogen receptor expression. Nevertheless, in the therapeutic clinical context, paying attention to the radiation dose administered to the pancreas and kidneys is crucial.

The Pattern of Metastatic Breast Cancer: A Prospective Head-to-Head Comparison of [18F]FDG-PET/CT and CE-CT.

The study aimed to compare the metastatic pattern of breast cancer and the intermodality proportion of agreement between [18F]FDG-PET/CT and CE-CT. Women with metastatic breast cancer (MBC) were enrolled prospectively and underwent a combined [18F]FDG-PET/CT and CE-CT scan to diagnose MBC. Experienced nuclear medicine and radiology physicians evaluated the scans blinded to the opposite scan results. Descriptive statistics were applied, and the intermodality proportion of agreement was used to compare [18F]FDG-PET/CT and CE-CT. In total, 76 women with verified MBC were enrolled in the study. The reported number of site-specific metastases for [18F]FDG-PET/CT vs. CE-CT was 53 (69.7%) vs. 44 (57.9%) for bone lesions, 31 (40.8%) vs. 43 (56.6%) for lung lesions, and 16 (21.1%) vs. 23 (30.3%) for liver lesions, respectively. The proportion of agreement between imaging modalities was 76.3% (95% CI 65.2-85.3) for bone lesions; 82.9% (95% CI 72.5-90.6) for liver lesions; 57.9% (95% CI 46.0-69.1) for lung lesions; and 59.2% (95% CI 47.3-70.4) for lymph nodes. In conclusion, bone and distant lymph node metastases were reported more often by [18F]FDG-PET/CT than CE-CT, while liver and lung metastases were reported more often by CE-CT than [18F]FDG-PET/CT. Agreement between scans was highest for bone and liver lesions and lowest for lymph node metastases.

Cost-effectiveness of 2-[18F]FDG-PET/CT versus CE-CT for response monitoring in patients with metastatic breast cancer: a register-based comparative study.

We evaluated the cost-effectiveness of 2-[18F]FDG-PET/CT compared to CE-CT for response monitoring in metastatic breast cancer (MBC) patients. The study included 300 biopsy-verified MBC patients treated at Odense University Hospital (Denmark). CE-CT was used in 144 patients, 83 patients underwent 2-[18F]FDG-PET/CT, and 73 patients received a combination of both. Hospital resource-based costs (2007-2019) were adjusted to the 2019 level. The incremental cost-effectiveness ratio (ICER) was calculated by comparing average costs per patient and gained survival with CE-CT. During a median follow-up of 33.0 months, patients in the 2-[18F]FDG-PET/CT group had more short admissions (median 6 vs. 2) and fewer overnight admissions (5 vs. 12) compared to the CE-CT group. The mean total cost per patient was €91,547 for CE-CT, €83,965 for 2-[18F]FDG-PET/CT, and €165,784 for the combined group. The ICER for 2-[18F]FDG-PET/CT compared to CE-CT was €-527/month, indicating gaining an extra month of survival at a lower cost (€527). 2-[18F]FDG-PET/CT was more cost-effective in patients with favorable prognostic factors (oligometastatic or estrogen receptor-positive disease), while CE-CT was more cost-effective in poor prognosis patients (liver/lung metastases or performance status ≥ 2 at baseline). In conclusion, our study suggests that 2-[18F]FDG-PET/CT is a cost-effective modality for response monitoring in metastatic breast cancer.

2-[18F]FDG-PET/CT is a better predictor of survival than conventional CT: a prospective study of response monitoring in metastatic breast cancer.

This study aimed to compare CE-CT and 2-[18F]FDG-PET/CT for response monitoring metastatic breast cancer (MBC). The primary objective was to predict progression-free and disease-specific survival for responders vs. non-responders on CE-CT and 2-[18F]FDG-PET/CT. The secondary objective was to assess agreement between response categorization for the two modalities. Treatment response in women with MBC was monitored prospectively by simultaneous CE-CT and 2-[18F]FDG-PET/CT, allowing participants to serve as their own controls. The standardized response evaluation criteria in solid tumors (RECIST 1.1) and PET response criteria in solid tumors (PERCIST) were used for response categorization. For prediction of progression-free and disease-specific survival, treatment response was dichotomized into responders (partial and complete response) and non-responders (stable and progressive disease) at the first follow-up scan. Progression-free survival was defined as the time from baseline until disease progression or death from any cause. Disease-specific survival was defined as the time from baseline until breast cancer-specific death. Agreement between response categorization for both modalities was analyzed for all response categories and responders vs. non-responders. At the first follow-up, tumor response was reported more often by 2-[18F]FDG-PET/CT than CE-CT, with only fair agreement on response categorization between the two modalities (weighted Kappa 0.28). Two-year progression-free survival for responders vs. non-responders by CE-CT was 54.2% vs. 46.0%, compared with 59.1% vs. 14.3% by 2-[18F]FDG-PET/CT. Correspondingly, 2-year disease-specific survival were 83.3% vs. 77.8% for CE-CT and 84.6% vs. 61.9% for 2-[18F]FDG-PET/CT. Tumor response on 2-[18F]FDG-PET/CT was significantly associated with progression-free (HR: 3.49, P < 0.001) and disease-specific survival (HR 2.35, P = 0.008), while no association was found for tumor response on CE-CT. In conclusion, 2-[18F]FDG-PET/CT appears a better predictor of progression-free and disease-specific survival than CE-CT when used to monitor metastatic breast cancer. In addition, we found low concordance between response categorization between the two modalities. TRIAL REGISTRATION: Clinical. TRIALS: gov. NCT03358589. Registered 30/11/2017-Retrospectively registered, http://www. CLINICALTRIALS: gov.

Comparison of Image Quality and Quantification Parameters between Q.Clear and OSEM Reconstruction Methods on FDG-PET/CT Images in Patients with Metastatic Breast Cancer.

We compared the image quality and quantification parameters through bayesian penalized likelihood reconstruction algorithm (Q.Clear) and ordered subset expectation maximization (OSEM) algorithm for 2-[18F]FDG-PET/CT scans performed for response monitoring in patients with metastatic breast cancer in prospective setting. We included 37 metastatic breast cancer patients diagnosed and monitored with 2-[18F]FDG-PET/CT at Odense University Hospital (Denmark). A total of 100 scans were analyzed blinded toward Q.Clear and OSEM reconstruction algorithms regarding image quality parameters (noise, sharpness, contrast, diagnostic confidence, artefacts, and blotchy appearance) using a five-point scale. The hottest lesion was selected in scans with measurable disease, considering the same volume of interest in both reconstruction methods. SULpeak (g/mL) and SUVmax (g/mL) were compared for the same hottest lesion. There was no significant difference regarding noise, diagnostic confidence, and artefacts within reconstruction methods; Q.Clear had significantly better sharpness (p < 0.001) and contrast (p = 0.001) than the OSEM reconstruction, while the OSEM reconstruction had significantly less blotchy appearance compared with Q.Clear reconstruction (p < 0.001). Quantitative analysis on 75/100 scans indicated that Q.Clear reconstruction had significantly higher SULpeak (5.33 ± 2.8 vs. 4.85 ± 2.5, p < 0.001) and SUVmax (8.27 ± 4.8 vs. 6.90 ± 3.8, p < 0.001) compared with OSEM reconstruction. In conclusion, Q.Clear reconstruction revealed better sharpness, better contrast, higher SUVmax, and higher SULpeak, while OSEM reconstruction had less blotchy appearance.

Value assessment of artificial intelligence in medical imaging: a scoping review.

BACKGROUND: Artificial intelligence (AI) is seen as one of the major disrupting forces in the future healthcare system. However, the assessment of the value of these new technologies is still unclear, and no agreed international health technology assessment-based guideline exists. This study provides an overview of the available literature in the value assessment of AI in the field of medical imaging. METHODS: We performed a systematic scoping review of published studies between January 2016 and September 2020 using 10 databases (Medline, Scopus, ProQuest, Google Scholar, and six related databases of grey literature). Information about the context (country, clinical area, and type of study) and mentioned domains with specific outcomes and items were extracted. An existing domain classification, from a European assessment framework, was used as a point of departure, and extracted data were grouped into domains and content analysis of data was performed covering predetermined themes. RESULTS: Seventy-nine studies were included out of 5890 identified articles. An additional seven studies were identified by searching reference lists, and the analysis was performed on 86 included studies. Eleven domains were identified: (1) health problem and current use of technology, (2) technology aspects, (3) safety assessment, (4) clinical effectiveness, (5) economics, (6) ethical analysis, (7) organisational aspects, (8) patients and social aspects, (9) legal aspects, (10) development of AI algorithm, performance metrics and validation, and (11) other aspects. The frequency of mentioning a domain varied from 20 to 78% within the included papers. Only 15/86 studies were actual assessments of AI technologies. The majority of data were statements from reviews or papers voicing future needs or challenges of AI research, i.e. not actual outcomes of evaluations. CONCLUSIONS: This review regarding value assessment of AI in medical imaging yielded 86 studies including 11 identified domains. The domain classification based on European assessment framework proved useful and current analysis added one new domain. Included studies had a broad range of essential domains about addressing AI technologies highlighting the importance of domains related to legal and ethical aspects.

Factors affecting hospital services overutilization and reductive strategies in Iran: a qualitative study to explore experts' views.

OBJECTIVES: This study aimed to investigate the viewpoints of the main stakeholders of the Iranian healthcare system about the overutilization of hospital services and strategies to eliminate or reduce it in Iran. METHODS: This is a qualitative study and thematic data analysis using face-to-face semi-structured interviews and Focus Group Discussions (FGDs). We conducted eight interviewers and two FGDs with hospital stakeholders including faculty members, insurance organizations' authorities, experienced hospital administrative staff, hospital managers, and health-care providers. RESULTS: The factors leading to the overutilization of hospital services were categorized into four main themes including site of service, quality, supplier push, and demand pull. Strategies for eliminating or reducing the overutilization of hospital services are also identified based on the influential factors. CONCLUSION: Addressing overutilization of hospital services in the health system and adherence to policies for reducing or eliminating overutilization is a way to make preventive strategies to overcome overutilization. Developing a national plan to integrate utilization management into health system programs is a strategy to combat overutilization in various levels of the health system including hospital setting.

Model for ASsessing the value of Artificial Intelligence in medical imaging (MAS-AI).

OBJECTIVES: Artificial intelligence (AI) is seen as a major disrupting force in the future healthcare system. However, the assessment of the value of AI technologies is still unclear. Therefore, a multidisciplinary group of experts and patients developed a Model for ASsessing the value of AI (MAS-AI) in medical imaging. Medical imaging is chosen due to the maturity of AI in this area, ensuring a robust evidence-based model. METHODS: MAS-AI was developed in three phases. First, a literature review of existing guides, evaluations, and assessments of the value of AI in the field of medical imaging. Next, we interviewed leading researchers in AI in Denmark. The third phase consisted of two workshops where decision makers, patient organizations, and researchers discussed crucial topics for evaluating AI. The multidisciplinary team revised the model between workshops according to comments. RESULTS: The MAS-AI guideline consists of two steps covering nine domains and five process factors supporting the assessment. Step 1 contains a description of patients, how the AI model was developed, and initial ethical and legal considerations. In step 2, a multidisciplinary assessment of outcomes of the AI application is done for the five remaining domains: safety, clinical aspects, economics, organizational aspects, and patient aspects. CONCLUSIONS: We have developed an health technology assessment-based framework to support the introduction of AI technologies into healthcare in medical imaging. It is essential to ensure informed and valid decisions regarding the adoption of AI with a structured process and tool. MAS-AI can help support decision making and provide greater transparency for all parties.

A role of FDG-PET/CT for response evaluation in metastatic breast cancer?

Breast cancer prognosis is steadily improving due to early detection of primary cancer in screening programs and revolutionizing treatment development. In the metastatic setting, therapy improvements render breast cancer a chronic disease. Although FDG-PET/CT has emerged as a highly accurate method for staging metastatic breast cancer, there has been no change in response evaluation methods for decades. FDG-PET/CT has proven high prognostic values in patients with metastatic breast cancer when using quantitative PET methods. It has also shown a higher predictive value than conventional CT when applying the respective response evaluation criteria, RECIST and PERCIST. Response categorization using FDG-PET/CT is more sensitive in detecting progressive and regressive disease, while conventional imaging such as CT and bone scintigraphy deem stable disease more often. These findings reflect the higher accuracy of FDG-PET/CT for response evaluation in this patient group. But does the higher accuracy of FDG-PET/CT translate into a patient benefit when implementing it for monitoring response to palliative treatment? We have evidence of survival benefit from a retrospective study indicating the superiority of using FDG-PET/CT compared with conventional imaging for response evaluation in metastatic breast cancer patients. The survival benefit seems to result from earlier detection of progression with FDG-PET/CT than conventional imaging, leading to an earlier change in treatment with potentially better efficacy of the subsequent treatment line. FDG-PET/CT can be used semiquantitatively as suggested in PERCIST. However, we still need to improve clinically applicable methods based on neural network modeling to better integrate the quantitative information in a smart and standardized way, enabling relevant comparability between scans, patients, and institutions. Such innovation is warranted to support imaging specialists in diagnostic response assessment. Prospective multicenter studies analyzing patients' survival, quality of life, societal and patient costs of replacing conventional imaging with FDG-PET/CT are needed before firm conclusions can be drawn on which type of scan to recommend in future clinical guidelines.

Response monitoring in metastatic breast cancer: a comparison of survival times between FDG-PET/CT and CE-CT.

BACKGROUND: We compared overall survival for metastatic breast cancer (MBC) patients monitored with CE-CT, FDG-PET/CT or a combination of them in an observational setting. METHODS: Patients with biopsy-verified (recurrent or de novo) MBC (n = 300) who were treated at Odense university hospital (Denmark) and response monitored with FDG-PET/CT (n = 83), CE-CT (n = 144), or a combination of these (n = 73) were followed until 2019. Survival was compared between the scan groups, and were adjusted for clinico-histopathological variables representing potential confounders in a Cox proportional-hazard regression model. RESULTS: The study groups were mostly comparable regarding baseline characteristics, but liver metastases were reported more frequently in CE-CT group (38.9%) than in FDG-PET/CT group (19.3%) and combined group (24.7%). Median survival was 30.0 months for CE-CT group, 44.3 months for FDG-PET/CT group and 54.0 months for Combined group. Five-year survival rates were significantly higher for FDG-PET/CT group (41.9%) and combined group (43.3%), than for CE-CT group (15.8%). Using the CE-CT group as reference, the hazard ratio was 0.44 (95% CI: 0.29-0.68, P = 0.001) for the FDG-PET/CT group after adjusting for baseline characteristics. FDG-PET/CT detected the first progression 4.7 months earlier than CE-CT, leading to earlier treatment change. CONCLUSIONS: In this single-center, observational study, patients with metastatic breast cancer who were response monitored with FDG-PET/CT alone or in combination with CE-CT had longer overall survival than patients monitored with CE-CT alone. Confirmation of these findings by further, preferably randomised clinical trials is warranted.

How to increase value and reduce waste in research: initial experiences of applying Lean thinking and visual management in research leadership.

Waste in research has been well documented, but initiatives to reduce it are scarce. Here, we share our initial experiences of implementing Lean thinking and visual management into hospital research units in the Region of Southern Denmark. A Transformation Guiding Team (TGT) anchored in the top management was established with participation from leaders, researchers and patient representatives. The role of the TGT was to implement Lean methods, considering patients as primary end-users of the research results. This is in line with an explicit decision on setting patient values first in clinical settings at participating hospitals. The leaders of the research units were instructed in Lean thinking and Lean methods during a five-module course focusing on increasing value and reducing waste in research production. Initial experiences were that Lean tools could create a patient-centred vision that through visual management could identify waste in work processes. Concerns were lack of evidence for using Lean methods in research leadership and that the model itself could be a time consumer. Some lessons learnt were that adding Lean tools in research leadership should not just provide increased research productivity, but also improve other important key performance indicators such as quality of research and patient-relevant results. We intend to evaluate the value of the initiative by follow-up research and publish the outcome of key behavioural and key performance indicators.

Age at Diagnosis of Breast Cancer in Iran: A Systematic Review and Meta-Analysis.

BACKGROUND: Breast cancer is responsible for up to 25% of all cancers in Iran. The age at diagnosis of Iranian breast cancer patients starts a decade earlier than most of developed countries. This study aimed to evaluate the mean age at diagnosis of Iranian breast cancer patients. METHODS: In this systematic review and meta-analysis, the mean age at diagnosis of Iranian breast cancer patients and its pattern between 2008 and 2017, were evaluated. All papers with age at diagnosis of histopathological verified breast cancer patients were considered eligible to enter to the analysis. We used databases including Medline/PubMed, Scopus, Embase, Cochrane Library, Iranmedex and SID for the search process. The meta-analysis was performed only on studies with separate data for female patients, using random-effects model, Mantel and Haenszel method and the Comprehensive Meta-analysis software. RESULTS: Finally, 92 studies with 19,784 patients (both-genders) were included. The mean age at diagnosis had increased from 47.93 (2008) to 49.91 (2016) years. The meta-analysis was done on 78 studies containing of 15,071 female patients and the mean age at diagnosis was 46.76±1.19. There was a wide range of age at diagnosis within different provinces. The mean age at Hamadan and Khuzestan provinces were the lowest and highest, respectively (42.48±7.96 vs. 51.00±11.47). The heterogeneity of studies was statistically significant (I2=99.744). CONCLUSION: Mean age at diagnosis of Iranian women with breast cancer was 46.76±1.19. There was an increasing pattern in mean age of diagnosis at breast cancer patients within the past 10 years.

Machine learning techniques for mortality prediction in emergency departments: a systematic review.

OBJECTIVES: This systematic review aimed to assess the performance and clinical feasibility of machine learning (ML) algorithms in prediction of in-hospital mortality for medical patients using vital signs at emergency departments (EDs). DESIGN: A systematic review was performed. SETTING: The databases including Medline (PubMed), Scopus and Embase (Ovid) were searched between 2010 and 2021, to extract published articles in English, describing ML-based models utilising vital sign variables to predict in-hospital mortality for patients admitted at EDs. Critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist was used for study planning and data extraction. The risk of bias for included papers was assessed using the prediction risk of bias assessment tool. PARTICIPANTS: Admitted patients to the ED. MAIN OUTCOME MEASURE: In-hospital mortality. RESULTS: Fifteen articles were included in the final review. We found that eight models including logistic regression, decision tree, K-nearest neighbours, support vector machine, gradient boosting, random forest, artificial neural networks and deep neural networks have been applied in this domain. Most studies failed to report essential main analysis steps such as data preprocessing and handling missing values. Fourteen included studies had a high risk of bias in the statistical analysis part, which could lead to poor performance in practice. Although the main aim of all studies was developing a predictive model for mortality, nine articles did not provide a time horizon for the prediction. CONCLUSION: This review provided an updated overview of the state-of-the-art and revealed research gaps; based on these, we provide eight recommendations for future studies to make the use of ML more feasible in practice. By following these recommendations, we expect to see more robust ML models applied in the future to help clinicians identify patient deterioration earlier.

Diagnosis of bone metastases in breast cancer: Lesion-based sensitivity of dual-time-point FDG-PET/CT compared to low-dose CT and bone scintigraphy.

We compared lesion-based sensitivity of dual-time-point FDG-PET/CT, bone scintigraphy (BS), and low-dose CT (LDCT) for detection of various types of bone metastases in patients with metastatic breast cancer. Prospectively, we included 18 patients with recurrent breast cancer who underwent dual-time-point FDG-PET/CT with LDCT and BS within a median time interval of three days. A total of 488 bone lesions were detected on any of the modalities and were categorized by the LDCT into osteolytic, osteosclerotic, mixed morphologic, and CT-negative lesions. Lesion-based sensitivity was 98.2% (95.4-99.3) and 98.8% (96.8-99.5) for early and delayed FDG-PET/CT, respectively, compared with 79.9% (51.1-93.8) for LDCT, 76.0% (36.3-94.6) for BS, and 98.6% (95.4-99.6) for the combined BS+LDCT. BS detected only 51.2% of osteolytic lesions which was significantly lower than other metastatic types. SUVs were significantly higher for all lesion types on delayed scans than on early scans (P<0.0001). Osteolytic and mixed-type lesions had higher SUVs than osteosclerotic and CT-negative metastases at both time-points. FDG-PET/CT had significantly higher lesion-based sensitivity than LDCT and BS, while a combination of the two yielded sensitivity comparable to that of FDG-PET/CT. Therefore, FDG-PET/CT could be considered as a sensitive one-stop-shop in case of clinical suspicion of bone metastases in breast cancer patients.

Clinical Impact of FDG-PET/CT Compared with CE-CT in Response Monitoring of Metastatic Breast Cancer.

We compared response categories and impacts on treatment decisions for metastatic breast cancer (MBC) patients that are response-monitored with contrast-enhanced computed-tomography (CE-CT) or fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT). A comparative diagnostic study was performed on MBC patients undergoing response monitoring by CE-CT (n = 34) or FDG-PET/CT (n = 31) at the Odense University Hospital (Denmark). The responses were assessed visually and allocated into categories of complete response (CR/CMR), partial response (PR/PMR), stable disease (SD/SMD), and progressive disease (PD/PMD). Response categories, clinical impact, and positive predictive values (PPV) were compared for follow-up scans. A total of 286 CE-CT and 189 FDG-PET/CT response monitoring scans were performed. Response categories were distributed into CR (3.8%), PR (8.4%), SD (70.6%), PD (15%), and others (2.1%) by CE-CT and into CMR (22.2%), PMR (23.8%), SMD (31.2%), PMD (18.5%), and others (4.4%) by FDG-PET/CT, revealing a significant difference between the groups (P < 0.001). PD and PMD caused changes of treatment in 79.1% and 60%, respectively (P = 0.083). PPV for CE-CT and FDG-PET/CT was 0.85 (95% CI: 0.72-0.97) and 0.70 (95% CI: 0.53-0.87), respectively (P = 0.17). FDG-PET/CT indicated regression of disease more frequently than CE-CT, while CE-CT indicated stable disease more often. FDG-PET/CT seems to be more sensitive than CE-CT for monitoring response in metastatic breast cancer.

FDG-PET/CT for Response Monitoring in Metastatic Breast Cancer: The Feasibility and Benefits of Applying PERCIST.

BACKGROUND: We aimed to examine the feasibility and potential benefit of applying PET Response Criteria in Solid Tumors (PERCIST) for response monitoring in metastatic breast cancer (MBC). Further, we introduced the nadir scan as a reference. METHODS: Response monitoring FDG-PET/CT scans in 37 women with MBC were retrospectively screened for PERCIST standardization and measurability criteria. One-lesion PERCIST based on changes in SULpeak measurements of the hottest metastatic lesion was used for response categorization. The baseline (PERCISTbaseline) and the nadir scan (PERCISTnadir) were used as references for PERCIST analyses. RESULTS: Metastatic lesions were measurable according to PERCIST in 35 of 37 (94.7%) patients. PERCIST was applied in 150 follow-up scans, with progression more frequently reported by PERCISTnadir (36%) than PERCISTbaseline (29.3%; p = 0.020). Reasons for progression were (a) more than 30% increase in SULpeak of the hottest lesion (n = 7, 15.9%), (b) detection of new metastatic lesions (n = 28, 63.6%), or both (a) and (b) (n = 9, 20.5%). CONCLUSIONS: PERCIST, with the introduction of PERCISTnadir, allows a graphical interpretation of disease fluctuation that may be beneficial in clinical decision-making regarding potential earlier termination of non-effective toxic treatment. PERCIST seems feasible for response monitoring in MBC but prospective studies are needed to come this closer.

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

This study aimed to compare the prognostic value of quantitative measures of [18F]-fluorodeoxyglucose positron emission tomography with integrated computed tomography (FDG-PET/CT) for the response monitoring of patients with metastatic breast cancer (MBC). In this prospective study, 22 patients with biopsy-verified MBC diagnosed between 2011 and 2014 at Odense University Hospital (Denmark) were followed up until 2019. A dual-time-point FDG-PET/CT scan protocol (1 and 3 h) was applied at baseline, when MBC was diagnosed. Baseline characteristics and quantitative measures of maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), corrected SUVmean (cSUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and corrected TLG (cTLG) were collected. Survival time was analyzed using the Kaplan-Meier method and was regressed on MTV, TLG, and cTLG while adjusting for clinicopathological characteristics. Among the 22 patients included (median age: 59.5 years), 21 patients (95%) died within the follow-up period. Median survival time was 29.13 months (95% Confidence interval: 20.4-40 months). Multivariable Cox proportional hazards regression analyses of survival time showed no influence from the SUVmean, cSUVmean, or SUVmax, while increased values of MTV, TLG, and cTLG were significantly associated with slightly higher risk, with hazard ratios ranging between 1.0003 and 1.004 (p = 0.007 to p = 0.026). Changes from 1 to 3 h were insignificant for all PET measures in the regression model. In conclusion, MTV and TLG are potential prognostic markers for overall survival in MBC patients.