A review of modelling methodologies for flood source area (FSA) identification

Flooding is an important global hazard that causes an average annual loss of over 40 billion USD and affects a population of over 250 million globally. The complex process of flooding depends on spatial and temporal factors such as weather patterns, topography, and geomorphology. In urban environments where the landscape is ever-changing, spatial factors such as ground cover, green spaces, and drainage systems have a significant impact. Understanding source areas that have a major impact on flooding is, therefore, crucial for strategic flood risk management (FRM). Although flood source area (FSA) identification is not a new concept, its application is only recently being applied in flood modelling research. Continuous improvements in the technology and methodology related to flood models have enabled this research to move beyond traditional methods, such that, in recent years, modelling projects have looked beyond affected areas and recognised the need to address flooding at its source, to study its influence on overall flood risk. These modelling approaches are emerging in the field of FRM and propose innovative methodologies for flood risk mitigation and design implementation; however, they are relatively under-examined. In this paper, we present a review of the modelling approaches currently used to identify FSAs, i.e. unit flood response (UFR) and adaptation-driven approaches (ADA). We highlight their potential for use in adaptive decision making and outline the key challenges for the adoption of such approaches in FRM practises

[18F]Fluciclatide PET as a biomarker of response to combination therapy of pazopanib and paclitaxel in platinum-resistant/refractory ovarian cancer

BACKGROUND: Angiogenesis is a driver of platinum resistance in ovarian cancer. We assessed the effect of combination pazopanib and paclitaxel followed by maintenance pazopanib in patients with platinum-resistant/refractory ovarian cancer. Integrins αvβ3 and αvβ5 are both upregulated in tumor-associated vasculature. [18F]Fluciclatide is a novel PET tracer that has high affinity for integrins αvβ3/5, and was used to assess the anti-angiogenic effect of pazopanib. PATIENTS AND METHODS: We conducted an open-label, phase Ib study in patients with platinum-resistant/refractory ovarian cancer. Patients received 1 week of single-agent pazopanib (800 mg daily) followed by combination therapy with weekly paclitaxel (80 mg/m2). Following completion of 18 weeks of combination therapy, patients continued with single-agent pazopanib until disease progression. Dynamic [18F]fluciclatide-PET imaging was conducted at baseline and after 1 week of pazopanib. Response (RECIST 1.1), toxicities, and survival outcomes were recorded. Circulating markers of angiogenesis were assessed with therapy. RESULTS: Fourteen patients were included in the intention-to-treat analysis. Complete and partial responses were seen in seven patients (54%). Median progression-free survival (PFS) was 10.63 months, and overall survival (OS) was 18.5 months. Baseline [18F]fluciclatide uptake was predictive of long PFS. Elevated baseline circulating angiopoietin and fibroblast growth factor (FGF) were predictive of greater reduction in SUV60,mean following pazopanib. Kinetic modeling of PET data indicated a reduction in K1 and Ki following pazopanib indicating reduced radioligand delivery and retention. CONCLUSIONS: Combination therapy followed by maintenance pazopanib is effective and tolerable in platinum-resistant/refractory ovarian cancer. [18F]Fluciclatide-PET uptake parameters predict clinical outcome with pazopanib therapy indicating an anti-angiogenic response

Somatostatin Receptor PET/MR Imaging of Inflammation in Patients With Large Vessel Vasculitis and Atherosclerosis

Background: Assessing inflammatory disease activity in large vessel vasculitis (LVV) can be challenging by conventional measures. Objectives: We aimed to investigate somatostatin receptor 2 (SST2) as a novel inflammation-specific molecular imaging target in LVV. Methods: In a prospective, observational cohort study, in vivo arterial SST2 expression was assessed by positron emission tomography/magnetic resonance imaging (PET/MRI) using 68Ga-DOTATATE and 18F-FET-βAG-TOCA. Ex vivo mapping of the imaging target was performed using immunofluorescence microscopy; imaging mass cytometry; and bulk, single-cell, and single-nucleus RNA sequencing. Results: Sixty-one participants (LVV: n = 27; recent atherosclerotic myocardial infarction of ≤2 weeks: n = 25; control subjects with an oncologic indication for imaging: n = 9) were included. Index vessel SST2 maximum tissue-to-blood ratio was 61.8% (P < 0.0001) higher in active/grumbling LVV than inactive LVV and 34.6% (P = 0.0002) higher than myocardial infarction, with good diagnostic accuracy (area under the curve: ≥0.86; P < 0.001 for both). Arterial SST2 signal was not elevated in any of the control subjects. SST2 PET/MRI was generally consistent with 18F-fluorodeoxyglucose PET/computed tomography imaging in LVV patients with contemporaneous clinical scans but with very low background signal in the brain and heart, allowing for unimpeded assessment of nearby coronary, myocardial, and intracranial artery involvement. Clinically effective treatment for LVV was associated with a 0.49 ± 0.24 (standard error of the mean [SEM]) (P = 0.04; 22.3%) reduction in the SST2 maximum tissue-to-blood ratio after 9.3 ± 3.2 months. SST2 expression was localized to macrophages, pericytes, and perivascular adipocytes in vasculitis specimens, with specific receptor binding confirmed by autoradiography. SSTR2-expressing macrophages coexpressed proinflammatory markers. Conclusions: SST2 PET/MRI holds major promise for diagnosis and therapeutic monitoring in LVV. (PET Imaging of Giant Cell and Takayasu Arteritis [PITA], NCT04071691; Residual Inflammation and Plaque Progression Long-Term Evaluation [RIPPLE], NCT04073810

Somatostatin receptor PET/MR imaging of inflammation in patients with large vessel vasculitis and atherosclerosis.

BACKGROUND: Assessing inflammatory disease activity in large vessel vasculitis (LVV) can be challenging by conventional measures. OBJECTIVES: We aimed to investigate somatostatin receptor 2 (SST2) as a novel inflammation-specific molecular imaging target in LVV. METHODS: In a prospective, observational cohort study, in vivo arterial SST2 expression was assessed by positron emission tomography/magnetic resonance imaging (PET/MRI) using 68Ga-DOTATATE and 18F-FET-βAG-TOCA. Ex vivo mapping of the imaging target was performed using immunofluorescence microscopy; imaging mass cytometry; and bulk, single-cell, and single-nucleus RNA sequencing. RESULTS: Sixty-one participants (LVV: n = 27; recent atherosclerotic myocardial infarction of ≤2 weeks: n = 25; control subjects with an oncologic indication for imaging: n = 9) were included. Index vessel SST2 maximum tissue-to-blood ratio was 61.8% (P < 0.0001) higher in active/grumbling LVV than inactive LVV and 34.6% (P = 0.0002) higher than myocardial infarction, with good diagnostic accuracy (area under the curve: ≥0.86; P < 0.001 for both). Arterial SST2 signal was not elevated in any of the control subjects. SST2 PET/MRI was generally consistent with 18F-fluorodeoxyglucose PET/computed tomography imaging in LVV patients with contemporaneous clinical scans but with very low background signal in the brain and heart, allowing for unimpeded assessment of nearby coronary, myocardial, and intracranial artery involvement. Clinically effective treatment for LVV was associated with a 0.49 ± 0.24 (standard error of the mean [SEM]) (P = 0.04; 22.3%) reduction in the SST2 maximum tissue-to-blood ratio after 9.3 ± 3.2 months. SST2 expression was localized to macrophages, pericytes, and perivascular adipocytes in vasculitis specimens, with specific receptor binding confirmed by autoradiography. SSTR2-expressing macrophages coexpressed proinflammatory markers. CONCLUSIONS: SST2 PET/MRI holds major promise for diagnosis and therapeutic monitoring in LVV. (PET Imaging of Giant Cell and Takayasu Arteritis [PITA], NCT04071691; Residual Inflammation and Plaque Progression Long-Term Evaluation [RIPPLE], NCT04073810)