Background Surgery is the main modality of cure for solid cancers and was prioritised to continue during COVID-19 outbreaks. This study aimed to identify immediate areas for system strengthening by comparing the delivery of elective cancer surgery during the COVID-19 pandemic in periods of lockdown versus light restriction. Methods This international, prospective, cohort study enrolled 20 006 adult (≥18 years) patients from 466 hospitals in 61 countries with 15 cancer types, who had a decision for curative surgery during the COVID-19 pandemic and were followed up until the point of surgery or cessation of follow-up (Aug 31, 2020). Average national Oxford COVID-19 Stringency Index scores were calculated to define the government response to COVID-19 for each patient for the period they awaited surgery, and classified into light restrictions (index <20), moderate lockdowns (20–60), and full lockdowns (>60). The primary outcome was the non-operation rate (defined as the proportion of patients who did not undergo planned surgery). Cox proportional-hazards regression models were used to explore the associations between lockdowns and non-operation. Intervals from diagnosis to surgery were compared across COVID-19 government response index groups. This study was registered at ClinicalTrials.gov , NCT04384926 . Findings Of eligible patients awaiting surgery, 2003 (10·0%) of 20 006 did not receive surgery after a median follow-up of 23 weeks (IQR 16–30), all of whom had a COVID-19-related reason given for non-operation. Light restrictions were associated with a 0·6% non-operation rate (26 of 4521), moderate lockdowns with a 5·5% rate (201 of 3646; adjusted hazard ratio [HR] 0·81, 95% CI 0·77–0·84; p<0·0001), and full lockdowns with a 15·0% rate (1775 of 11 827; HR 0·51, 0·50–0·53; p<0·0001). In sensitivity analyses, including adjustment for SARS-CoV-2 case notification rates, moderate lockdowns (HR 0·84, 95% CI 0·80–0·88; p<0·001), and full lockdowns (0·57, 0·54–0·60; p<0·001), remained independently associated with non-operation. Surgery beyond 12 weeks from diagnosis in patients without neoadjuvant therapy increased during lockdowns (374 [9·1%] of 4521 in light restrictions, 317 [10·4%] of 3646 in moderate lockdowns, 2001 [23·8%] of 11 827 in full lockdowns), although there were no differences in resectability rates observed with longer delays. Interpretation Cancer surgery systems worldwide were fragile to lockdowns, with one in seven patients who were in regions with full lockdowns not undergoing planned surgery and experiencing longer preoperative delays. Although short-term oncological outcomes were not compromised in those selected for surgery, delays and non-operations might lead to long-term reductions in survival. During current and future periods of societal restriction, the resilience of elective surgery systems requires strengthening, which might include...

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[11C](+)McN-5652 is an established positron emission tomography tracer used to assess serotonergic transporter density. Several methods have been used to analyze [11C](+)McN-5652 data; however, no evaluation of candidate methods has been published in detail yet. In this study, compartmental modeling using a one-tissue compartment model (K1, k2"), a two-tissue compartment model (K1 to k4), and a noncompartmental method that relies on a reference region devoid of specific binding sites were assessed. Because of its low density of serotonergic transporters, white matter was chosen as reference. Parameters related to transporter density were the total distribution volume DV" (= K1/k2", one tissue compartment), DVtot, (=K1/k1' (1 + k3/k4), two tissue compartments), and Rv (= k3'/k4, noncompartmental method). The DV", DVtot, and Rv values extended over a similar range and reflected the known pattern of serotonergic transporters. However, all parameters related to transporter density were markedly confounded by nonspecific binding. With regard to K1, the one-tissue compartment model yielded markedly lower values, which were, however, more stable. The minimal study duration needed to determine stable values for the distribution volume was approximately 60 minutes. The choice of the method to analyze [11C](+)McN-5652 data depends on the situation. Parametric maps of Rv are useful if no information on K1 is needed. If compartmental modeling is chosen, both the one- and the two-tissue compartment models have advantages. The one-tissue compartment model underestimates K1 but yields more robust values. The distribution volumes calculated with both models contain a similar amount of information. None of the parameters reflected serotonergic transporter density in a true quantitative manner, as all were confounded by nonspecific binding.

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The single photon emission computed tomography (SPECT) radiotracer [123I]iomazenil is used to assess benzodiazepine receptor binding parameters. These measurements are relative indices of benzodiazepine receptor concentration (B'max). To evaluate the ability of such indices in accurately accessing the B'max the authors compared them with absolute values of B'max, measured using positron emission tomography (PET). The authors performed SPECT, PET, and magnetic resonance imaging (MRI) studies on a group composed of seven subjects. For SPECT studies, the authors administered a single injection of [123I]iomazenil and estimated the total and specific distribution volumes (DV(T SPECT), DV(S SPECT)) and the binding potential (BP) using unconstrained (BP(SPECT)) and constrained (BP(C SPECT)) compartmental models. For PET studies, the authors used a multiinjection approach with [11C]flumazenil and unlabeled flumazenil to estimate absolute values of receptor concentration, B'max, and some other binding parameters. The authors studied the correlation of different binding parameters with B'max. To study the robustness of the binding parameter measurements at the pixel level, the authors applied a wavelet-based filter to improve signal-to-noise ratio of time-concentration curves, and the calculated kinetic parameters were used to build up parametric images. For PET data, the B'max and the DV(PET) were highly correlated (r = 0.988). This confirms that it is possible to use the DV(PET) to access benzodiazepine receptor density. For SPECT data, the correlation between DV(SPECT) estimated using a two- and three-compartment model was also high (r = 0.999). The DV(T SPECT) and BP(C SPECT) parameters estimated with a constrained three-compartment model or the DV(T''SPECT) parameter estimated with a two-compartment model were also highly correlated to the B'max parameter estimated with PET. Finally, the robustness of the binding parameters allowed the authors to build pixel-by-pixel parametric images using SPECT data.

IV, Retrospective study.

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