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Purpose To compare target volume delineation of anal cancer using positron emission tomography (PET) and magnetic resonance imaging (MRI) with respect to inter-observer and inter-modality variability. Methods Nineteen patients with anal cancer undergoing chemoradiotherapy were prospectively included. Planning computed tomography (CT) images were co-registered with 18F–fluorodexocyglucose (FDG) PET/CT images and T2 and diffusion weighted (DW) MR images. Three oncologists delineated the Gross Tumor Volume (GTV) according to national guidelines and the visible tumor tissue (GTV T ). MRI and PET based delineations were evaluated by absolute volumes and Dice similarity coefficients. Results The median volume of the GTVs was 27 and 31 cm 3 for PET and MRI, respectively, while it was 6 and 11 cm 3 for GTV T . Both GTV and GTV T volumes were highly correlated between delineators ( r  = 0.90 and r  = 0.96, respectively). The median Dice similarity coefficient was 0.75 when comparing the GTVs based on PET/CT (GTV PET ) with the GTVs based on MRI and CT (GTV MRI ). The median Dice coefficient was 0.56 when comparing the visible tumor volume evaluated by PET (GTV T_PET ) with the same volume evaluated by MRI (GTV T_MRI ). Margins of 1–2 mm in the axial plane and 7–8 mm in superoinferior direction were required for coverage of the individual observer’s GTVs. Conclusions The rather good agreement between PET- and MRI-based GTVs indicates that either modality may be used for standard target delineation of anal cancer. However, larger deviations were found for GTV T , which may impact future tumor boost strategies.

Lead-212 (212Pb) is being investigated for alpha therapies, but it can be challenging to image. To investigate the quantitative accuracy of 212Pb SPECT images for patient geometries and low activity concentrations, we imaged an anthropomorphic phantom with 212Pb, and studied the deviations of SPECT derived activity concentrations.BACKGROUNDLead-212 (212Pb) is being investigated for alpha therapies, but it can be challenging to image. To investigate the quantitative accuracy of 212Pb SPECT images for patient geometries and low activity concentrations, we imaged an anthropomorphic phantom with 212Pb, and studied the deviations of SPECT derived activity concentrations.Fillable phantom compartment shells of the kidneys, liver and five vertebrae (T11-L3) were 3D-printed based on a patient's CT-images. The same patient's [18F]F-PSMA-1007 PET image was used as a basis for the relative distribution of 212Pb activity within the phantom compartments. The phantom was imaged with a Siemens Symbia Intevo Bold SPECT/CT, with a total of 3.4-3.8 MBq 212Pb for three acquisitions and 1.0-1.1 MBq 212Pb for three acquisitions, while recording energy windows centred at 79 keV and 239 keV. The SPECT images were reconstructed with Siemens' Flash-3D with a variety of iterations, subsets, and matrix sizes. Activity concentrations for each phantom compartment were measured from the images using a calibration factor measured in a uniform cross calibration phantom and compared to the activity concentrations in 1 ml samples extracted from each compartment, which were analysed using a gamma counter.METHODSFillable phantom compartment shells of the kidneys, liver and five vertebrae (T11-L3) were 3D-printed based on a patient's CT-images. The same patient's [18F]F-PSMA-1007 PET image was used as a basis for the relative distribution of 212Pb activity within the phantom compartments. The phantom was imaged with a Siemens Symbia Intevo Bold SPECT/CT, with a total of 3.4-3.8 MBq 212Pb for three acquisitions and 1.0-1.1 MBq 212Pb for three acquisitions, while recording energy windows centred at 79 keV and 239 keV. The SPECT images were reconstructed with Siemens' Flash-3D with a variety of iterations, subsets, and matrix sizes. Activity concentrations for each phantom compartment were measured from the images using a calibration factor measured in a uniform cross calibration phantom and compared to the activity concentrations in 1 ml samples extracted from each compartment, which were analysed using a gamma counter.Quantification was relatively stable across energy windows and matrix sizes, but best results were achieved using 30-120 reconstruction updates. Low activity concentration volumes representing background and vertebral bodies (0.03-0.05 kBq/ml) were not quantifiable with deviations over 400% for all investigated reconstructions. The activity concentrations in the liver and kidneys were underestimated by 10-50% compared to the gamma counter measurements. Precision between SPECT acquisitions was higher for the larger image matrix, with standard deviations of liver and kidney measurements less than 6% for the higher activity images, and less than 8% for the lower activity images.RESULTSQuantification was relatively stable across energy windows and matrix sizes, but best results were achieved using 30-120 reconstruction updates. Low activity concentration volumes representing background and vertebral bodies (0.03-0.05 kBq/ml) were not quantifiable with deviations over 400% for all investigated reconstructions. The activity concentrations in the liver and kidneys were underestimated by 10-50% compared to the gamma counter measurements. Precision between SPECT acquisitions was higher for the larger image matrix, with standard deviations of liver and kidney measurements less than 6% for the higher activity images, and less than 8% for the lower activity images.We found that larger volumes, such as liver and kidneys with at least 210 Bq/ml, may be quantifiable with an accuracy of approx. 30-40%. While very low activity concentrations below 54 Bq/ml were not quantifiable, this still indicate carefully used imaging results to be of value in dosimetric calculations, also when characterising latter parts of time activity curves.CONCLUSIONWe found that larger volumes, such as liver and kidneys with at least 210 Bq/ml, may be quantifiable with an accuracy of approx. 30-40%. While very low activity concentrations below 54 Bq/ml were not quantifiable, this still indicate carefully used imaging results to be of value in dosimetric calculations, also when characterising latter parts of time activity curves.

Lead-212 ( Pb) is being investigated for alpha therapies, but it can be challenging to image. To investigate the quantitative accuracy of Pb SPECT images for patient geometries and low activity concentrations, we imaged an anthropomorphic phantom with Pb, and studied the deviations of SPECT derived activity concentrations. Fillable phantom compartment shells of the kidneys, liver and five vertebrae (T11-L3) were 3D-printed based on a patient's CT-images. The same patient's [ F]F-PSMA-1007 PET image was used as a basis for the relative distribution of Pb activity within the phantom compartments. The phantom was imaged with a Siemens Symbia Intevo Bold SPECT/CT, with a total of 3.4-3.8 MBq Pb for three acquisitions and 1.0-1.1 MBq Pb for three acquisitions, while recording energy windows centred at 79 keV and 239 keV. The SPECT images were reconstructed with Siemens' Flash-3D with a variety of iterations, subsets, and matrix sizes. Activity concentrations for each phantom compartment were measured from the images using a calibration factor measured in a uniform cross calibration phantom and compared to the activity concentrations in 1 ml samples extracted from each compartment, which were analysed using a gamma counter. Quantification was relatively stable across energy windows and matrix sizes, but best results were achieved using 30-120 reconstruction updates. Low activity concentration volumes representing background and vertebral bodies (0.03-0.05 kBq/ml) were not quantifiable with deviations over 400% for all investigated reconstructions. The activity concentrations in the liver and kidneys were underestimated by 10-50% compared to the gamma counter measurements. Precision between SPECT acquisitions was higher for the larger image matrix, with standard deviations of liver and kidney measurements less than 6% for the higher activity images, and less than 8% for the lower activity images. We found that larger volumes, such as liver and kidneys with at least 210 Bq/ml, may be quantifiable with an accuracy of approx. 30-40%. While very low activity concentrations below 54 Bq/ml were not quantifiable, this still indicate carefully used imaging results to be of value in dosimetric calculations, also when characterising latter parts of time activity curves.

Purpose The introduction of immunotherapy in pleural mesothelioma (PM) has highlighted the need for effective outcome predictors. This study explores the role of [18F]FDG PET/CT in predicting outcomes in PM treated with immunotherapy. Methods Patients from the NIPU trial, receiving ipilimumab and nivolumab +/- telomerase vaccine in second-line, were included. [18F]FDG PET/CT was obtained at baseline (n = 100) and at week-5 (n = 76). Metabolic tumour volume (MTV) and peak standardised uptake value (SUV peak ) were evaluated in relation to survival outcomes. Wilcoxon rank-sum test was used to assess differences in MTV, total lesion glycolysis (TLG), maximum standardised uptake value (SUV max ) and SUV peak between patients exhibiting an objective response, defined as either partial response or complete response according to the modified Response Criteria in Solid Tumours (mRECIST) and immune RECIST (iRECIST), and non-responders, defined as either stable disease or progressive disease as their best overall response. Results Univariate Cox regression revealed significant associations of MTV with OS (HR 1.36, CI: 1.14, 1.62, p < 0.001) and PFS (HR 1.18, CI: 1.03, 1.34, p = 0.02), while multivariate analysis showed a significant association with OS only (HR 1.35, CI: 1.09, 1.68, p = 0.007). While SUV peak was not significantly associated with OS or PFS in univariate analyses, it was significantly associated with OS in multivariate analysis (HR 0.43, CI: 0.23, 0.80, p = 0.008). Objective responders had significant reductions in TLG, SUV max and SUV peak at week-5. Conclusion MTV provides prognostic value in PM treated with immunotherapy. High SUV peak was not associated with inferior outcomes, which could be attributed to the distinct mechanisms of immunotherapy. Early reductions in PET metrics correlated with treatment response. Study registration The NIPU trial (NCT04300244) is registered at clinicaltrials.gov. https://classic.clinicaltrials.gov/ct2/show/NCT04300244?cond=Pleural+Mesothelioma&cntry=NO&draw=2&rank=4

The introduction of immunotherapy in pleural mesothelioma (PM) has highlighted the need for effective outcome predictors. This study explores the role of [18F]FDG PET/CT in predicting outcomes in PM treated with immunotherapy.PURPOSEThe introduction of immunotherapy in pleural mesothelioma (PM) has highlighted the need for effective outcome predictors. This study explores the role of [18F]FDG PET/CT in predicting outcomes in PM treated with immunotherapy.Patients from the NIPU trial, receiving ipilimumab and nivolumab +/- telomerase vaccine in second-line, were included. [18F]FDG PET/CT was obtained at baseline (n = 100) and at week-5 (n = 76). Metabolic tumour volume (MTV) and peak standardised uptake value (SUVpeak) were evaluated in relation to survival outcomes. Wilcoxon rank-sum test was used to assess differences in MTV, total lesion glycolysis (TLG), maximum standardised uptake value (SUVmax) and SUVpeak between patients exhibiting an objective response, defined as either partial response or complete response according to the modified Response Criteria in Solid Tumours (mRECIST) and immune RECIST (iRECIST), and non-responders, defined as either stable disease or progressive disease as their best overall response.METHODSPatients from the NIPU trial, receiving ipilimumab and nivolumab +/- telomerase vaccine in second-line, were included. [18F]FDG PET/CT was obtained at baseline (n = 100) and at week-5 (n = 76). Metabolic tumour volume (MTV) and peak standardised uptake value (SUVpeak) were evaluated in relation to survival outcomes. Wilcoxon rank-sum test was used to assess differences in MTV, total lesion glycolysis (TLG), maximum standardised uptake value (SUVmax) and SUVpeak between patients exhibiting an objective response, defined as either partial response or complete response according to the modified Response Criteria in Solid Tumours (mRECIST) and immune RECIST (iRECIST), and non-responders, defined as either stable disease or progressive disease as their best overall response.Univariate Cox regression revealed significant associations of MTV with OS (HR 1.36, CI: 1.14, 1.62, p < 0.001) and PFS (HR 1.18, CI: 1.03, 1.34, p = 0.02), while multivariate analysis showed a significant association with OS only (HR 1.35, CI: 1.09, 1.68, p = 0.007). While SUVpeak was not significantly associated with OS or PFS in univariate analyses, it was significantly associated with OS in multivariate analysis (HR 0.43, CI: 0.23, 0.80, p = 0.008). Objective responders had significant reductions in TLG, SUVmax and SUVpeak at week-5.RESULTSUnivariate Cox regression revealed significant associations of MTV with OS (HR 1.36, CI: 1.14, 1.62, p < 0.001) and PFS (HR 1.18, CI: 1.03, 1.34, p = 0.02), while multivariate analysis showed a significant association with OS only (HR 1.35, CI: 1.09, 1.68, p = 0.007). While SUVpeak was not significantly associated with OS or PFS in univariate analyses, it was significantly associated with OS in multivariate analysis (HR 0.43, CI: 0.23, 0.80, p = 0.008). Objective responders had significant reductions in TLG, SUVmax and SUVpeak at week-5.MTV provides prognostic value in PM treated with immunotherapy. High SUVpeak was not associated with inferior outcomes, which could be attributed to the distinct mechanisms of immunotherapy. Early reductions in PET metrics correlated with treatment response.CONCLUSIONMTV provides prognostic value in PM treated with immunotherapy. High SUVpeak was not associated with inferior outcomes, which could be attributed to the distinct mechanisms of immunotherapy. Early reductions in PET metrics correlated with treatment response.The NIPU trial (NCT04300244) is registered at clinicaltrials.gov. https://classic.STUDY REGISTRATIONThe NIPU trial (NCT04300244) is registered at clinicaltrials.gov. https://classic.gov/ct2/show/NCT04300244?cond=Pleural+Mesothelioma&cntry=NO&draw=2&rank=4.CLINICALTRIALSgov/ct2/show/NCT04300244?cond=Pleural+Mesothelioma&cntry=NO&draw=2&rank=4.

Purpose Non-invasive response monitoring can potentially be used to guide therapy selection for breast cancer patients. We employed dynamic 2-deoxy-2-[ 18 F]fluoro-D-glucose positron emission tomography ([ 18 F]FDG PET) to evaluate changes in three breast cancer xenograft lines in mice following three chemotherapy regimens. Procedures Sixty-six athymic nude mice bearing bilateral breast cancer xenografts (two basal-like and one luminal-like subtype) underwent three 60 min [ 18 F]FDG PET scans. Scans were performed prior to and 3 and 10 days after treatment with doxorubicin, paclitaxel, or carboplatin. Tumor growth was monitored in parallel. A pharmacokinetic compartmental model was fitted to the tumor uptake curves, providing estimates of transfer rates between the vascular, non-metabolized, and metabolized compartments. Early and late standardized uptake values (SUV E and SUV L , respectively); the rate constants k 1 , k 2 , and k 3 , and the intravascular fraction v B were estimated. Changes in tumor volume were used as a response measure. Multivariate partial least-squares regression (PLSR) was used to assess if PET parameters could model tumor response and to identify PET parameters with the largest impact on response. Results Treatment responders had significantly larger perfusion-related parameters ( k 1 and k 2 ) and lower metabolism-related parameter ( k 3 ) than non-responders 10 days after the start of treatment. These findings were further supported by the PLSR analysis, which showed that k 1 and k 2 at day 10 and changes in k 3 explained most of the variability in response to therapy, whereas SUV L and particularly SUV E were of lesser importance. Conclusions Overall, rate parameters related to both tumor perfusion and metabolism were associated with tumor response. Conventional metrics of [ 18 F]FDG uptake such as SUV E and SUV L apparently had little relation to tumor response, thus necessitating full dynamic scanning and pharmacokinetic analysis for optimal evaluation of chemotherapy-induced changes in breast cancers.

Non-invasive response monitoring can potentially be used to guide therapy selection for breast cancer patients. We employed dynamic 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]FDG PET) to evaluate changes in three breast cancer xenograft lines in mice following three chemotherapy regimens.PURPOSENon-invasive response monitoring can potentially be used to guide therapy selection for breast cancer patients. We employed dynamic 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]FDG PET) to evaluate changes in three breast cancer xenograft lines in mice following three chemotherapy regimens.Sixty-six athymic nude mice bearing bilateral breast cancer xenografts (two basal-like and one luminal-like subtype) underwent three 60 min [18F]FDG PET scans. Scans were performed prior to and 3 and 10 days after treatment with doxorubicin, paclitaxel, or carboplatin. Tumor growth was monitored in parallel. A pharmacokinetic compartmental model was fitted to the tumor uptake curves, providing estimates of transfer rates between the vascular, non-metabolized, and metabolized compartments. Early and late standardized uptake values (SUVE and SUVL, respectively); the rate constants k 1, k 2, and k 3, and the intravascular fraction v B were estimated. Changes in tumor volume were used as a response measure. Multivariate partial least-squares regression (PLSR) was used to assess if PET parameters could model tumor response and to identify PET parameters with the largest impact on response.PROCEDURESSixty-six athymic nude mice bearing bilateral breast cancer xenografts (two basal-like and one luminal-like subtype) underwent three 60 min [18F]FDG PET scans. Scans were performed prior to and 3 and 10 days after treatment with doxorubicin, paclitaxel, or carboplatin. Tumor growth was monitored in parallel. A pharmacokinetic compartmental model was fitted to the tumor uptake curves, providing estimates of transfer rates between the vascular, non-metabolized, and metabolized compartments. Early and late standardized uptake values (SUVE and SUVL, respectively); the rate constants k 1, k 2, and k 3, and the intravascular fraction v B were estimated. Changes in tumor volume were used as a response measure. Multivariate partial least-squares regression (PLSR) was used to assess if PET parameters could model tumor response and to identify PET parameters with the largest impact on response.Treatment responders had significantly larger perfusion-related parameters (k 1 and k 2) and lower metabolism-related parameter (k 3) than non-responders 10 days after the start of treatment. These findings were further supported by the PLSR analysis, which showed that k 1 and k 2 at day 10 and changes in k 3 explained most of the variability in response to therapy, whereas SUVL and particularly SUVE were of lesser importance.RESULTSTreatment responders had significantly larger perfusion-related parameters (k 1 and k 2) and lower metabolism-related parameter (k 3) than non-responders 10 days after the start of treatment. These findings were further supported by the PLSR analysis, which showed that k 1 and k 2 at day 10 and changes in k 3 explained most of the variability in response to therapy, whereas SUVL and particularly SUVE were of lesser importance.Overall, rate parameters related to both tumor perfusion and metabolism were associated with tumor response. Conventional metrics of [18F]FDG uptake such as SUVE and SUVL apparently had little relation to tumor response, thus necessitating full dynamic scanning and pharmacokinetic analysis for optimal evaluation of chemotherapy-induced changes in breast cancers.CONCLUSIONSOverall, rate parameters related to both tumor perfusion and metabolism were associated with tumor response. Conventional metrics of [18F]FDG uptake such as SUVE and SUVL apparently had little relation to tumor response, thus necessitating full dynamic scanning and pharmacokinetic analysis for optimal evaluation of chemotherapy-induced changes in breast cancers.

The new standard of cause of death classification is an automated selection of the underlying cause of death using the international software Automated Classification of Medical Entities (ACME). Norwegian mortality rates are, however, based on manual classification of deaths. The aim of this study was to investigate how the use of ACME would influence Norwegian prostate cancer mortality rates. A previously described cohort of Norwegian prostate cancer patients deceased during 1996 was applied. Multiple causes of death data based on information from death certificates, autopsies and queries was coded according to ACME specifications, thereby ACME selected the underlying cause of death. In addition, the underlying cause of death that originally was manually classified for the official mortality statistics was retrieved from Statistics Norway in all cases. Age-standardized prostate cancer mortality rates (world population) per 100 000 person-years were calculated. A total of 2012 cases were included. On the basis of ACME classification, the age-standardized prostate cancer mortality rate in Norway for 1996 would have been 24.4 (95% confidence interval: 22.9-26.0) as compared with the rate based on manual classification for the official mortality statistics of 24.9 (95% confidence interval: 23.4-26.5). Thus, automated classification by ACME does not significantly influence the age-adjusted Norwegian prostate cancer mortality rate for the year 1996. There is reason to assume that the use of manual classification of deaths is not a major explanation of the high prostate cancer mortality rates in Norway.