| 1. |
- Anand, Aseem, et al.
(författare)
-
Assessing Radiographic Response to 223Ra with an Automated Bone Scan Index in Metastatic Castration-Resistant Prostate Cancer Patients
- 2020
-
Ingår i: Journal of Nuclear Medicine. - : Society of Nuclear Medicine. - 0161-5505 .- 2159-662X .- 1535-5667. ; 61:5, s. 671-675
-
Tidskriftsartikel (refereegranskat)abstract
- For effective clinical management of patients being treated with 223Ra, there is a need for radiographic response biomarkers to minimize disease progression and to stratify patients for subsequent treatment options. The objective of this study was to evaluate an automated bone scan index (aBSI) as a quantitative assessment of bone scans for radiographic response in patients with metastatic castration-resistant prostate cancer (mCRPC). Methods: In a multicenter retrospective study, bone scans from patients with mCRPC treated with monthly injections of 223Ra were collected from 7 hospitals in Sweden. Patients with available bone scans before treatment with 223Ra and at treatment discontinuation were eligible for the study. The aBSI was generated at baseline and at treatment discontinuation. The Spearman rank correlation was used to correlate aBSI with the baseline covariates: alkaline phosphatase (ALP) and prostate-specific antigen (PSA). The Cox proportional-hazards model and Kaplan-Meier curve were used to evaluate the association of covariates at baseline and their change at treatment discontinuation with overall survival (OS). The concordance index (C-index) was used to evaluate the discriminating strength of covariates in predicting OS. Results: Bone scan images at baseline were available from 156 patients, and 67 patients had both a baseline and a treatment discontinuation bone scan (median, 5 doses; interquartile range, 3-6 doses). Baseline aBSI (median, 4.5; interquartile range, 2.4-6.5) was moderately correlated with ALP (r = 0.60, P < 0.0001) and with PSA (r = 0.38, P = 0.003). Among baseline covariates, aBSI (P = 0.01) and ALP (P = 0.001) were significantly associated with OS, whereas PSA values were not (P = 0.059). After treatment discontinuation, 36% (24/67), 80% (54/67), and 13% (9/67) of patients demonstrated a decline in aBSI, ALP, and PSA, respectively. As a continuous variable, the relative change in aBSI after treatment, compared with baseline, was significantly associated with OS (P < 0.0001), with a C-index of 0.67. Median OS in patients with both aBSI and ALP decline (median, 134 wk) was significantly longer than in patients with ALP decline only (median, 77 wk; P = 0.029). Conclusion: Both aBSI at baseline and its change at treatment discontinuation were significant parameters associated with OS. The study warrants prospective validation of aBSI as a quantitative imaging response biomarker to predict OS in patients with mCRPC treated with 223Ra.
|
|
| 2. |
|
|
| 3. |
- Jakobson Mo, Susanna, 1968-, et al.
(författare)
-
I-123-FP-Cit and I-123-IBZM SPECT uptake in a prospective normal material analysed with two different semiquantitative image evaluation tools
- 2013
-
Ingår i: Nuclear Medicine Communications. - : Lippincott Williams & Wilkins. - 0143-3636 .- 1473-5628. ; 34:10, s. 978-989
-
Tidskriftsartikel (refereegranskat)abstract
- Objective The need for age-adjusted and/or sex-adjusted reference values in dopamine transporter (DAT) and dopamine D2 receptor (D2R) imaging with single-photon emission computed tomography (SPECT) in a longitudinal study of parkinsonian diseases was investigated. We used two different image evaluation tools with a cross-sectional and longitudinal statistical approach.Materials and methods Baseline DAT and/or D2R SPECT were performed in 51 healthy controls (HC), age-matched to patients in an ongoing prospective study on idiopathic parkinsonism. Twenty-four HC were re-examined after 3 years and 21 HC were examined again after 5 years. SPECT was performed with I-123-FP-Cit and I-123-IBZM on a two-headed hybrid gamma camera. Regions of interest and volumes of interest (VOIs) were used for image evaluation. A cross-sectional and longitudinal statistical analysis was carried out.Results Fewer sex-based differences and less age dependency were seen in DAT SPECT uptake ratios compared with D2R SPECT uptake ratios and when comparing uptake ratios obtained with regions of interest against those with VOIs. In the cross-sectional analysis, a significant age-dependent decline was seen in women in both DAT and D2R uptakes with the VOI method but not in men with either evaluation method. In the longitudinal dataset, both a slight decline and increase over time were seen in DAT uptake; however, a general pattern of decrease was seen in both men and women in D2R uptake.Conclusion The choice of the image evaluation method can influence the pattern of sex-based and age-related differences. The results speak for the use of age-stratified reference values for women, in particular when using a VOI method.
|
|
| 4. |
- Mortensen, Mike A., et al.
(författare)
-
Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study
- 2019
-
Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 39:6, s. 399-406
-
Tidskriftsartikel (refereegranskat)abstract
- Aim : To test the feasibility of a fully automated artificial intelligence-based method providing PET measures of prostate cancer (PCa). Methods : A convolutional neural network (CNN) was trained for automated measurements in 18F-choline (FCH) PET/CT scans obtained prior to radical prostatectomy (RP) in 45 patients with newly diagnosed PCa. Automated values were obtained for prostate volume, maximal standardized uptake value (SUVmax), mean standardized uptake value of voxels considered abnormal (SUVmean) and volume of abnormal voxels (Volabn). The product SUVmean × Volabn was calculated to reflect total lesion uptake (TLU). Corresponding manual measurements were performed. CNN-estimated data were compared with the weighted surgically removed tissue specimens and manually derived data and related to clinical parameters assuming that 1 g ≈ 1 ml of tissue. Results : The mean (range) weight of the prostate specimens was 44 g (20–109), while CNN-estimated volume was 62 ml (31–108) with a mean difference of 13·5 g or ml (95% CI: 9·78–17·32). The two measures were significantly correlated (r = 0·77, P<0·001). Mean differences (95% CI) between CNN-based and manually derived PET measures of SUVmax, SUVmean, Volabn (ml) and TLU were 0·37 (−0·01 to 0·75), −0·08 (−0·30 to 0·14), 1·40 (−2·26 to 5·06) and 9·61 (−3·95 to 23·17), respectively. PET findings Volabn and TLU correlated with PSA (P<0·05), but not with Gleason score or stage. Conclusion : Automated CNN segmentation provided in seconds volume and simple PET measures similar to manually derived ones. Further studies on automated CNN segmentation with newer tracers such as radiolabelled prostate-specific membrane antigen are warranted.
|
|
| 5. |
- Reza Felix, Mariana, et al.
(författare)
-
Bone Scan Index as an Imaging Biomarker in Metastatic Castration-resistant Prostate Cancer : A Multicentre Study Based on Patients Treated with Abiraterone Acetate (Zytiga) in Clinical Practice
- 2016
-
Ingår i: European Urology Focus. - : Elsevier BV. - 2405-4569. ; 2:5, s. 540-546
-
Tidskriftsartikel (refereegranskat)abstract
- Background Abiraterone acetate (AA) prolongs survival in metastatic castration-resistant prostate cancer (mCRPC) patients. To measure treatment response accurately in bone, quantitative methods are needed. The Bone Scan Index (BSI), a prognostic imaging biomarker, reflects the tumour burden in bone as a percentage of the total skeletal mass calculated from bone scintigraphy. Objective To evaluate the value of BSI as a biomarker for outcome evaluation in mCRPC patients on treatment with AA according to clinical routine. Design, setting, and participants We retrospectively studied 104 mCRPC patients who received AA following disease progression after chemotherapy. All patients underwent whole-body bone scintigraphy before and during AA treatment. Baseline and follow-up BSI data were obtained using EXINI BoneBSI software (EXINI Diagnostics AB, Lund, Sweden). Outcome measurements and statistical analysis Associations between change in BSI, clinical parameters at follow-up, and overall survival (OS) were evaluated using the Cox proportional hazards regression models and Kaplan-Meier estimates. Discrimination between variables was assessed using the concordance index (C-index). Results and limitations Patients with an increase in BSI at follow-up of at most 0.30 (n = 54) had a significantly longer median survival time than those with an increase of BSI >0.30 (n = 50) (median: 16 vs 10 mo; p = 0.001). BSI change was also associated with OS in a multivariate Cox analysis including commonly used clinical parameters for prognosis (C-index = 0.7; hazard ratio: 1.1; p = 0.03). The retrospective design was a limitation. Conclusions Change in BSI was significantly associated with OS in mCRPC patients undergoing AA treatment following disease progression in a postchemotherapy setting. BSI may be a useful imaging biomarker for outcome evaluation in this group of patients, and it could be a valuable complementary tool in monitoring patients with mCRPC on second-line therapies. Patient summary Bone Scan Index (BSI) change is related to survival time in metastatic castration-resistant prostate cancer (mCRPC) patients on abiraterone acetate. BSI may be a valuable complementary decision-making tool supporting physicians monitoring patients with mCRPC on second-line therapies.
|
|
| 6. |
- Abuhasanein, Suleiman, et al.
(författare)
-
A novel model of artificial intelligence based automated image analysis of CT urography to identify bladder cancer in patients investigated for macroscopic hematuria
- 2024
-
Ingår i: Scandinavian Journal of Urology. - : Medical Journal Sweden AB. - 2168-1805 .- 2168-1813. ; 59, s. 90-97
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To evaluate whether artificial intelligence (AI) based automatic image analysis utilising convolutional neural networks (CNNs) can be used to evaluate computed tomography urography (CTU) for the presence of urinary bladder cancer (UBC) in patients with macroscopic hematuria. METHODS: Our study included patients who had undergone evaluation for macroscopic hematuria. A CNN-based AI model was trained and validated on the CTUs included in the study on a dedicated research platform (Recomia.org). Sensitivity and specificity were calculated to assess the performance of the AI model. Cystoscopy findings were used as the reference method. RESULTS: The training cohort comprised a total of 530 patients. Following the optimisation process, we developed the last version of our AI model. Subsequently, we utilised the model in the validation cohort which included an additional 400 patients (including 239 patients with UBC). The AI model had a sensitivity of 0.83 (95% confidence intervals [CI], 0.76-0.89), specificity of 0.76 (95% CI 0.67-0.84), and a negative predictive value (NPV) of 0.97 (95% CI 0.95-0.98). The majority of tumours in the false negative group (n = 24) were solitary (67%) and smaller than 1 cm (50%), with the majority of patients having cTaG1-2 (71%). CONCLUSIONS: We developed and tested an AI model for automatic image analysis of CTUs to detect UBC in patients with macroscopic hematuria. This model showed promising results with a high detection rate and excessive NPV. Further developments could lead to a decreased need for invasive investigations and prioritising patients with serious tumours.
|
|
| 7. |
- Anand, Aseem, et al.
(författare)
-
A preanalytic validation study of automated bone scan index : Effect on accuracy and reproducibility due to the procedural variabilities in bone scan image acquisition
- 2016
-
Ingår i: Journal of Nuclear Medicine. - : Society of Nuclear Medicine. - 0161-5505 .- 2159-662X. ; 57:12, s. 1865-1871
-
Tidskriftsartikel (refereegranskat)abstract
- The effect of the procedural variability in image acquisition on the quantitative assessment of bone scan is unknown. Here, we have developed and performed preanalytical studies to assess the impact of the variability in scanning speed and in vendor-specific γ-camera on reproducibility and accuracy of the automated bone scan index (BSI). Methods: Two separate preanalytical studies were performed: a patient study and a simulation study. In the patient study, to evaluate the effect on BSI reproducibility, repeated bone scans were prospectively obtained from metastatic prostate cancer patients enrolled in 3 groups (Grp). In Grp1, the repeated scan speed and the γ-camera vendor were the same as that of the original scan. In Grp2, the repeated scan was twice the speed of the original scan. In Grp3, the repeated scan used a different γ-camera vendor than that used in the original scan. In the simulation study, to evaluate the effect on BSI accuracy, bone scans of a virtual phantom with predefined skeletal tumor burden (phantom-BSI) were simulated against the range of image counts (0.2, 0.5, 1.0, and 1.5 million) and separately against the resolution settings of the γ-cameras. The automated BSI was measured with a computer-automated platform. Reproducibility was measured as the absolute difference between the repeated BSI values, and accuracy was measured as the absolute difference between the observed BSI and the phantom-BSI values. Descriptive statistics were used to compare the generated data. Results: In the patient study, 75 patients, 25 in each group, were enrolled. The reproducibility of Grp2 (mean ± SD, 0.35 ± 0.59) was observed to be significantly lower than that of Grp1 (mean ± SD, 0.10 ± 0.13; P < 0.0001) and that of Grp3 (mean ± SD, 0.09 ± 0.10; P < 0.0001). However, no significant difference was observed between the reproducibility of Grp3 and Grp1 (P = 0.388). In the simulation study, the accuracy at 0.5 million counts (mean ± SD, 0.57 ± 0.38) and at 0.2 million counts (mean ± SD, 4.67 ± 0.85) was significantly lower than that observed at 1.5 million counts (mean ± SD, 0.20 ± 0.26; P < 0.0001). No significant difference was observed in the accuracy data of the simulation study with vendor-specific γ-cameras (P 5 0.266). Conclusion: In this study, we observed that the automated BSI accuracy and reproducibility were dependent on scanning speed but not on the vendor-specific γ-cameras. Prospective BSI studies should standardize scanning speed of bone scans to obtain image counts at or above 1.5 million.
|
|
| 8. |
|
|
| 9. |
- Anand, Aseem, et al.
(författare)
-
Automated Bone Scan Index as a quantitative imaging biomarker in metastatic castration-resistant prostate cancer patients being treated with enzalutamide
- 2016
-
Ingår i: EJNMMI Research. - : Springer. - 2191-219X. ; 6
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Having performed analytical validation studies, we are now assessing the clinical utility of the upgraded automated Bone Scan Index (BSI) in metastatic castration-resistant prostate cancer (mCRPC). In the present study, we retrospectively evaluated the discriminatory strength of the automated BSI in predicting overall survival (OS) in mCRPC patients being treated with enzalutamide.METHODS: Retrospectively, we included patients who received enzalutamide as a clinically approved therapy for mCRPC and had undergone bone scan prior to starting therapy. Automated BSI, prostate-specific antigen (PSA), hemoglobin (HgB), and alkaline phosphatase (ALP) were obtained at baseline. Change in automated BSI and PSA were obtained from patients who have had bone scan at week 12 of treatment follow-up. Automated BSI was obtained using the analytically validated EXINI Bone(BSI) version 2. Kendall's tau (τ) was used to assess the correlation of BSI with other blood-based biomarkers. Concordance index (C-index) was used to evaluate the discriminating strength of automated BSI in predicting OS.RESULTS: Eighty mCRPC patients with baseline bone scans were included in the study. There was a weak correlation of automated BSI with PSA (τ = 0.30), with HgB (τ = -0.17), and with ALP (τ = 0.56). At baseline, the automated BSI was observed to be predictive of OS (C-index 0.72, standard error (SE) 0.03). Adding automated BSI to the blood-based model significantly improved the C-index from 0.67 to 0.72, p = 0.017. Treatment follow-up bone scans were available from 62 patients. Both change in BSI and percent change in PSA were predictive of OS. However, the combined predictive model of percent PSA change and change in automated BSI (C-index 0.77) was significantly higher than that of percent PSA change alone (C-index 0.73), p = 0.041.CONCLUSIONS: The upgraded and analytically validated automated BSI was found to be a strong predictor of OS in mCRPC patients. Additionally, the change in automated BSI demonstrated an additive clinical value to the change in PSA in mCRPC patients being treated with enzalutamide.
|
|
| 10. |
- Anand, Aseem, et al.
(författare)
-
Automated Bone Scan Index to Optimize Prostate Cancer Working Group Radiographic Progression Criteria for Men With Metastatic Castration-Resistant Prostate Cancer
- 2022
-
Ingår i: Clinical Genitourinary Cancer. - : Elsevier BV. - 1558-7673. ; 20:3, s. 270-277
-
Tidskriftsartikel (refereegranskat)abstract
- Introduction: Radiographic progression-free survival (rPFS) by Prostate Cancer Working Group (PCWG) criteria is a radiographic endpoint. The automated bone scan index (aBSI) quantifies osseous disease burden on bone scintigraphy as a percentage of total skeletal weight. Using the aBSI, we sought to quantify increase in tumor burden represented by PCWG progression criteria, and to determine the interval increase that best associates with overall survival (OS). Patient and Methods: Retrospective analysis of trials using androgen receptor axis–targeted drugs for metastatic castration resistant prostate cancer patients (mCRPC). aBSI increase in bone disease was assessed from baseline scan to time-to-progression (per PCWG criteria). Threshold for time to aBSI increase were explored and the association between each time-to-threshold and OS was computed. Results: A total of 169 mCPRC patients had bone scans available for aBSI analysis. Of these, 90 (53%) had progression in bone meeting PCWG criteria. Total aBSI increase in patients meeting PCWG criteria was 1.22 (interquartile range [IQR]: 0.65-2.49), with a median relative increase of 109% (IQR: 40%-377%). Median aBSI at baseline was 3.1 (IQR: 1.3-7.1). The best association between OS and time-to-progression occurred with an absolute increase in aBSI equal to 0.6 (Kendall's tau 0.52). Conclusion: An absolute increase of 0.6 or more in aBSI from the first follow-up scan results in the highest association with OS in patients with mCRPC. The rPFS by PCWG, identified progression at nearly twice this tumor burden, suggesting that aBSI may be used to further develop the PCWG criteria without degrading its association with OS.
|
|
