| 1. |
- Abrahamsson, Johan, et al.
(författare)
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Complete metabolic response with [18F]fluorodeoxyglucose-positron emission tomography/computed tomography predicts survival following induction chemotherapy and radical cystectomy in clinically lymph node positive bladder cancer
- 2022
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Ingår i: BJU International. - : Wiley. - 1464-4096 .- 1464-410X. ; 129:2, s. 174-181
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To determine whether repeated [18F]fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET-CT) scans can predict increased cancer-specific survival (CSS) after induction chemotherapy followed by radical cystectomy (RC). Patients and Methods: Between 2007 and 2018, 86 patients with clinically lymph node (LN)-positive bladder cancer (T1–T4, N1–N3, M0–M1a) were included and underwent a repeated FDG-PET-CT during cisplatin-based induction chemotherapy. The 71 patients that had a response to chemotherapy underwent RC. Response to chemotherapy was evaluated in LNs through repeated FDG-PET-CT and stratified as partial response or complete response using three different methods: maximum standardised uptake value (SUVmax), adapted Deauville criteria, and total lesion glycolysis (TLG). Progression-free survival (PFS) and CSS were analysed for all three methods by Cox regression analysis. Results: After a median follow-up of 40 months, 15 of the 71 patients who underwent RC had died from bladder cancer. Using SUVmax and the adapted Deauville criteria, multivariable Cox regression analyses adjusting for age, clinical tumour stage and LN stage showed that complete response was associated with increased PFS (hazard ratio [HR] 3.42, 95% confidence interval [CI] 1.20–9.77) and CSS (HR 3.30, 95% CI 1.02–10.65). Using TLG, a complete response was also associated with increased PFS (HR 5.17, 95% CI 1.90–14.04) and CSS (HR 6.32, 95% CI 2.06–19.41). Conclusions: Complete metabolic response with FDG-PET-CT predicts survival after induction chemotherapy followed by RC in patients with LN-positive bladder cancer and comprises a novel tool in evaluating response to chemotherapy before surgery. This strategy has the potential to tailor treatment in individual patients by identifying significant response to chemotherapy, which motivates the administration of a full course of induction chemotherapy with a higher threshold for suspending treatment due to toxicity and side-effects.
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| 2. |
- Abuhasanein, Suleiman, et al.
(författare)
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A novel model of artificial intelligence based automated image analysis of CT urography to identify bladder cancer in patients investigated for macroscopic hematuria
- 2024
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Ingår i: Scandinavian journal of urology. - : Medical Journal Sweden AB. - 2168-1805 .- 2168-1813. ; 59, s. 90-97
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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.
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| 3. |
- Abuhasanein, Suleiman, et al.
(författare)
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A novel model of artificial intelligence based automated image analysis of CT urography to identify bladder cancer in patients investigated for macroscopic hematuria
- 2024
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Ingår i: Scandinavian Journal of Urology. - : Medical Journal Sweden AB. - 2168-1805 .- 2168-1813. ; 59, s. 90-97
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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.
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| 4. |
- Almer, Jakob, et al.
(författare)
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Prevalence of manual Strauss LBBB criteria in patients diagnosed with the automated Glasgow LBBB criteria.
- 2015
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Ingår i: Journal of Electrocardiology. - : Elsevier BV. - 1532-8430 .- 0022-0736. ; 48:4, s. 558-564
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Tidskriftsartikel (refereegranskat)abstract
- About one-third of patients undergoing cardiac resynchronization therapy because of left bundle branch block (LBBB) and heart failure do not improve. Strauss et al. have developed strict criteria to more accurately define complete LBBB in this patient group. The aim of this study was to investigate the prevalence of the manual application of the Strauss criteria for LBBB (QRS≥140ms in men, ≥130ms in women, along with mid-QRS notching/slurring) in consecutive patients who have been diagnosed with LBBB by the automated Glasgow criteria (QRS≥120ms).
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| 5. |
- Anand, Aseem, et al.
(författare)
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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
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Ingår i: Journal of Nuclear Medicine. - : Society of Nuclear Medicine. - 0161-5505 .- 2159-662X. ; 57:12, s. 1865-1871
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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.
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| 6. |
- Anand, Aseem, et al.
(författare)
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Assessing Radiographic Response to 223Ra with an Automated Bone Scan Index in Metastatic Castration-Resistant Prostate Cancer Patients
- 2020
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Ingår i: Journal of Nuclear Medicine. - : Society of Nuclear Medicine. - 0161-5505 .- 2159-662X .- 1535-5667. ; 61:5, s. 671-675
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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.
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| 7. |
- Bajc, Marika, et al.
(författare)
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Assessment of Ventilation and Perfusion in Patients with COVID-19 Discloses Unique Information of Pulmonary Function to a Clinician : Case Reports of V/P SPECT
- 2021
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Ingår i: Clinical Medicine Insights: Circulatory, Respiratory and Pulmonary Medicine. - : SAGE Publications. - 1179-5484. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- V/P SPECT from 4 consecutive patients with COVID-19 suggests that ventilation and perfusion images may be applied to diagnose or exclude pulmonary embolism, verify nonsegmental diversion of perfusion from the ventilated areas (dead space ventilation) that may represent inflammation of the pulmonary vasculature, detect the reversed mismatch of poor ventilation and better preserved perfusion (shunt perfusion) in bilateral pulmonary inflammation and indicate redistribution of lung perfusion (antigravitational hyperperfusion) due to cardiac congestion. V/P mismatch and reversed mismatch may be extensive enough to diminish dramatically preserved matching ventilation/perfusion and to induce severe hypoxemia in COVID-19.
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| 8. |
- Bjöersdorff, Mimmi, et al.
(författare)
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Detection of lymph node metastases in patients with prostate cancer: Comparing conventional and digital F-18 -fluorocholine PET-CT using histopathology as a reference
- 2022
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Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 42:6, s. 381-388
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Tidskriftsartikel (refereegranskat)abstract
- Background: Positron emission tomography-computed tomography (PET-CD with [F-18]-fluorocholine (FCH) is used to detect and stage metastatic lymph nodes in patients with prostate cancer. Improvements to hardware and software have recently been made. We compared the capability of detecting regional lymph node metastases using conventional and digital silicon photomultiplier (SiPM)-based PET-CT technology for FCH. Extended pelvic lymph node dissection (ePLND) histopathology was used as a reference method. Methods: The study retrospectively examined 177 patients with intermediate or high-risk prostate cancer who had undergone staging with FCH PET-CT before ePLND. Images were obtained with either the conventional Philips Gemini PET-CT (n = 93) or the digital SiPM-based GE Discovery MI PET-CT (n = 84) and compared. Results: Images that were obtained using the Philips Gemini PET-CT system showed 19 patients (20%) with suspected lymph node metastases, whereas the GE Discovery MI PET-CT revealed 36 such patients (43%). The sensitivity, specificity, and positive and negative predictive values were 0.3, 0.84, 0.47, and 0.72 for the Philips Gemini, while they were 0.58, 0.62, 0.31, and 0.83 for the GE Discovery MI, respectively. The areas under the curves in a receiver operating characteristic curve analysis were similar between the two PET-CT systems (0.57 for Philips Gemini and 0.58 for GE Discovery MI, p = 0.89). Conclusions: Marked differences in sensitivity and specificity were found for the different PET-CT systems, although the overall diagnostic performance was similar. These differences are probably due to differences in both hardware and software, including reconstruction algorithms, and should be considered when new technology is introduced.
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| 9. |
- Bjöersdorff, Mimmi, et al.
(författare)
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Impact of penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm for 18 F-fluorocholine PET-CT regarding image quality and interpretation
- 2019
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Ingår i: EJNMMI Physics. - : Springer Science and Business Media LLC. - 2197-7364. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Recently, the block-sequential regularized expectation maximization (BSREM) reconstruction algorithm was commercially introduced (Q.Clear, GE Healthcare, Milwaukee, WI, USA). However, the combination of noise-penalizing factor (β), acquisition time, and administered activity for optimal image quality has not been established for 18 F-fluorocholine (FCH). The aim was to compare image quality and diagnostic performance of different reconstruction protocols for patients with prostate cancer being examined with 18 F-FCH on a silicon photomultiplier-based PET-CT. Thirteen patients were included, injected with 4 MBq/kg, and images were acquired after 1 h. Images were reconstructed with frame durations of 1.0, 1.5, and 2.0 min using β of 150, 200, 300, 400, 500, and 550. An ordered subset expectation maximization (OSEM) reconstruction with a frame duration of 2.0 min was used for comparison. Images were quantitatively analyzed regarding standardized uptake values (SUV) in metastatic lymph nodes, local background, and muscle to obtain contrast-to-noise ratios (CNR) as well as the noise level in muscle. Images were analyzed regarding image quality and number of metastatic lymph nodes by two nuclear medicine physicians. Results: The highest median CNR was found for BSREM with a β of 300 and a frame duration of 2.0 min. The OSEM reconstruction had the lowest median CNR. Both the noise level and lesion SUV max decreased with increasing β. For a frame duration of 1.5 min, the median quality score was highest for β 400-500, and for a frame duration of 2.0 min the score was highest for β 300-500. There was no statistically significant difference in the number of suspected lymph node metastases between the different image series for one of the physicians, and for the other physician the number of lymph nodes differed only for one combination of image series. Conclusions: To achieve acceptable image quality at 4 MBq/kg 18 F-FCH, we propose using a β of 400-550 with a frame duration of 1.5 min. The lower β should be used if a high CNR is desired and the higher if a low noise level is important.
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| 10. |
- Borrelli, P., et al.
(författare)
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AI-based detection of lung lesions in F-18 FDG PET-CT from lung cancer patients
- 2021
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Ingår i: Ejnmmi Physics. - : Springer Science and Business Media LLC. - 2197-7364. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Background[F-18]-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) is a well-established modality in the work-up of patients with suspected or confirmed diagnosis of lung cancer. Recent research efforts have focused on extracting theragnostic and textural information from manually indicated lung lesions. Both semi-automatic and fully automatic use of artificial intelligence (AI) to localise and classify FDG-avid foci has been demonstrated. To fully harness AI's usefulness, we have developed a method which both automatically detects abnormal lung lesions and calculates the total lesion glycolysis (TLG) on FDG PET-CT.MethodsOne hundred twelve patients (59 females and 53 males) who underwent FDG PET-CT due to suspected or for the management of known lung cancer were studied retrospectively. These patients were divided into a training group (59%; n = 66), a validation group (20.5%; n = 23) and a test group (20.5%; n = 23). A nuclear medicine physician manually segmented abnormal lung lesions with increased FDG-uptake in all PET-CT studies. The AI-based method was trained to segment the lesions based on the manual segmentations. TLG was then calculated from manual and AI-based measurements, respectively and analysed with Bland-Altman plots.ResultsThe AI-tool's performance in detecting lesions had a sensitivity of 90%. One small lesion was missed in two patients, respectively, where both had a larger lesion which was correctly detected. The positive and negative predictive values were 88% and 100%, respectively. The correlation between manual and AI TLG measurements was strong (R-2 = 0.74). Bias was 42 g and 95% limits of agreement ranged from -736 to 819 g. Agreement was particularly high in smaller lesions.ConclusionsThe AI-based method is suitable for the detection of lung lesions and automatic calculation of TLG in small- to medium-sized tumours. In a clinical setting, it will have an added value due to its capability to sort out negative examinations resulting in prioritised and focused care on patients with potentially malignant lesions.
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| 11. |
- Borrelli, P., et al.
(författare)
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Artificial intelligence-aided CT segmentation for body composition analysis: a validation study
- 2021
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Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 5:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundBody composition is associated with survival outcome in oncological patients, but it is not routinely calculated. Manual segmentation of subcutaneous adipose tissue (SAT) and muscle is time-consuming and therefore limited to a single CT slice. Our goal was to develop an artificial-intelligence (AI)-based method for automated quantification of three-dimensional SAT and muscle volumes from CT images.MethodsEthical approvals from Gothenburg and Lund Universities were obtained. Convolutional neural networks were trained to segment SAT and muscle using manual segmentations on CT images from a training group of 50 patients. The method was applied to a separate test group of 74 cancer patients, who had two CT studies each with a median interval between the studies of 3days. Manual segmentations in a single CT slice were used for comparison. The accuracy was measured as overlap between the automated and manual segmentations.ResultsThe accuracy of the AI method was 0.96 for SAT and 0.94 for muscle. The average differences in volumes were significantly lower than the corresponding differences in areas in a single CT slice: 1.8% versus 5.0% (p <0.001) for SAT and 1.9% versus 3.9% (p < 0.001) for muscle. The 95% confidence intervals for predicted volumes in an individual subject from the corresponding single CT slice areas were in the order of 20%.Conclusions The AI-based tool for quantification of SAT and muscle volumes showed high accuracy and reproducibility and provided a body composition analysis that is more relevant than manual analysis of a single CT slice.
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| 12. |
- Borrelli, Pablo, et al.
(författare)
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Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival
- 2021
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Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 41:1, s. 62-67
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods can provide an objective image analysis. We aimed at developing and validating an AI-based tool for detection of lymph node lesions. Methods A group of 399 patients with biopsy-proven PCa who had undergone(18)F-choline PET/CT for staging prior to treatment were used to train (n = 319) and test (n = 80) the AI-based tool. The tool consisted of convolutional neural networks using complete PET/CT scans as inputs. In the test set, the AI-based lymph node detections were compared to those of two independent readers. The association with PCa-specific survival was investigated. Results The AI-based tool detected more lymph node lesions than Reader B (98 vs. 87/117;p = .045) using Reader A as reference. AI-based tool and Reader A showed similar performance (90 vs. 87/111;p = .63) using Reader B as reference. The number of lymph node lesions detected by the AI-based tool, PSA, and curative treatment was significantly associated with PCa-specific survival. Conclusion This study shows the feasibility of using an AI-based tool for automated and objective interpretation of PET/CT images that can provide assessments of lymph node lesions comparable with that of experienced readers and prognostic information in PCa patients.
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| 13. |
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| 14. |
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| 15. |
- Borrelli, P., et al.
(författare)
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Freely available convolutional neural network-based quantification of PET/CT lesions is associated with survival in patients with lung cancer
- 2022
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Ingår i: EJNMMI Physics. - : Springer Science and Business Media LLC. - 2197-7364. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Metabolic positron emission tomography/computed tomography (PET/CT) parameters describing tumour activity contain valuable prognostic information, but to perform the measurements manually leads to both intra- and inter-reader variability and is too time-consuming in clinical practice. The use of modern artificial intelligence-based methods offers new possibilities for automated and objective image analysis of PET/CT data. Purpose: We aimed to train a convolutional neural network (CNN) to segment and quantify tumour burden in [18F]-fluorodeoxyglucose (FDG) PET/CT images and to evaluate the association between CNN-based measurements and overall survival (OS) in patients with lung cancer. A secondary aim was to make the method available to other researchers. Methods: A total of 320 consecutive patients referred for FDG PET/CT due to suspected lung cancer were retrospectively selected for this study. Two nuclear medicine specialists manually segmented abnormal FDG uptake in all of the PET/CT studies. One-third of the patients were assigned to a test group. Survival data were collected for this group. The CNN was trained to segment lung tumours and thoracic lymph nodes. Total lesion glycolysis (TLG) was calculated from the CNN-based and manual segmentations. Associations between TLG and OS were investigated using a univariate Cox proportional hazards regression model. Results: The test group comprised 106 patients (median age, 76years (IQR 61–79); n = 59 female). Both CNN-based TLG (hazard ratio 1.64, 95% confidence interval 1.21–2.21; p = 0.001) and manual TLG (hazard ratio 1.54, 95% confidence interval 1.14–2.07; p = 0.004) estimations were significantly associated with OS. Conclusion: Fully automated CNN-based TLG measurements of PET/CT data showed were significantly associated with OS in patients with lung cancer. This type of measurement may be of value for the management of future patients with lung cancer. The CNN is publicly available for research purposes. © 2022, The Author(s).
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| 16. |
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| 17. |
- Cerić Andelius, Irma, et al.
(författare)
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First clinical experience of a ring-configured cadmium zinc telluride camera : A comparative study versus conventional gamma camera systems
- 2024
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Ingår i: Clinical Physiology and Functional Imaging. - 1475-0961. ; 44:1, s. 79-88
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: A novel semiconductor cadmium zinc telluride (CZT) gamma camera system using a block sequential regularized expectation maximization (BSREM) reconstruction algorithm is now clinically available. Here we investigate how a multi-purpose ring-configurated CZT system can be safely applied in clinics and describe the initial optimization process.METHOD: Seventy-six patients (bone-, cardiac- and lung scan) were scanned on a conventional gamma camera (planar and/or single-photon emission computed tomography [SPECT]/SPECT-CT) used in clinical routine and on the ring-configurated CZT camera Starguide (GE Healthcare). These data were used to validate and optimize the Starguide system for routine clinical use.RESULTS: Comparable image quality for the Starguide system, to that of the conventional gamma camera, was achieved for bone scan (4 min/bed position [BP] using a relative difference prior [RDP] with gamma 2 and beta 0.4, along with 10 iterations and 10 subsets), cardiac scan (8 min [stress] and 3 min 20 s [rest] using median root prior [MRP] with beta 0.07 non attenuation corrected and 0.008 attenuation corrected and 50 interations and 10 subsets for both stress and rest) and lung scan (10 min [vent] and 5 min [perf] using RDP with gamma 0.5 and beta 0.03 [vent] and 0.02 [perf] and 20 interations and 10 subsets for both vent and perf).CONCLUSIONS: It was possible to transition from a conventional gamma camera to the Starguide system as part of the clinical routine, with acceptable image quality. Images from the Starguide system were deemed to be at least as good as those from a conventional gamma camera.
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| 18. |
- Economou Lundeberg, Johan, et al.
(författare)
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Comparison between silicon photomultiplier-based and conventional PET/CT in patients with suspected lung cancer—a pilot study
- 2019
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Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Lung cancer is one of the most common cancers in the world. Early detection and correct staging are fundamental for treatment and prognosis. Positron emission tomography with computed tomography (PET/CT) is recommended clinically. Silicon (Si) photomultiplier (PM)-based PET technology and new reconstruction algorithms are hoped to increase the detection of small lesions and enable earlier detection of pathologies including metastatic spread. The aim of this study was to compare the diagnostic performance of a SiPM-based PET/CT (including a new block-sequential regularization expectation maximization (BSREM) reconstruction algorithm) with a conventional PM-based PET/CT including a conventional ordered subset expectation maximization (OSEM) reconstruction algorithm. The focus was patients admitted for 18F-fluorodeoxyglucose (FDG) PET/CT for initial diagnosis and staging of suspected lung cancer. Patients were scanned on both a SiPM-based PET/CT (Discovery MI; GE Healthcare, Milwaukee, MI, USA) and a PM-based PET/CT (Discovery 690; GE Healthcare, Milwaukee, MI, USA). Standardized uptake values (SUV) and image interpretation were compared between the two systems. Image interpretations were further compared with histopathology when available. Results: Seventeen patients referred for suspected lung cancer were included in our single injection, dual imaging study. No statically significant differences in SUVmax of suspected malignant primary tumours were found between the two PET/CT systems. SUVmax in suspected malignant intrathoracic lymph nodes was 10% higher on the SiPM-based system (p = 0.026). Good consistency (14/17 cases) between the PET/CT systems were found when comparing simplified TNM staging. The available histology results did not find any obvious differences between the systems. Conclusion: In a clinical setting, the new SiPM-based PET/CT system with a new BSREM reconstruction algorithm provided a higher SUVmax for suspected lymph node metastases compared to the PM-based system. However, no improvement in lung cancer detection was seen.
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| 19. |
- Edenbrandt, Lars, et al.
(författare)
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Area of ischemia assessed by physicians and software packages from myocardial perfusion scintigrams
- 2014
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Ingår i: BMC Medical Imaging. - : BioMed Central. - 1471-2342. ; 14:5
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Tidskriftsartikel (refereegranskat)abstract
- Background: The European Society of Cardiology recommends that patients with greater than 10% area of ischemia should receive revascularization. We investigated inter-observer variability for the extent of ischemic defects reported by different physicians and by different software tools, and if inter-observer variability was reduced when the physicians were provided with a computerized suggestion of the defects. Methods: Twenty-five myocardial perfusion single photon emission computed tomography (SPECT) patients who were regarded as ischemic according to the final report were included. Eleven physicians in nuclear medicine delineated the extent of the ischemic defects. After at least two weeks, they delineated the defects again, and were this time provided a suggestion of the defect delineation by EXINI Heart(TM) (EXINI). Summed difference scores and ischemic extent values were obtained from four software programs. Results: The median extent values obtained from the 11 physicians varied between 8% and 34%, and between 9% and 16% for the software programs. For all 25 patients, mean extent obtained from EXINI was 17.0% (+/- standard deviation (SD) 14.6%). Mean extent for physicians was 22.6% (+/- 15.6%) for the first delineation and 19.1% (+/- 14.9%) for the evaluation where they were provided computerized suggestion. Intra-class correlation (ICC) increased from 0.56 (95% confidence interval (CI) 0.41-0.72) to 0.81 (95% CI 0.71-0.90) between the first and the second delineation, and SD between physicians were 7.8 (first) and 5.9 (second delineation). Conclusions: There was large variability in the estimated ischemic defect size obtained both from different physicians and from different software packages. When the physicians were provided with a suggested delineation, the inter-observer variability decreased significantly.
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| 20. |
- Frennered, Anna, et al.
(författare)
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Patterns of pathologic lymph nodes in anal cancer : a PET-CT-based analysis with implications for radiotherapy treatment volumes
- 2021
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Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: This study investigates the patterns of PET-positive lymph nodes (LNs) in anal cancer. The aim was to provide information that could inform future anal cancer radiotherapy contouring guidelines. Methods: The baseline [18F]-FDG PET-CTs of 190 consecutive anal cancer patients were retrospectively assessed. LNs with a Deauville score (DS) of ≥3 were defined as PET-positive. Each PET-positive LN was allocated to a LN region and a LN sub-region; they were then mapped on a standard anatomy reference CT. The association between primary tumor localization and PET-positive LNs in different regions were analyzed. Results: PET-positive LNs (n = 412) were identified in 103 of 190 patients (54%). Compared to anal canal tumors with extension into the rectum, anal canal tumors with perianal extension more often had inguinal (P < 0.001) and less often perirectal (P < 0.001) and internal iliac (P < 0.001) PET-positive LNs. Forty-two patients had PET-positive LNs confined to a solitary region, corresponding to first echelon nodes. The most common solitary LN region was inguinal (25 of 42; 60%) followed by perirectal (26%), internal iliac (10%), and external iliac (2%). No PET-positive LNs were identified in the ischiorectal fossa or in the inguinal area located posterolateral to deep vessels. Skip metastases above the bottom of the sacroiliac joint were quite rare. Most external iliac PET-positive LNs were located posterior to the external iliac vein; only one was located in the lateral external iliac sub-region. Conclusions: The results support some specific modifications to the elective clinical target volume (CTV) in anal cancer. These changes would lead to reduced volumes of normal tissue being irradiated, which could contribute to a reduction in radiation side-effects.
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| 21. |
- Gulevski, Stephanie, et al.
(författare)
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MRI morphological characteristics of lymph nodes in anal squamous cell carcinoma
- 2024
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Ingår i: Abdominal Radiology. - 2366-004X. ; 49:4, s. 1042-1050
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesPre-treatment staging of anal squamous cell carcinoma (ASCC) includes pelvic MRI and [18F]-fluorodeoxyglucose positron emission tomography with computed tomography (PET-CT). MRI criteria to define lymph node metastases (LNMs) in ASCC are currently lacking. The aim of this study was to describe the morphological characteristics of lymph nodes (LNs) on MRI in ASCC patients with PET-CT-positive LNs.MethodsASCC patients treated at Skåne University Hospital between 2009 and 2017 were eligible for inclusion if at least one positive LN according to PET-CT and a pre-treatment MRI were present. All PET-CT-positive LNs and PET-CT-negative LNs were retrospectively identified on baseline MRI. Each LN was independently classified according to pre-determined morphological characteristics by two radiologists blinded to clinical patient information.ResultsSixty-seven ASCC patients were included, with a total of 181 PET-CT-positive LNs identified on baseline MRI with a median short-axis diameter of 9.0 mm (range 7.5–12 mm). MRI morphological characteristics of PET-CT-positive LNs included regular contour (87%), round shape (89%), and homogeneous signal intensity on T2-weighed images (67%). An additional 78 PET-CT-negative LNs were identified on MRI. These 78 LNs had a median size of 6.8 mm (range 5.5–8.0 mm). The majority of PET-CT-negative LNs had a regular contour, round shape, and a homogeneous signal that was congruent to the primary tumor.ConclusionsThere are MRI-specific morphological characteristics for pelvic LNs in ASCC. PET-CT-positive and negative LNs share similar morphological features apart from size, with PET-CT-positive LNs being significantly larger. Further studies are needed to determine discrimination criteria for LNM in ASCC.
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| 22. |
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| 23. |
- Gålne, Anni, et al.
(författare)
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AI-based quantification of whole-body tumour burden on somatostatin receptor PET/CT
- 2023
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Ingår i: European Journal of Hybrid Imaging. - 2510-3636. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Segmenting the whole-body somatostatin receptor-expressing tumour volume (SRETVwb) on positron emission tomography/computed tomography (PET/CT) images is highly time-consuming but has shown value as an independent prognostic factor for survival. An automatic method to measure SRETVwb could improve disease status assessment and provide a tool for prognostication. This study aimed to develop an artificial intelligence (AI)-based method to detect and quantify SRETVwb and total lesion somatostatin receptor expression (TLSREwb) from [68Ga]Ga-DOTA-TOC/TATE PET/CT images. Methods: A UNet3D convolutional neural network (CNN) was used to train an AI model with [68Ga]Ga-DOTA-TOC/TATE PET/CT images, where all tumours were manually segmented with a semi-automatic method. The training set consisted of 148 patients, of which 108 had PET-positive tumours. The test group consisted of 30 patients, of which 25 had PET-positive tumours. Two physicians segmented tumours in the test group for comparison with the AI model. Results: There were good correlations between the segmented SRETVwb and TLSREwb by the AI model and the physicians, with Spearman rank correlation coefficients of r = 0.78 and r = 0.73, respectively, for SRETVwb and r = 0.83 and r = 0.81, respectively, for TLSREwb. The sensitivity on a lesion detection level was 80% and 79%, and the positive predictive value was 83% and 84% when comparing the AI model with the two physicians. Conclusion: It was possible to develop an AI model to segment SRETVwb and TLSREwb with high performance. A fully automated method makes quantification of tumour burden achievable and has the potential to be more widely used when assessing PET/CT images.
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| 24. |
- Hakacova, Nina, et al.
(författare)
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Computer-based rhythm diagnosis and its possible influence on nonexpert electrocardiogram readers.
- 2012
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Ingår i: Journal of Electrocardiology. - : Elsevier BV. - 1532-8430 .- 0022-0736. ; 45, s. 18-22
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Systems providing computer-based analysis of the resting electrocardiogram (ECG) seek to improve the quality of health care by providing accurate and timely automatic diagnosis of, for example, cardiac rhythm to clinicians. The accuracy of these diagnoses, however, remains questionable. OBJECTIVES: We tested the hypothesis that (a) 2 independent automated ECG systems have better accuracy in rhythm diagnosis than nonexpert clinicians and (b) both systems provide correct diagnostic suggestions in a large percentage of cases where the diagnosis of nonexpert clinicians is incorrect. METHODS: Five hundred ECGs were manually analyzed by 2 senior experts, 3 nonexpert clinicians, and automatically by 2 automated systems. The accuracy of the nonexpert rhythm statements was compared with the accuracy of each system statement. The proportion of rhythm statements when the clinician's diagnoses were incorrect and the systems instead provided correct diagnosis was assessed. RESULTS: A total of 420 sinus rhythms and 156 rhythm disturbances were recognized by expert reading. Significance of the difference in accuracy between nonexperts and systems was P = .45 for system A and P = .11 for system B. The percentage of correct automated diagnoses in cases when the clinician was incorrect was 28% ± 10% for system A and 25% ± 11% for system B (P = .09). CONCLUSION: The rhythm diagnoses of automated systems did not reach better average accuracy than those of nonexpert readings. The computer diagnosis of rhythm can be incorrect in cases where the clinicians fail in reaching the correct ECG diagnosis.
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| 25. |
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