| 1. |
- Makvandi, Kianoush, et al.
(författare)
-
Multiparametric magnetic resonance imaging allows non-invasive functional and structural evaluation of diabetic kidney disease
- 2022
-
Ingår i: Clinical Kidney Journal. - : Oxford University Press (OUP). - 2048-8505 .- 2048-8513. ; 15:7
-
Tidskriftsartikel (refereegranskat)abstract
- Background We sought to develop a novel non-contrast multiparametric MRI (mpMRI) protocol employing several complementary techniques in a single scan session for a comprehensive functional and structural evaluation of diabetic kidney disease (DKD). Methods In the cross-sectional part of this prospective observational study, 38 subjects ages 18-79 years with type 2 diabetes and DKD [estimated glomerular filtration rate (eGFR) 15-60 mL/min/1.73 m(2)] and 20 age- and gender-matched healthy volunteers (HVs) underwent mpMRI. Repeat mpMRI was performed on 23 DKD subjects and 10 HVs. By measured GFR (mGFR), 2 DKD subjects had GFR stage G2, 16 stage G3 and 20 stage G4/G5. A wide range of MRI biomarkers associated with kidney haemodynamics, oxygenation and macro/microstructure were evaluated. Their optimal sensitivity, specificity and repeatability to differentiate diabetic versus healthy kidneys and categorize various stages of disease as well as their correlation with mGFR/albuminuria was assessed. Results Several MRI biomarkers differentiated diabetic from healthy kidneys and distinct GFR stages (G3 versus G4/G5); mean arterial flow (MAF) was the strongest predictor (sensitivity 0.94 and 1.0, specificity 1.00 and 0.69; P = .04 and .004, respectively). Parameters significantly correlating with mGFR were specific measures of kidney haemodynamics, oxygenation, microstructure and macrostructure, with MAF being the strongest univariate predictor (r = 0.92; P < .0001). Conclusions A comprehensive and repeatable non-contrast mpMRI protocol was developed that, as a single, non-invasive tool, allows functional and structural assessment of DKD, which has the potential to provide valuable insights into underlying pathophysiology, disease progression and analysis of efficacy/mode of action of therapeutic interventions in DKD.
|
|
| 2. |
- Huvila, J., et al.
(författare)
-
Combined ASRGL1 and p53 immunohistochemistry as an independent predictor of survival in endometrioid endometrial carcinoma
- 2018
-
Ingår i: Gynecologic Oncology. - : Academic Press Inc.. - 0090-8258 .- 1095-6859. ; 149:1, s. 173-180
-
Tidskriftsartikel (refereegranskat)abstract
- Objective: In clinical practise, prognostication of endometrial cancer is based on clinicopathological risk factors. The use of immunohistochemistry-based markers as prognostic tools is generally not recommended and a systematic analysis of their utility as a panel is lacking. We evaluated whether an immunohistochemical marker panel could reliably assess endometrioid endometrial cancer (EEC) outcome independent of clinicopathological information. Methods: A cohort of 306 EEC specimens was profiled using tissue microarray (TMA). Cost- and time-efficient immunohistochemical analysis of well-established tissue biomarkers (ER, PR, HER2, Ki-67, MLH1 and p53) and two new biomarkers (L1CAM and ASRGL1) was carried out. Statistical modelling with embedded variable selection was applied on the staining results to identify minimal prognostic panels with maximal prognostic accuracy without compromising generalizability. Results: A panel including p53 and ASRGL1 immunohistochemistry was identified as the most accurate predictor of relapse-free and disease-specific survival. Within this panel, patients were allocated into high- (5.9%), intermediate- (29.5%) and low- (64.6%) risk groups where high-risk patients had a 30-fold risk (P < 0.001) of dying of EEC compared to the low-risk group. Conclusions: P53 and ASRGL1 immunoprofiling stratifies EEC patients into three risk groups with significantly different outcomes. This simple and easily applicable panel could provide a useful tool in EEC risk stratification and guiding the allocation of treatment modalities.
|
|
| 3. |
- Borrelli, Pablo, et al.
(författare)
-
Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival
- 2021
-
Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 41:1, s. 62-67
-
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.
|
|
| 4. |
- Polymeri, Erini, et al.
(författare)
-
Deep learning-based quantification of PET/CT prostate gland uptake : association with overall survival
- 2020
-
Ingår i: Clinical Physiology and Functional Imaging. - Chichester : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 40:2, s. 106-113
-
Tidskriftsartikel (refereegranskat)abstract
- Aim: To validate a deep-learning (DL) algorithm for automated quantification of prostate cancer on positron emission tomography/computed tomography (PET/CT) and explore the potential of PET/CT measurements as prognostic biomarkers. Material and methods: Training of the DL-algorithm regarding prostate volume was performed on manually segmented CT images in 100 patients. Validation of the DL-algorithm was carried out in 45 patients with biopsy-proven hormone-naïve prostate cancer. The automated measurements of prostate volume were compared with manual measurements made independently by two observers. PET/CT measurements of tumour burden based on volume and SUV of abnormal voxels were calculated automatically. Voxels in the co-registered 18F-choline PET images above a standardized uptake value (SUV) of 2·65, and corresponding to the prostate as defined by the automated segmentation in the CT images, were defined as abnormal. Validation of abnormal voxels was performed by manual segmentation of radiotracer uptake. Agreement between algorithm and observers regarding prostate volume was analysed by Sørensen-Dice index (SDI). Associations between automatically based PET/CT biomarkers and age, prostate-specific antigen (PSA), Gleason score as well as overall survival were evaluated by a univariate Cox regression model. Results: The SDI between the automated and the manual volume segmentations was 0·78 and 0·79, respectively. Automated PET/CT measures reflecting total lesion uptake and the relation between volume of abnormal voxels and total prostate volume were significantly associated with overall survival (P = 0·02), whereas age, PSA, and Gleason score were not. Conclusion: Automated PET/CT biomarkers showed good agreement to manual measurements and were significantly associated with overall survival. © 2019 The Authors. Clinical Physiology and Functional Imaging published by John Wiley & Sons Ltd on behalf of Scandinavian Society of Clinical Physiology and Nuclear Medicine
|
|
| 5. |
- Friedli, Iris, et al.
(författare)
-
Magnetic Resonance Imaging in Clinical Trials of Diabetic Kidney Disease
- 2023
-
Ingår i: Journal of Clinical Medicine. - 2077-0383. ; 12:14
-
Forskningsöversikt (refereegranskat)abstract
- Chronic kidney disease (CKD) associated with diabetes mellitus (DM) (known as diabetic kidney disease, DKD) is a serious and growing healthcare problem worldwide. In DM patients, DKD is generally diagnosed based on the presence of albuminuria and a reduced glomerular filtration rate. Diagnosis rarely includes an invasive kidney biopsy, although DKD has some characteristic histological features, and kidney fibrosis and nephron loss cause disease progression that eventually ends in kidney failure. Alternative sensitive and reliable non-invasive biomarkers are needed for DKD (and CKD in general) to improve timely diagnosis and aid disease monitoring without the need for a kidney biopsy. Such biomarkers may also serve as endpoints in clinical trials of new treatments. Non-invasive magnetic resonance imaging (MRI), particularly multiparametric MRI, may achieve these goals. In this article, we review emerging data on MRI techniques and their scientific, clinical, and economic value in DKD/CKD for diagnosis, assessment of disease pathogenesis and progression, and as potential biomarkers for clinical trial use that may also increase our understanding of the efficacy and mode(s) of action of potential DKD therapeutic interventions. We also consider how multi-site MRI studies are conducted and the challenges that should be addressed to increase wider application of MRI in DKD.
|
|
| 6. |
- Hofving, Tobias, 1989, et al.
(författare)
-
177 Lu-octreotate therapy for neuroendocrine tumours is enhanced by Hsp90 inhibition
- 2019
-
Ingår i: Endocrine-Related Cancer. - 1479-6821 .- 1351-0088. ; 26:4, s. 437-449
-
Tidskriftsartikel (refereegranskat)abstract
- Lu-177-octreotate is an FDA-approved radionuclide therapy for patients with gastroenteropancreatic neuroendocrine tumours (NETs) expressing somatostatin receptors. The Lu-177-octreotate therapy has shown promising results in clinical trials by prolonging progression-free survival, but complete responses are still uncommon. The aim of this study was to improve the Lu-177-octreotate therapy by means of combination therapy. To identify radiosensitising inhibitors, two cell lines, GOT1 and P-STS, derived from small intestinal neuroendocrine tumours (SINETs), were screened with 1224 inhibitors alone or in combination with external radiation. The screening revealed that inhibitors of Hsp90 can potentiate the tumour cell-killing effect of radiation in a synergistic fashion (GOT1; false discovery rate < 3.2 x 10(-11)). The potential for Hsp90 inhibitor ganetespib to enhance the anti-tumour effect of Lu-177-octreotate in an in vivo setting was studied in the somatostatin receptor-expressing GOT1 xenograft model. The combination led to a larger decrease in tumour volume relative to monotherapies and the tumour-reducing effect was shown to be synergistic. Using patient-derived tumour cells from eight metastatic SINETs, we could show that ganetespib enhanced the effect of Lu-177-octreotate therapy for all investigated patient tumours. Levels of Hsp90 protein expression were evaluated in 767 SINETs from 379 patients. We found that Hsp90 expression was upregulated in tumour cells relative to tumour stroma in the vast majority of SINETs. We conclude that Hsp90 inhibitors enhance the tumour-killing effect of Lu-177-octreotate therapy synergistically in SINET tumour models and suggest that this potentially promising combination should be further evaluated.
|
|
| 7. |
- Ying, T. M., et al.
(författare)
-
Automated artificial intelligence-based analysis of skeletal muscle volume predicts overall survival after cystectomy for urinary bladder cancer
- 2021
-
Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 5:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background Radical cystectomy for urinary bladder cancer is a procedure associated with a high risk of complications, and poor overall survival (OS) due to both patient and tumour factors. Sarcopenia is one such patient factor. We have developed a fully automated artificial intelligence (AI)-based image analysis tool for segmenting skeletal muscle of the torso and calculating the muscle volume. Methods All patients who have undergone radical cystectomy for urinary bladder cancer 2011-2019 at Sahlgrenska University Hospital, and who had a pre-operative computed tomography of the abdomen within 90 days of surgery were included in the study. All patients CT studies were analysed with the automated AI-based image analysis tool. Clinical data for the patients were retrieved from the Swedish National Register for Urinary Bladder Cancer. Muscle volumes dichotomised by the median for each sex were analysed with Cox regression for OS and logistic regression for 90-day high-grade complications. The study was approved by the Swedish Ethical Review Authority (2020-03985). Results Out of 445 patients who underwent surgery, 299 (67%) had CT studies available for analysis. The automated AI-based tool failed to segment the muscle volume in seven (2%) patients. Cox regression analysis showed an independent significant association with OS (HR 1.62; 95% CI 1.07-2.44; p = 0.022). Logistic regression did not show any association with high-grade complications. Conclusion The fully automated AI-based CT image analysis provides a low-cost and meaningful clinical measure that is an independent biomarker for OS following radical cystectomy.
|
|
| 8. |
- Nordin, Elise, 1985, et al.
(författare)
-
An inverse association between plasma benzoxazinoid metabolites and PSA after rye intake in men with prostate cancer revealed with a new method
- 2022
-
Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 12:1
-
Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer (PC) is a common cancer among men, and preventive strategies are warranted. Benzoxazinoids (BXs) in rye have shown potential against PC in vitro but human studies are lacking. The aim was to establish a quantitative method for analysis of BXs and investigate their plasma levels after a whole grain/bran rye vs refined wheat intervention, as well as exploring their association with PSA, in men with PC. A quantitative method for analysis of 22 BXs, including novel metabolites identified by mass spectrometry and NMR, was established, and applied to plasma samples from a randomized crossover study where patients with indolent PC (n = 17) consumed 485 g whole grain rye/rye bran or fiber supplemented refined wheat daily for 6 wk. Most BXs were significantly higher in plasma after rye (0.3–19.4 nmol/L in plasma) vs. refined wheat (0.05–2.9 nmol/L) intake. HBOA-glc, 2-HHPAA, HBOA-glcA, 2-HPAA-glcA were inversely correlated to PSA in plasma (p < 0.04). To conclude, BXs in plasma, including metabolites not previously analyzed, were quantified. BX metabolites were significantly higher after rye vs refined wheat consumption. Four BX-related metabolites were inversely associated with PSA, which merits further investigation.
|
|
| 9. |
- Stranne, Johan, 1970, et al.
(författare)
-
The rate of deterioration of erectile function increases with age: results from a longitudinal population based survey
- 2019
-
Ingår i: Scandinavian Journal of Urology. - : Medical Journals Sweden AB. - 2168-1805 .- 2168-1813. ; 53:2-3, s. 161-165
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Increasing age as a risk factor for erectile dysfunction (ED) is in most studies assumed to be a linear function. If this is not the case the assumption could lead to bias, e.g. when men of different ages are compared in interventional studies on ED. Objective: To explore the risk of developing ED over time for men from different age groups. Materials and methods: A questionnaire was sent to a number of male residents in Gothenburg, Sweden, in 1992 (n = 10,458). Men were randomly selected according to year of birth to obtain several cohorts at 5-year intervals of ages 45, 50, 55 years, etc., up to the age of 85 or older. In 2003 an analogous, slightly expanded, questionnaire was sent to a random sample of men from the age cohorts 46, 51 years, etc. (n = 10,845). A total of 4072 men received both surveys, thereby constituting a group of men followed longitudinally for 11 years. The future risk of developing ED in the different age cohorts, adjusted for a number of ED risk factors, was then assessed. Results: A total of 3257 men responded to both questionnaires (response rate = 80%, age range = 56–103 years). The risk of having ED increased substantially with increasing age, both within each survey and longitudinally between the surveys. The adjusted risk of developing ED within the next 11 years increased with a factor of 10, from 1.8% at the age of 45 years at baseline to as much as 11.4% at the age of 65 years. Conclusion: Age as a risk-factor for ED is a non-linear function and should be adjusted as such to avoid bias when including men of different ages in interventional studies on ED.
|
|
| 10. |
- Polymeri, Erini, et al.
(författare)
-
Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients
- 2021
-
Ingår i: Scandinavian Journal of Urology. - : Medical Journals Sweden AB. - 2168-1805 .- 2168-1813. ; 55:6, s. 427-433
-
Tidskriftsartikel (refereegranskat)abstract
- Objective Artificial intelligence (AI) offers new opportunities for objective quantitative measurements of imaging biomarkers from positron-emission tomography/computed tomography (PET/CT). Clinical image reporting relies predominantly on observer-dependent visual assessment and easily accessible measures like SUVmax, representing lesion uptake in a relatively small amount of tissue. Our hypothesis is that measurements of total volume and lesion uptake of the entire tumour would better reflect the disease`s activity with prognostic significance, compared with conventional measurements. Methods An AI-based algorithm was trained to automatically measure the prostate and its tumour content in PET/CT of 145 patients. The algorithm was then tested retrospectively on 285 high-risk patients, who were examined using F-18-choline PET/CT for primary staging between April 2008 and July 2015. Prostate tumour volume, tumour fraction of the prostate gland, lesion uptake of the entire tumour, and SUVmax were obtained automatically. Associations between these measurements, age, PSA, Gleason score and prostate cancer-specific survival were studied, using a Cox proportional-hazards regression model. Results Twenty-three patients died of prostate cancer during follow-up (median survival 3.8 years). Total tumour volume of the prostate (p = 0.008), tumour fraction of the gland (p = 0.005), total lesion uptake of the prostate (p = 0.02), and age (p = 0.01) were significantly associated with disease-specific survival, whereas SUVmax (p = 0.2), PSA (p = 0.2), and Gleason score (p = 0.8) were not. Conclusion AI-based assessments of total tumour volume and lesion uptake were significantly associated with disease-specific survival in this patient cohort, whereas SUVmax and Gleason scores were not. The AI-based approach appears well-suited for clinically relevant patient stratification and monitoring of individual therapy.
|
|
