Anu Kenttämies

ORCID: 0000-0002-3937-5307
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About
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Research Areas
  • Prostate Cancer Diagnosis and Treatment
  • Prostate Cancer Treatment and Research
  • Radiomics and Machine Learning in Medical Imaging
  • Cardiac Imaging and Diagnostics
  • Peptidase Inhibition and Analysis
  • Cancer, Lipids, and Metabolism
  • Bladder and Urothelial Cancer Treatments
  • Research in Social Sciences
  • Ubiquitin and proteasome pathways
  • Ultrasound and Hyperthermia Applications
  • MRI in cancer diagnosis
  • Health Systems, Economic Evaluations, Quality of Life
  • Cardiovascular Disease and Adiposity
  • Thermoregulation and physiological responses
  • Neurological disorders and treatments
  • Colorectal Cancer Screening and Detection
  • Molecular Biology Techniques and Applications
  • Parkinson's Disease Mechanisms and Treatments
  • Urologic and reproductive health conditions
  • Hemodynamic Monitoring and Therapy
  • Nursing Roles and Practices
  • Advanced MRI Techniques and Applications
  • Cardiac, Anesthesia and Surgical Outcomes
  • Restless Legs Syndrome Research
  • Urological Disorders and Treatments

University of Helsinki
2008-2024

Helsinki University Hospital
2017-2024

University College London
2023

Whipps Cross University Hospital
2023

Barts Health NHS Trust
2023

Royal Free London NHS Foundation Trust
2023

Royal London Hospital
2023

Aava Medical Centre
2021

Imaging Center
2021

Ministry for Foreign Affairs of Finland
2008

Francesco Giganti Alexander Ng Aqua Asif Vinson Wai‐Shun Chan Marimo Rossiter and 89 more Arjun Nathan Pramit Khetrapal Louise Dickinson Shonit Punwani Chris Brew‐Graves Alex Freeman Mark Emberton Caroline M. Moore Clare Allen Veeru Kasivisvanathan Adriano Basso Dias Aiman Haider Amara Khan Angela Tong Antti Rannikko Anu Kenttämies Ardeshir R. Rastinehad Armando Stabile Arnauld Villers Ash Tewari Aytekin Oto Bas Israël Byron Gaing Carmen Chi-Min Cho Carolina Aulló González Chau Hung Lee Christian Wetterauer Claudia Kesch Daniel A. Adamo Daniel Margolis Daniel José López Ruiz David Margel Declan G. Murphy Enrique Gómez‐Gómez Felix K.‐H. Chun Felix Preißer Francis Thomas Geert Villeirs Giancarlo Marra Gianluca Giannarini Giorgio Brembilla G. Robert Guglielmo Manenti Hannes Cash Ingrid Potyka Jan Philipp Radtke Jeffrey J. Leow Jens Theysohn Jim C. Hu Jingfei Ma Lance A. Mynderse Lars Boesen Lars Budäus Lars Schimmöller Lee Alexander Grant Luca Orecchia Maarten de Rooij Maneesh Ghei Marco Gatti Mariano Volpacchio Markku H. Vaarala Martina Pecoraro Massimo Imbriaco Matthias Roethke M.A. Rodríguez Cabello Nazar Miguel Paras Singh Nicola Muirhead Peter Ka‐Fung Chiu Philip Ryan Philippe Puech Pierre Mozer Pieter De Visschere Públio César Cavalcante Viana Raphaële Renard Penna Réka Novotta Renato Cuocolo Richard O’Sullivan Rossano Girometti Sangeet Ghai Scott E. Eggener Tharakeswara Bathala Tho Pham Tristan Barrett Valeria Panebianco Vibeke Løgager Vinayak Wagaskar Yaara Ber Y. Lebras

Background High variability in prostate MRI quality might reduce accuracy cancer detection. Purpose To prospectively evaluate the of scanners taking part control phase global PRIME (Prostate Imaging Using ± Contrast Enhancement) trial using Prostate Quality (PI-QUAL) standardized scoring system, give recommendations on how to improve protocols, and establish whether could be improved by these recommendations. Materials Methods In prospective clinical (PRIME), for each scanner, centers...

10.1148/radiol.231130 article EN Radiology 2023-10-01

Importance Magnetic Resonance Imaging (MRI) coupled with Prostate Imaging-Reporting and Data System (PI-RADS) provides a standardized scoring system for assessing clinical significance of prostate cancer (PCa). However, the association between PI-RADS scores key end-points remains underexplored due to limited follow-up data. Objective To evaluate cancer-specific mortality (PCSM), overall survival (OS), metastasis-free (MFS), biochemical recurrence (BCR) across multiple cohorts. Design,...

10.1101/2025.03.20.25324337 preprint EN cc-by medRxiv (Cold Spring Harbor Laboratory) 2025-03-21

Abstract Background Continuous levodopa‐carbidopa intestinal gel ( LCIG ) diminishes daily “off” time and dyskinesia in patients with advanced Parkinson′s disease PD ). Complications are common percutaneous endoscopic gastrostomy a jejunal extension tube PEG ‐J). Aim of the Study To report clinical outcome years 2006–2014 at Helsinki University Hospital. Patients Methods Levodopa‐carbidopa treatment started following ‐J placement after successful in‐hospital trial nasojejunal tube....

10.1002/brb3.737 article EN cc-by Brain and Behavior 2017-06-05

Abstract Magnetic resonance imaging (MRI) is increasingly used to triage patients for prostate biopsy. However, 9% 24% of clinically significant (cs) cancers (PCas) are not visible in MRI. We aimed identify histomic and transcriptomic determinants MRI visibility their association metastasis, PCa‐specific death (PCSD). studied 45 radical prostatectomy‐treated with csPCa (grade group [GG]2‐3), including 30 MRI‐visible 15 MRI‐invisible lesions, 18 men without PCa. First, histological...

10.1002/ijc.34743 article EN cc-by International Journal of Cancer 2023-09-28

Abstract Background: We compare the risk of clinically significant (csPCa; ISUP Grade Group ≥ 2) and insignificant prostate cancer (isPCa; 1) in men with a non-suspicious MRI (nMRI; PI-RADS ≤ general population, assess value PSA density (PSAD) stratification. Methods: In this retrospective population-based cohort study we identified 1,682 50–79-year-old men, who underwent nMRI at HUS (2016–2019). compared their age-standardized incidence rates (IRs) csPCa odds isPCa to local age- sex-matched...

10.1158/1055-9965.epi-23-1208 article EN cc-by-nc-nd Cancer Epidemiology Biomarkers & Prevention 2024-01-25

Introduction This study was conducted to describe the changes in repeat multiparametric MRI (mpMRI) occurring prostate cancer (PCa) patients during active surveillance (AS), and possible associations between mpMRI-related parameters predicting biopsy (Bx) Gleason score (GS) upgrading >3+3 protocol-based treatment change (TC). Materials methods The cohort consisted of 76 AS with GS 3+3 PCa at least two consecutive mpMRIs performed 2006–2015. Patients were followed according Prostate Cancer...

10.1371/journal.pone.0189272 article EN cc-by PLoS ONE 2017-12-27

To evaluate the feasibility of a population-based screening trial using prostate-specific antigen (PSA), kallikrein panel and multiparametric magnetic resonance imaging (MRI) aimed at minimizing overdiagnosis, while retaining mortality benefit.Feasibility algorithm was evaluated in terms participation, test results cancer detection. A random sample 400 men aged 65 years identified from population registry invited for with three stepwise tests (PSA, MRI). Men PSA levels ≥3 ng/mL were further...

10.1111/bju.15683 article EN cc-by-nc BJU International 2021-12-27

Abstract: Bathing in sauna is common Finland, where there are approximately 2 million saunas among the population of 5.2 million. In this paper, deaths occurring while a 1990–2002 Finland were studied by analyzing police and forensic autopsy reports, death certificates, toxicological results. The annual rate was less than per 100,000 inhabitants. Close to half (51%) cases determined be natural exposure heat cause 25%. Overall, 50% all under influence alcohol. main conclusion that rare event...

10.1111/j.1556-4029.2008.00703.x article EN Journal of Forensic Sciences 2008-05-01

The aim of this study is to investigate the potential impact prostate magnetic resonance imaging (MRI) -related interreader variability on a population-based randomized cancer screening trial (ProScreen). From January 2014 2018, 100 men aged 50-63 years with clinical suspicion (PCa) in Helsinki University Hospital underwent MRI. Nine radiologists individually reviewed pseudonymized MRI scans all two ProScreen centers. All were biopsied according histological composite variable comprising...

10.1186/s40644-020-00351-w article EN cc-by Cancer Imaging 2020-10-09

Background To determine the added value of preoperative prostate multiparametric MRI (mpMRI) supplementary to clinical variables and their role in predicting post prostatectomy adverse findings biochemically recurrent cancer (BCR). Methods All consecutive patients treated at HUS Helsinki University Hospital with robot assisted radical (RALP) between 2014 2015 were included analysis. The mpMRI data, variables, histopathological characteristics, follow-up information collected. Study...

10.1371/journal.pone.0235779 article EN cc-by PLoS ONE 2020-07-09

Some clinically significant prostate cancers are missed by MRI. We asked whether the tumor stroma in surgically treated localized cancer lesions positive or negative with MRI different their cellular and molecular properties, differences reflected to clinical course of disease. profiled stromal immune cell composition MRI-classified applying multiplexed fluorescence IHC (mfIHC) automated image analysis a cohort 343 patients (cohort I). compared variables between MRI-visible lesions,...

10.1158/2767-9764.crc-21-0183 article EN cc-by Cancer Research Communications 2022-03-21

<p>Supplementary Table S2. Baseline characteristics and follow-up details. A table listing baseline characteristic details for the participants of each study cohort.</p>

10.1158/1055-9965.25729207.v1 preprint EN cc-by 2024-05-01

<p>MRI specifications. A table listing the MRI sequence parameters used by two scanners in study. Images were obtained with phased-array coil and without endorectal coil.</p>

10.1158/1055-9965.25729210.v1 preprint EN cc-by 2024-05-01

<p>Supplementary Figure S1. Formula used for calculating follow-up time the general population. The Supplementary S1 illustrates process of to calculate men in population cohort at age Y. Population data (A and B) are sourced from Statistics Finland (RRID:SCR_024843) prostate cancer (PCa) is based on institutional pathology data. This calculation was repeated all ages (50-79 years).</p>

10.1158/1055-9965.25729213.v1 preprint EN cc-by 2024-05-01

<p>Supplementary Figure S1. Formula used for calculating follow-up time the general population. The Supplementary S1 illustrates process of to calculate men in population cohort at age Y. Population data (A and B) are sourced from Statistics Finland (RRID:SCR_024843) prostate cancer (PCa) is based on institutional pathology data. This calculation was repeated all ages (50-79 years).</p>

10.1158/1055-9965.25729213 preprint EN 2024-05-01

<p>Supplementary Table S2. Baseline characteristics and follow-up details. A table listing baseline characteristic details for the participants of each study cohort.</p>

10.1158/1055-9965.25729207 preprint EN cc-by 2024-05-01

<p>MRI specifications. A table listing the MRI sequence parameters used by two scanners in study. Images were obtained with phased-array coil and without endorectal coil.</p>

10.1158/1055-9965.25729210 preprint EN 2024-05-01

<div>AbstractBackground:<p>We compare the risk of clinically significant (csPCa; ISUP Grade Group ≥ 2) and insignificant prostate cancer (isPCa; 1) in men with a nonsuspicious MRI (nMRI; PI-RADS ≤ general population, assess value PSA density (PSAD) stratification.</p>Methods:<p>In this retrospective population-based cohort study we identified 1,682 50–79-year-old men, who underwent nMRI at HUS (2016–2019). We compared their age-standardized incidence rates (IR) csPCa...

10.1158/1055-9965.c.7209244.v1 preprint EN 2024-05-01

<div>AbstractBackground:<p>We compare the risk of clinically significant (csPCa; ISUP Grade Group ≥ 2) and insignificant prostate cancer (isPCa; 1) in men with a nonsuspicious MRI (nMRI; PI-RADS ≤ general population, assess value PSA density (PSAD) stratification.</p>Methods:<p>In this retrospective population-based cohort study we identified 1,682 50–79-year-old men, who underwent nMRI at HUS (2016–2019). We compared their age-standardized incidence rates (IR) csPCa...

10.1158/1055-9965.c.7209244 preprint EN 2024-05-01
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