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Browsing by Author "Mirtti, Tuomas"

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  • Risk of clinically significant prostate cancer after a non-suspicious prostate MRI - a comparison with the general population 
    Hoffström, Jaakko; Pylväläinen, Juho; Kenttämies, Anu; Auvinen, Anssi; Mirtti, Tuomas; Rannikko, Antti (2024)
    Background MRI (magnetic resonance imaging) of the prostate has become increasingly common in prostate cancer diagnostics. How clinicians should proceed after a non-suspicious MRI result is still unclear. This study compares the risk of clinically significant and insignificant prostate cancer in men with a non-suspicious MRI of the prostate with the general population. In addition, the correlation of PSA density with risk of prostate cancer is also evaluated. Methods In this retrospective population based cohort study 1682 men between 50-79 years of age with non-suspicious MRI results were identified. The cohort's age standardized incidence of clinically significant prostate cancer and the odds of clinically insignificant prostate cancer is compared with a local age and sex matched population, which consisted of 230,458 men. The comparison is made by calculating the incidence ratio and the odds ratio with 95% confidence intervals. The follow up period was six years. The comparison was repeated for those men with both non-suspicious MRI and low PSA density (<0.15ng/ml). Results The incidence of clinically significant prostate cancer in men with a non-suspicious MRI was significantly higher compared with the general population (1852 vs. 552 per 100,000 person-years, incidence ratio 3.4). By combining low PSA density with non-suspicious MRI results, the incidence dropped significantly (778 vs 552 per 100,000 person-years, incidence ratio 1.4). The odds ratio for clinically insignificant prostate cancer was 2.4 for all men with non-suspicious MRI and 5.0 for those men who also had low PSA density. Conclusions The risk of clinically significant prostate cancer is elevated even after a non-suspicious MRI compared with the general population. Low PSA density significantly reduced the risk of clinically significant prostate cancer. The odds ratio for clinically insignificant prostate cancer increased with low PSA density, which in turn increases the risk of overdiagnosis. The decision to biopsy the prostate should base on more risk factors than only non-suspicious MRI results.
  • Three-Dimensional Presentation of Tumor Histopathology : A Model Using Tongue Squamous Cell Carcinoma 
    Koivuholma, Anne; Aro, Katri; Mäkitie, Antti; Salmi, Mika; Mirtti, Tuomas; Hagström, Jaana; Atula, Timo (2021)
    Lääketieteessä kuvantamistutkimuksissa hyödynnetään usein kolmiulotteista (3D) mallintamista, jotta tutkittava kohde pystyttäisiin hahmottamaan yksiselitteisemmin. Sen sijaan histopatologiassa kaksiulotteinen (2D) esittämistapa on edelleen vallitseva tapa ilmoittaa esimerkiksi poistetun kasvaimen leikkausmarginaalit. Tutkimuksemme tarkoitus oli esittää leikkauksessa poistetun pehmytkudosresekaatin sisällä olevan kasvaimen dimensiot ja siitä tehtyjen histologisten leikkeiden sijainnit 3D muodossa luomalla resekaatista ja sen leikkeistä digitaalinen 3D-malli. Kehittelimme menetelmän käyttäen yleisesti saatavilla olevia instrumentteja keskittyen kielen levyepiteelikarsinooman mallintamiseen. Loimme menetelmän tunnistamalla ja ratkomalla ongelmia, jotka liittyivät histologisten leikkeiden leikesuuntien valintaan, joka aiemman kirjallisuuden perusteella on ollut keskeinen haaste pehmytkudosresekaatin 3D-mallin luomisessa. Tavanomaiseen resekaatin käsittelyyn verrattuna lisävaiheita olivat ainoastaan leikkausresekaatin skannaaminen ennen histopatologisten leikkeiden keräämistä sekä itse karsinooman mallintaminen digitaaliseksi. Nämä lisävaiheet vaativat ainoastaan 3D pöytäskannerin ja 3D mallinnusohjelmiston. Työssä esittelemme leikkausresekaatin ja histopatologisten leikkeiden mallintamiseen liittyviä haasteita ja niille kehittämiämme ratkaisuja. Työn tuloksena esittelemme valmiin 3D-mallin kielen levyepiteelikarsinooman leikkausresekaatista ja sen sisällä olevasta varsinaisesta kasvaimesta sekä digitaalisena mallina että puoliläpäisevänä valumallina (3D-tuloste). Kuvaamme työssä myös työvaiheet, jotka vaaditaan 3D-mallin luomiseksi. Julkaisuhetkellä tietääksemme työmme on ensimmäinen yritys esittää kielikasvaimen histopatologiset marginaalit 3D muodossa, kun aiemmin vain 2D muoto on ollut saatavilla. 3D-mallin luominen metodillamme ei vaadi ennalta määrättyjä leikesuuntia. Metodimme tarjoaa yksiselitteisemmän ja selkeämmän tavan havainnollistaa kasvaimen marginaalit, topografia ja orientaatio. Metodiamme voitaisiin tulevaisuudessa käyttää työkaluna postoperatiivisessa arvioinnissa sekä adjuvanttihoitojen suunnitelussa.
  • Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers 
    Lehto, Timo-Pekka; Stürenberg, Carolin; Malén, Adrian; Erikson, Andrew; Koistinen, Hannu; Mills, Ian; Rannikko, Antti; Mirtti, Tuomas (2021)
    Background: Improved prognostication is needed to minimize overtreatment in Grade Group (GG) 2-4 prostate cancer. Our aim was to determine, at messenger RNA (mRNA) level, the performance of the genes in the commercial panels Decipher, Oncotype DX, Prolaris and mutational panel MSK-IMPACT to predict metastasis-free and prostate cancer-specific death (PCSD) in patients with GG2-4 prostate cancer at radical prostatectomy. Methods: The retrospective cohort consisted of GG2-4 patients treated with radical prostatectomy (median follow-up 10.4 years). Seventy-six cases with post-operative metastasis or PCSD and 84 controls with similar clinical baseline risk, but without progression, were analyzed. Index lesion mRNA transcripts were analyzed using NanoString technology. Random forest models were trained using panel gene sets to predict clinical endpoints and area under the curve (AUC), sensitivity, specificity, Youden index and number needed to diagnose (NND) was measured. Survival probability was assessed with Kaplan-Meier estimator. Results: All gene sets outperformed clinical parameters and predicted metastasis-free and prostate cancer-specific survival. However, there were significant differences between the panels. In metastasis prediction, the genes in Oncotype DX had inferior performance (area under the curve [AUC] = 0.65) compared to other panels (AUC = 0.73-0.74). Decipher, MSK-IMPACT and Prolaris showed similar NND (2.83-3.12) with Oncotype DX having highest NND (4.79). In PCSD prediction, the Prolaris gene set performed worse (AUC = 0.66) than MSK-IMPACT or Decipher (AUC = 0.72). Oncotype DX performed similarly to other panels (AUC=0.69, p > .05). Oncotype DX demonstrated lowest NND (2.79) compared to other panels (4.22-5.66). Conclusion: Transcript analysis of genes included in commercial panels is feasible in survival prediction of GG2-4 patients after radical prostatectomy and may aid in clinical decision making. There were significant differences between the panels, and overall stronger predictive gene sets are needed. Prospective investigation is warranted in biopsy materials.

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