The feasibility of conducting manual image segmentation of 3D sonographic images of axillary lymph nodes

School of Allied Medical Professions ScholarshipThe current standards of axillary lymph node staging following cancer diagnosis involve significant ionization, morbidity, and cost. While sonography has not yet been used in this capacity, three dimensional ultrasound has been used in the modeling of breast tumors with some success. This study was interested in determining whether 3D ultrasound could be used to manually segment axillary lymph node images in order to determine a reliable volume for later possible clinical significance. Fourteen volunteers were collected and one to three of their axillary lymph nodes imaged using a 4D16L GE transducer, specially designed to make volume measurements. Each node was then manually segmented using a deformable snake by two licensed sonographers and one untrained student and their volume results compared. Between the licensed sonographers for nodes 1, 2, and 3 correlations of r = 0.9 were achieved. Between the student and Sonographer A correlations of r = 0.6, 0.9, and 0.9, respectively, were accomplished, while with Sonographer B the correlations were r = 0.5, 0.9, and 0.9. This demonstrated the feasibility and validity of this technology, as well as indicated the importance of increased operator training. Three dimensional ultrasound should not be ruled out as a non-ionizing, less invasive alternative in lymph node staging. Advisor: Dr. Kevin EvansNo embarg

Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice

While cross-sectional imaging has seen continuous progress and plays an undiscussedpivotal role in the diagnostic management and treatment planning of patients with rectal cancer, alargely unmet need remains for improved staging accuracy, assessment of treatment response andprediction of individual patient outcome. Moreover, the increasing availability of target therapies hascalled for developing reliable diagnostic tools for identifying potential responders and optimizingoverall treatment strategy on a personalized basis. Radiomics has emerged as a promising, still fullyevolving research topic, which could harness the power of modern computer technology to generatequantitative information from imaging datasets based on advanced data-driven biomathematicalmodels, potentially providing an added value to conventional imaging for improved patient manage-ment. The present study aimed to illustrate the contribution that current radiomics methods appliedto magnetic resonance imaging can offer to managing patients with rectal cancer

Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics

In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients' risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these "big data" in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer

Multimodality Imaging in Prostate Cancer

ABSTRACT Prostate cancer is the most common cancer in men in Finland. Its aggressiveness varies widely, from indolent to fatal disease. Accurate characterization of prostate cancer is extremely essential to prevent overtreatment while sustaining good survivorship and high quality of life. This is feasible using novel technology in imaging and automatic tools in treatment planning. In the first part of this thesis work, the aim was to evaluate anti-1-amino-3-18Ffluorocyclobutane-1-carboxylic acid (18F-FACBC) PET/CT, PET/MRI, and multiparametric MRI (mpMRI) in detection of primary prostate cancer. The uptake of 18F-FACBC was significantly stronger in tumors with higher Gleason score and it may therefore assist in targeted biopsies when combined with MRI. 18F-FACBC PET/MRI outperformed PET/CT but did not demonstrate higher diagnostic performance than mpMRI performed separately. Furthermore, PET/MRI and mpMRI failed to detect pelvic lymph node metastasis measuring less than 8mm. 18F-FACBC PET/MRI is promising in characterization of primary prostate cancer, especially if ablative treatments are planned. It is not likely to replace mpMRI in clinical practice. The second study assessed multimodality imaging in detecting bone metastasis in high-risk prostate cancer and breast cancer patients. All patients underwent 99mTc-HDP bone scintigraphy (BS), 99mTc-HDP SPECT, 99mTc-HDP SPECT/CT, 18F-NaF PET/CT, and whole body (wb) MRI+DWI. 99mTc-HDP SPECT/CT, 18F-NaF PET/CT, and wbMRI+DWI had superior sensitivity compared to conventional nuclear imaging. In particular non-BS techniques showed less equivocal findings. wbMRI+DWI was as accurate as 18F-NaF PET/CT for detecting bone metastasis and may be considered a potential “single-step” imaging modality for detection of bone metastasis in high-risk patients with prostate and breast cancer. The purpose of the third study was to evaluate and validate the performance of a fully automated segmentation tool (AST) in MRI-based radiotherapy planning of prostate cancer. It showed high agreement for delineating prostate, bladder, and rectum, compared to manual contouring, and suggested adoption of AST in clinical practice. Finally, the fourth study investigated the long-term toxicity after biologically guided radiotherapy in men with localized prostate cancer. Carbon-11 acetate (11C-ACE) PET-CT was used to guide dose escalation into metabolically active intraprostatic lesions. 11C-ACE PET-guided radiotherapy was feasible and well tolerated. Although erectile dysfunction was relatively common, severe gastro-intestinal symptoms were very rare, and no grade 3 genitourinary symptoms were present at five years after radiotherapy. The findings of this thesis have potential to improve diagnostic imaging and radiotherapy planning in primary and metastatic prostate cancer. Eventually, they are likely to improve patients’ quality of life and survival. KEYWORDS: prostate cancer, magnetic resonance imaging, positron emission tomography, radiotherapy planning, toxicity, bone metastasisTIIVISTELMÄ Eturauhassyöpä on miesten yleisin syöpä Suomessa. Sen taudinkuva vaihtelee laajasti rauhallisesta aggressiiviseen ja tappavaan. On oleellista, että taudin luonne arvioidaan tarkasti, jotta vältytään sen liialliselta hoidolta, tinkimättä erinomaisista hoitotuloksista selviytymisessä ja elämän laadussa. Uudet kuvantamisteknologiat ja automaattityökalut mahdollistavat tämän. Tämän väitöskirjan ensimmäisessä osatyössä oli tavoitteena arvioida anti-1-amino-3-18Ffluorosyklobutaani-1-karboksyylihappo (18F-FACBC) PET-tietokonetomografiaa (TT), PET-magneettiresonanssikuvantamista (MRI) ja multiparametrista MRI-kuvantamista (mpMRI) eturauhassyövän diagnoosivaiheessa. 18F-FACBC-kertymät olivat tilastollisesti merkitsevästi voimakkaampia korkean Gleason-luokituksen kasvaimissa, joten yhdistettyä PET-MRI-kuvantamista voidaan käyttää hyväksi esimerkiksi kohdennetussa koepalojen otossa. 18F-FACBC PET-MRI oli parempi kuin PET-TT ja samanveroinen kuin mpMRI eturauhassyövän diagnostiikassa. PET-MRI ja mpMRI eivät havainneet alle 8 mm:n läpimittaisia imusolmukemetastaaseja. 18F-FACBC PET-MRI on lupaava kuvantamismuoto eturauhassyövän diagnostiikassa, erityisesti kajoavia hoitoja suunniteltaessa, mutta ei korvanne mpMRI:a kliinisessä käytössä. Toinen osatyö käsitteli luustoetäpesäkkeiden toteamista eri kuvantamismenetelmillä korkean uusiutumisriskin eturauhas- ja rintasyöpäpotilailla. Kaikille potilaille tehtiin 99mTc-HDP luustokarttakuvaus, 99mTc-HDP SPECT, 99mTc-HDP SPECT-TT, 18F-NaF PET-TT ja koko kehon MRI diffuusiopainotettuna (wbMRI+DWI). 99mTc-HDP SPECT-TT, 18F-NaF PET-TT ja wbMRI+DWI olivat perinteistä luustokarttaa herkempiä luustometastaasien toteamisessa, koska epäspesifeiksi määriteltyjä muutoksia oli vähemmän. wbMRI+DWI osoitti yhtäläistä tarkkuutta luustometastaasien diagnosoinnissa 18F-NaF PET-TT:n verrattuna, joten sitä voitaisiin hyödyntää, käytettäessä vain yhtä kuvantamistapaa näiden potilaiden luustometastaasien toteamiseen. Kolmas osatyö arvioi ja validoi täysin automaattisen piirtotyökalun käyttöä MRI-pohjaisen sädehoidon suunnittelussa eturauhassyöpäpotilailla. Työkalu suoriutui hyvin eturauhasen, virtsarakon ja peräsuolen rajauksesta asiantuntijan käsin tekemiin rajauksiin verrattuna, puoltaen työkalun käyttöä luotettavasti myös kliinisessä työssä. Viimeisenä, neljännessä osatyössä arvioitiin biologisesti ohjatun eturauhassyövän sädehoidon aiheuttamia pitkäaikaishaittoja. Hiili-11 asetaatti (11C-ACE) PET-TT-kuvantamisen avulla suunniteltiin sädehoito, jossa metabolisesti aktiivisiin eturauhasen sisäisiin muutoksiin kohdistettiin korkeammat sädeannokset. 11C-ACE-PET-TT-ohjattu sädehoito oli toteuttamiskelpoinen ja hyvin siedetty. Vaikka erektiohäiriöt olivat suhteellisen yleisiä, vakavat suoliston haittavaikutukset olivat hyvin harvinaisia, eikä kolmannen asteen virtsateiden haittavaikutuksia esiintynyt lainkaan viiden vuoden kuluttua sädehoidosta. Tämän väitöskirjan löydökset voivat parantaa eturauhassyövän primaaridiagnostiikan kuvantamista ja sädehoidon suunnittelua, sekä luustoetäpesäkkeiden diagnostiikkaa. Näin voidaan kohentaa potilaiden elämänlaatua ja selviytymistä. AVAINSANAT: Eturauhassyöpä, magneettikuvaus, positroniemissiotomografia, sädehoidon suunnittelu, haittavaikutukset, luuston etäpesäkkee

Machine learning methods for histopathological image analysis

Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we introduce the application of digital pathological image analysis using machine learning algorithms, address some problems specific to such analysis, and propose possible solutions.Comment: 23 pages, 4 figure