Dosimetric study of different radiotherapy techniques for treating Hodgkin\u27s lymphoma in mediastinal region

Uvod: Hodgkinov limfom (HL) je maligna bolezen limfatičnega sistema. V Sloveniji je v letu 2010 za HL zbolelo 66 bolnikov, v letu 2011 pa 41. Zdravljenje bolnikov s HL poteka s sistemsko terapijo in obsevanjem (RT). RT lahko povzroča številne pozne posledice zdravljenja. Sodobne obsevalne tehnike, kot so intenzitetno modulirana radioterapija (IMRT) in volumetrična modulirana ločna radioterapija (VMAT) omogočajo visoko konformnost predpisane doze okoli tarče in večje ščitenje rizičnih organov v primerjavi s tridimenzionalno konformalno radioterapijo (3DCRT). Namen: Namen dozimetrične primerjave različnih obsevalnih tehnik pri obsevanju HL v področju medpljučja je ugotoviti, katera izmed tehnik pripomore k najnižjim prejetim dozam na rizične organe (OAR) v medpljučju ob ustrezni homogeni pokritosti tarčnih volumnov. Metode: V raziskavo je bilo vključenih 10 bolnic, ki so bile zdravljene s 3DCRT v področju medpljučja zaradi Hodgkinovega limfoma (HL) med februarjem 2011 in avgustom 2015 na Onkološkem inštitutu (OI) v Ljubljani. Za vsako od bolnic so bili izdelani obsevalni načrti v tehnikah IMRT, VMAT in B-VMAT (»butterfly« VMAT). Obsevalni načrti so bili izdelani po protokolih za načrtovanje IMRT obsevanja na OI. Parametri za pokritost načrtovalnega obsevalnega volumna (PTV) in dozno obremenitev pljuč, srca, dojk, ščitnice, požiralnika, sapnika, hrbtenjače in področja izven PTV so bili nato primerjani med obsevalnimi tehnikami. Za preverjanje statistično značilnih razlik je bil uporabljen Kruskal-Wallis test. Rezultati: Rezultati raziskave kažejo, da tehnike IMRT, VMAT in B-VMAT (CI= 0,630,660,56) konformneje pokrijejo PTV kot 3DCRT (CI= 0,4). Razlik v povprečni dozi znotraj PTV in razlik v homogenosti doze med obsevalnimi tehnikami ni bilo. Povprečna doza v pljučih (Dmean) je bila najnižja pri 3DCRT (4,4 Gy) in najvišja pri VMAT (7,4 Gy). Pri IMRT je Dmean znašal 6,6 Gy in pri B-VMAT 6,4 Gy. Pri dojkah je najbližje 3DCRT tehniki B-VMAT. Dmean na srce je bila pri vseh tehnikah v precej podobna (od 3,6 do 4,8 Gy). Za srce so bili parametri V10, V25, V30 nižji pri vseh moduliranih tehnikah. Izjema je B-VMAT, ki je srce najbolj obremenil pri V10 (17,1 %). Pri ščitnici, sapniku in področju izven tarče ni bilo bistvenih razlik med obsevalnimi tehnikami. Požiralnik in hrbtenjačo so modulirane tehnike manj obremenile. Zaključek: Tehnike IMRT, VMAT, B-VMAT so konformnejše pri pokrivanju PTV in omogočajo nižjo obremenitev OAR z višjimi dozami, hkrati pa z nizkimi dozami obremenijo večje področje v primerjavi s 3DCRT. Kot najbolj uravnotežena tehnika med prispevkom nizkih in visokih doz na OAR se je pokazala B-VMAT.Introduction: Hodgkin lymphoma (HL) is a malignant disease of the lymphatic system. There were 66 patients in year 2010 and 41 patients in year 2011 diagnosed with HL in Slovenia. Patients with HL are treated with systemic therapy and radiotherapy (RT). Treatment with RT can cause acute and many long-term complications. Modern RT techniques such as intensity modulated radiotherapy (IMRT) and volumetric modulated arc radiotherapy (VMAT) can conformably cover planning target volume (PTV) with prescribed dose and can better protect organs at risk (OAR). Purpose: The purpose of the dosimetric comparison is to determine which of the techniques is better in lowering doses to OAR in mediastinal region and in the same time allowing sufficiently homogeneous coverage of the PTV. Methods: The study included 10 patients who were treated with RT of mediastinal HL. Patients were treated at the Institute of Oncology Ljubljana between February 2011 and August 2015. All were treated with 3DCRT. For each of the patient treatment plans were made using IMRT, VMAT and B-VMAT ("butterfly" VMAT) techniques. All irradiation plans were made using protocols for IMRT planning at the Institute of Oncology Ljubljana. Coverage of PTV and doses to the lungs, heart, breast, thyroid, esophagus, trachea, spinal cord and the to the area outside the PTV were compared. In order to verify statistically significant difference Kruskal-Wallis test was used. Results: The results show that IMRT, VMAT and B-VMAT (CI = 0.630.660.56) had more conformal dose distribution over the PTV than the 3DCRT (CI = 0.4). There were no major differences in the mean doses and in the homogeneity index for the PTV. The mean lung dose (Dmean) was lowest in 3DCRT (4.4 Gy) and the highest for VMAT (7.4 Gy). In IMRT Dmean was 6.6 Gy and in B-VMAT was 6.4 Gy. Observing doses to breast, B-VMAT had the closest results to 3DCRT. Dmean of the heart was quite similar in all techniques (from 3.6 to 4.8 Gy). Parameters V10, V25, V30 for the heart were lower in modulated techniques in comparison to 3DCRT, except for B-VMAT, which was the highest in the V10 (17.1%). None of the differences were statistically significant. In the thyroid, trachea and the area outside the target there were no significant differences between RT techniques. Doses to esophagus and spinal cord were lowest in modulated techniques. Conclusion: All modern RT techniques (IMRT, VMAT, B-VMAT) are better in conformably covering the PTV with prescribed dose. They can lower the percentage of OARs covered with higher doses. At the same time, they cover much higher percentage of OARs with low doses compared to 3DCRT. The most balanced technique between the contribution of low and high doses in OAR is B-VMAT

CALCULATION OF ELECTRICAL ENERGY QUALITY PARAMETERS, AND REPORTING PROCESS OPTIMIZATION

Električna energija ima v našem vsakodnevnem življenju pomembno vlogo. Z liberalizacijo evropskega energetskega trga je postala tržno blago, ki mora ustrezati določenim standardom kakovosti, kar spremljamo z zakonsko predpisanimi parametri. V diplomski nalogi smo načrtovali informacijsko rešitev, ki v distribucijskem elektroenergetskem podjetju optimizira proces poročanja zahtevanih parametrov. Pri tem smo izkoristili napredne topološke funkcije geografskega informacijskega sistema.In our daily lives, electric energy plays an important role. Liberalization in the European energy market, has turned this energy into a good, which must attain certain standards of quality. Electric energy distribution companies are obliged to control the quality of supply services with parameters as defined in the legislation. In this diploma thesis, we have modelled and implemented an information solution, which optimizes the process of reporting electric energy quality parameters. It is based on advanced topology functions of the geographic information system

Implementacija novega procesa poročanja v organizaciji x

Reporting is present in every company. Whether it is small or big, it cannot be avoided. It plays a crucial role in the process and progress of business. The quality of reporting affects the development of the work environment and the company. Since business report is a document that contains business information, which supports the decisions about the future-oriented business decisions, it is very important for it to be designed in such a way that it contains the key information for the recipient and provides support for business decisions. The reporting process can take place horizontally upwards or downwards. Content and structure vary depending on the recipient of the report. We live in an age when our every step is accompanied by digitization, computerization, artificial intelligence, mass data, the Internet of Things, machine learning, and robotics. These changes have also affected the reporting process as well as its processes. The processes of data acquisition, processing and sharing have changed. Furthermore, the data quantity has increased, whereas the speed of the time in which to prepare the reports has decreased. We can have data without information, but we cannot have information without data. There is never enough time, especially nowadays when we are used to having everything at our fingertips. These are two conflicting factors – having more data and less time to prepare quality reports. The systems are developed to optimize the process, increase efficiency and quality and, what is nowadays most important, they have been created to obtain mass data in the shortest possible time. Therefore, it is important to adapt and implement software that can help achieve our daily tasks. We must know how to process huge amounts of real-time data and deliver the information they contain. It is crucial for companies to keep up with the environment and implement changes and innovations into their business process. A company is like a living organism for it must constantly evolve and grow. As soon as it stops growing and evolving, it can fail because it starts lagging and is therefore no longer competitive to others. To deliver faster feedback, companies need data of better quality. There are tools that can improve the business process, better facilitating the capacity of the human agents. The goal is to harness the employees’ full potential and knowledge for important tasks, such as analyzing, reviewing, and understanding data and acting upon them, invoking information technology to automate repetitive processes and facilitate better communication. The focus in this master’s thesis is on the reporting process in Group X. Group X is one of the world leaders in the automotive industry, a multinational corporation based in Canada with subsidiaries around the world. The complexity of the business reporting that is implemented for the Headquarters in Canada has to address the complexity of the multinational corporation to support the decision process. The aim of the thesis is to propose a reporting process for preparing and producing reports with a huge amount of data in a very time-efficient manner. We start by examining the existing processes and upon that, identifying the processes required for the reports to reach the final recipients. Our goal is to identify the toolset, which would increase efficiency, accuracy, credibility, and reduce errors in the fastest possible time. We investigate a short-term and a long-term solution. By a short-term solution, we mean a system, program, or a tool that can help us increase our potential by using digital resources, which are already existing in the organization. By a long-term solution, we mean a solution, which requires employment of specialized future tools in the field of reporting and in repetitive processes, which we can identify with current knowledge and expectations for development. This includes machine learning, robotic process automatization, artificial intelligence.Poročanje je prisotno v vsakem podjetju. Bodisi je majhno ali veliko, temu se ni moč izogniti. Ima pomembno in ključno vlogo v procesu in napredku poslovanja. Kakovost poročanja vpliva na razvoj delovnega okolja in podjetja. Ker je poročilo dokument, ki vsebuje informacije o poslovanju, na podlagi katerega se sprejemajo odločitve za naprej, je zelo pomembno, da je strukturirano tako, da vsebuje ključne informacije za prejemnika in zagotavlja podporo poslovnim odločitvam. Postopek poročanja lahko poteka vodoravno navzgor ali navzdol. Vsebina in struktura se razlikujeta glede na prejemnika poročila. Živimo v dobi, ko vsak naš korak spremljajo digitalizacija, informatizacija, umetna inteligenca, masovni podatki, internet stvari, strojno učenje in robotika. Te spremembe so vplivale tudi na proces poročanja in tudi na njegove postopke. Spremenili so se procesi pridobivanja, obdelave in izmenjave podatkov. Poleg tega se je povečala količina podatkov, medtem ko se je hitrost časa, v katerem je treba pripraviti poročila, zmanjšala. Lahko imamo podatke brez informacij, ne moremo pa imeti informacij brez podatkov. Časa ni nikoli dovolj, zlasti danes, ko smo navajeni imeti vse na dosegu roke. To sta dva nasprotujoča si dejavnika - več podatkov in manj časa za pripravo kakovostnih poročil. Sistemi so razviti za optimizacijo procesa, povečanje učinkovitosti in kakovosti ter, kar je danes najpomembnejše, ustvarjeni so za pridobivanje množice podatkov v najkrajšem možnem času. Zato je pomembno, da prilagodimo in uvedemo programsko opremo, ki nam lahko pomaga pri opravljanju vsakodnevnih nalog. Vedeti moramo, kako obdelati ogromne količine podatkov v realnem času in posredovati informacije, ki jih vsebujejo. Za podjetja je ključnega pomena, da sledijo okolju ter v svoje poslovne procese uvajajo spremembe in inovacije. Podjetje je kot živ organizem, saj se mora nenehno razvijati in rasti. Takoj ko preneha rasti in se razvijati, lahko propade, saj začne zaostajati in zato ni več konkurenčno drugim. Za hitrejše zagotavljanje povratnih informacij podjetja potrebujejo podatke boljše kakovosti. Obstajajo orodja, ki lahko izboljšajo poslovni proces in tako bolje olajšajo zmogljivosti človeških dejavnikov. Cilj je izkoristiti celoten potencial in znanje zaposlenih za pomembne naloge, kot so analiziranje, pregledovanje in razumevanje podatkov ter ukrepanje na njihovi podlagi, pri čemer se je treba sklicevati na informacijsko tehnologijo za avtomatizacijo ponavljajočih se procesov in omogočanje boljše komunikacije. V tej magistrski nalogi se bomo osredotočili na proces poročanja v skupini X, ki je ena izmed vodilnih v avtomobilski industriji na svetu. Skupina X je mednarodna korporacija s sedežem v Kanadi in podružnicami po vsem svetu. Cilj diplomske naloge je predlagati postopek poročanja za pripravo in izdelavo poročil z veliko količino podatkov na časovno zelo učinkovit način. Začnemo s preučevanjem obstoječih procesov in na podlagi tega opredelimo procese, ki so potrebni, da poročila dosežejo končne prejemnike. Naš cilj je opredeliti nabor orodij, ki bi povečal učinkovitost, natančnost, verodostojnost in zmanjšal število napak v najkrajšem možnem času. Preučujemo kratkoročno in dolgoročno rešitev. S kratkoročno rešitvijo mislimo na sistem, program ali orodje, ki nam lahko pomaga povečati potencial z uporabo digitalnih virov, ki že obstajajo v organizaciji. Z dolgoročno rešitvijo mislimo na rešitev, ki zahteva uvedbo specializiranih orodij na področju poročanja in v ponavljajočih se procesih, ki jih lahko opredelimo s trenutnim znanjem in pričakovanji za razvoj. To neizogibno vključuje strojno učenje, robotsko avtomatizacijo procesov, umetno inteligenco in masovne podatkov