Prostate Cases Research Articles

Incidence of Prostatic Carcinoma in Transurethral Resection Specimen

Objective: This study done to identify the rates of incidentally detected prostate cancer in patients undergoing surgical management of Benign Prostatic Hyperplasia (BPH). Methods: This cross section study was done on all transurethral resections of the prostate (TURP) cases. One hundred and eighty one men, aged 45 to 94 year, underwent TURP and their specimens were sent for the histopathological analysis. Those with a known diagnosis of prostate cancer prior to TURP were excluded (𝑛 = 5) from the analysis. Results: Hundred eighty-one patients had prostatic enlargement; fifteen patients (8.29%) patients were found to have prostate adenocarcinoma. Grade of disease ranged from Gleason score 7 to 10. Majority of them (fourteen patients) aged 65 year or above. Conclusion: Prostate carcinoma is showing high grade at the diagnosis and widely frequent (8.29%) in TURP, especially in-patient above 65 years (11.0%) and therefore a screening program advised.

Dosimetric evaluation of the capabilities of two clinical treatment planning systems for prostate cancer

Treatment planning systems play a key role in radiotherapy. Various commercial planning systems are currently available on the market. These systems usually differ in the algorithms used for radiation dose calculation and vary in the manner of implementation of the same algorithms. They also differ in optimizer algorithms used in search of the best treatment plan required to meet the user specified criteria. In this study, we evaluate two optimization systems available from two commercial treatment planning systems. The two systems used in the study are the Eclipse Planning System (version 10.042, Varian Medical Systems, Palo Alto); and, Monaco Planning System (version 3.01, Elekta CMS Software, St. Louis, MO). Computed tomographic images for ten patients, previously planned using Eclipse, were randomly selected from our patient database. We generated treatment plans for the ten cases utilizing the Monaco system. Monaco utilizes a set of biological and DVH functions in the optimization process, while Eclipse uses only dose volume objectives. Planners would need to understand the difference between the two methodologies for getting better outcomes in radiation treatment planning for cancer patients. All generated plans in the study were evaluated based on dose volume histogram (DVH) and isodose distributions. The overall performance of dose volume optimization was better compared to the biological optimization. Dose volume optimization was more efficient and easier to manipulate for our prostate cases. The biological optimization process provided good quality plans. However, the optimizer requires improvement to become more efficient.

Self-supervised learning for accelerated 3D high-resolution ultrasound imaging.

Ultrasound (US) imaging has been widely used in diagnosis, image-guided intervention, and therapy, where high-quality three-dimensional (3D) images are highly desired from sparsely acquired two-dimensional (2D) images. This study aims to develop a deep learning-based algorithm to reconstruct high-resolution (HR) 3D US images only reliant on the acquired sparsely distributed 2D images. We propose a self-supervised learning framework using cycle-consistent generative adversarial network (cycleGAN), where two independent cycleGAN models are trained with paired original US images and two sets of low-resolution (LR) US images, respectively. The two sets of LR US images are obtained through down-sampling the original US images along the two axes, respectively. In US imaging, in-plane spatial resolution is generally much higher than through-plane resolution. By learning the mapping from down-sampled in-plane LR images to original HR US images, cycleGAN can generate through-plane HR images from original sparely distributed 2D images. Finally, HR 3D US images are reconstructed by combining the generated 2D images from the two cycleGAN models. The proposed method was assessed on two different datasets. One is automatic breast ultrasound (ABUS) images from 70 breast cancer patients, the other is collected from 45 prostate cancer patients. By applying a spatial resolution enhancement factor of 3 to the breast cases, our proposed method achieved the mean absolute error (MAE) value of 0.90±0.15, the peak signal-to-noise ratio (PSNR) value of 37.88±0.88dB, and the visual information fidelity (VIF) value of 0.69±0.01, which significantly outperforms bicubic interpolation. Similar performances have been achieved using the enhancement factor of 5 in these breast cases and using the enhancement factors of 5 and 10 in the prostate cases. We have proposed and investigated a new deep learning-based algorithm for reconstructing HR 3D US images from sparely acquired 2D images. Significant improvement on through-plane resolution has been achieved by only using the acquired 2D images without any external atlas images. Its self-supervision capability could accelerate HR US imaging.

Novel methodology to assess the effect of contouring variation on treatment outcome.

Contouring variation is one of the largest systematic uncertainties in radiotherapy, yet its effect on clinical outcome has never been analyzed quantitatively. We propose a novel, robust methodology to locally quantify target contour variation in a large patient cohort and find where this variation correlates with treatment outcome. We demonstrate its use on biochemical recurrence for prostate cancer patients. We propose to compare each patient's target contours to a consistent and unbiased reference. This reference was created by auto-contouring each patient's target using an externally trained deep learning algorithm. Local contour deviation measured from the reference to the manual contour was projected to a common frame of reference, creating contour deviation maps for each patient. By stacking the contour deviation maps, time to event was modeled pixel-wise using a multivariate Cox proportional hazards model (CPHM). Hazard ratio (HR) maps for each covariate were created, and regions of significance found using cluster-based permutation testing on the z-statistics. This methodology was applied to clinical target volume (CTV) contours, containing only the prostate gland, from 232 intermediate- and high-risk prostate cancer patients. The reference contours were created using ADMIRE® v3.4 (Elekta AB, Sweden). Local contour deviations were computed in a spherical coordinate frame, where differences between reference and clinical contours were projected in a 2D map corresponding to sampling across the coronal and transverse angles every 3°. Time to biochemical recurrence was modeled using the pixel-wise CPHM analysis accounting for contour deviation, patient age, Gleason score, and treated CTV volume. We successfully applied the proposed methodology to a large patient cohort containing data from 232 patients. In this patient cohort, our analysis highlighted regions where the contour variation was related to biochemical recurrence, producing expected and unexpected results: (a) the interface between prostate-bladder and prostate-seminal vesicle interfaces where increase in the manual contour relative to the reference was related to a reduction of risk of biochemical recurrence by 4-8% per mm and (b) the prostate's right, anterior and posterior regions where an increase in the manual contour relative to the reference contours was related to an increase in risk of biochemical recurrence by 8-24% per mm. We proposed and successfully applied a novel methodology to explore the correlation between contour variation and treatment outcome. We analyzed the effect of contour deviation of the prostate CTV on biochemical recurrence for a cohort of more than 200 prostate cancer patients while taking basic clinical variables into account. Applying this methodology to a larger dataset including additional clinically important covariates and externally validating it can more robustly identify regions where contour variation directly relates to treatment outcome. For example, in the prostate case we use to demonstrate our novel methodology, external validation will help confirm or reject the counter-intuitive results (larger contours resulting in higher risk). Ultimately, the results of this methodology could inform contouring protocols based on actual patient outcomes.

Solving the volumetric modulated arc therapy (VMAT) problem using a sequential convex programming method

The volumetric modulated arc therapy (VMAT) problem is highly non-convex and much more difficult than the fixed-field intensity modulated radiotherapy optimization problem. To solve it efficiently, we propose a sequential convex programming algorithm that solves a sequence of convex optimization problems. Beginning by optimizing the aperture weights of many (72) evenly distributed beams using the beam’s eye view of the target from each direction as the initial aperture shape, the search space is constrained to allowing the leaves to move within a pre-defined step-size. A convex approximation problem is introduced and solved to optimize the leaf positions and the aperture weights within the search space. The algorithm is equipped with both local and global search strategies, whereby a global search is followed by a local search: a large step-size results in a global search with a less accurate convex approximation, followed by a small step-size local search with an accurate convex approximation. The performance of the proposed algorithm is tested on three patients with three different disease sites (paraspinal, prostate and oligometastasis). The algorithm generates VMAT plans comparable to the ideal 72-beam fluence map optimized plans (i.e. IMRT plans before leaf sequencing) in 14 iterations and 36 mins on average. The algorithm is also tested on a small down-sampled prostate case for which we could computationally afford to obtain the ground-truth by solving the non-convex mixed-integer optimization problem exactly. This general algorithm is able to produce results essentially equivalent to the ground-truth but 12 times faster. The algorithm is also scalable and can handle real clinical cases, whereas the ground-truth solution using mixed-integer optimization can only be obtained for highly down-sampled cases.

Metastatic Thyroid Cartilage Lesion from Prostatic Adenocarcinoma on 68Ga-Prostate-Specific Membrane Antigen Positron Emission Tomography-Computed Tomography Scan

Prostate cancer usually metastasizes to regional lymph nodes and bone. Laryngeal cartilage metastases are very rare and only few cases have been published so far describing thyroid cartilage metastatic lesions from prostate cancer. Here, we describe 5 cases of carcinoma prostate, 3 staging and 2 follow-up, where 68Ga-prostate-specific membrane antigen positron emission tomography/computed tomography (PET/CT) scan revealed multiple skeletal lesions along with thyroid cartilage metastasis. Initially, laryngeal cartilage metastases remain asymptomatic and in later stages patients present with symptoms. These metastatic lesions to thyroid cartilage are rare entities and can often easily be missed on conventional imaging. PET-CT imaging has overcome this diagnostic problem due to its ability to provide for both anatomical and functional imaging.

Assessment of isochromosome 12p and 12p abnormalities in germ cell tumors using fluorescence in situ hybridization, single-nucleotide polymorphism arrays, and next-generation sequencing/mate-pair sequencing

The identification of isochromosome 12p [i(12p)] and 12p gains have significant clinical utility in the diagnosis of germ cell tumors (GCTs). We have summarized the results of fluorescence in situ hybridization (FISH) assays to identify i(12p), performed in a Clinical Laboratory Improvement Amendments (CLIA)-validated setting for 536 specimens. In addition, the American Association for Cancer Research (AACR) Project GENIE registry and The Cancer Genome Atlas (TCGA) data sets were evaluated for chromosome 12p gains, and a limited number of cases were concurrently evaluated using FISH, single-nucleotide polymorphism (SNP) arrays and next-generation sequencing (NGS; including mate-pair sequencing). Specimens submitted for FISH testing were frequently from potential sites of metastases (male: 70.9% and female: 69.3%), and polysomy of chromosome 12 with or without concurrent i(12p) was a frequent finding, seen in 3% (16/536) and 35% (186/536) of cases, respectively. Our analysis suggests that 12p gains are likely to be present in approximately 73% of male GCTand in 32% of female GCT (AACR GENIE, n=555). When comparing TCGA cases of testicular GCT (n=149) to combined cases of sarcoma, colorectal, prostate, and urothelial carcinoma (n=1754), 12p gains had a sensitivity of 77.2% and specificity of 97.3% for GCT. Some advantages of FISH over SNP arrays/NGS include relatively lower cost, rapid turnaround time, the ability to analyze biopsy material with a limited number of tumor cells (50cells), and the ability to distinguish i(12p) from polysomy. The ability to spatially restrict the analysis to cells of interest is critical, as specimens submitted for testing often have low tumor purity. Disadvantages include false negative results due to an inability to detect segmental gains due to FISH probe design. With the availability of numerous testing modalities, including FISH, SNP arrays, and NGS-based assays, a nuanced understanding of the advantages and disadvantages of each methodology, as has been presented in this study, may inform appropriate testing strategies.

Characterization of penumbra sharpening and scattering by adaptive aperture for a compact pencil beam scanning proton therapy system.

To quantitatively access penumbra sharpening and scattering by adaptive aperture (AA) under various beam conditions and clinical cases for a Mevion S250i compact pencil beam scanning proton therapy system. First, in-air measurements were performed using a scintillation detector for single spot profile and lateral penumbra for five square field sizes (3×3 to 18×18cm2 ), three energies (33.04, 147.36, and 227.16MeV), and three snout positions (5, 15, and 33.6cm) with Open and AA field. Second, treatment plans were generated in RayStation treatment planning system (TPS) for various combination of target size (3- and 10-cm cube), target depth (5, 10, and 15cm) and air gap (5-20cm) for both Open and AA field. These plans were delivered to EDR2 films in the solid water and penumbra reduction by AA was quantified. Third, the effect of the AA scattered protons on the surface dose was studied at 5mm depth by EDR2 film and the RayStation TPS computation. Finally, dosimetric advantage of AA over Open field was studied for five brain and five prostate cases using the TPS simulation. The spot size changed dramatically from 3.8mm at proton beam energy of 227.15MeV to 29.4mm at energy 33.04MeV. In-air measurements showed that AA substantially reduced the lateral penumbra by 30% to 60%. The EDR2 film measurements in solid water presented the maximum penumbra reduction of 10 to 14mm depending on the target size. The maximum increase of 25% in field edge dose at 5mm depth as compared to central axis was observed. The substantial penumbra reduction by AA produced less dose to critical structures for all the prostate and brain cases. Adaptive aperture sharpens the penumbra by factor of two to three depending upon the beam condition. The absolute penumbra reduction with AA was more noticeable for shallower target, smaller target, and larger air gap. The AA-scattered protons contributed to increase in surface dose. Clinically, AA reduced the doses to critical structures.

Robust radiation therapy optimization using simulated treatment courses for handling deformable organ motion

We describe a radiation therapy treatment plan optimization method that explicitly considers the effects of interfraction organ motion through optimization on the clinical target volume (CTV), and investigate how it compares to conventional planning using a planning target volume (PTV). The method uses simulated treatment courses generated using patient images created by a deformable registration algorithm to replicate the effects of interfraction organ motion, and performs robust optimization aiming to achieve CTV coverage under all simulated treatment courses. The method was applied to photon-mediated treatments of three prostate cases and compared to conventional, PTV-based planning with margins selected to achieve similar CTV coverage as the robustly optimized plans. Clinical goals for the CTV and healthy tissue were used in comparison between the two types of plans. Out of the two clinical goals for overdosage of the CTV, the three robustly optimized plans violated respectively 2, 2, and 0 goals in the mean over the scenarios, whereas none of the PTV plans violated these goals. Of the ten clinical goals for rectum, bladder, anal canal, and bulbus, the robustly optimized plans violated respectively 0, 1, and 1 goals in the mean, whereas the PTV plans violated 5, 7, and 4 goals. Compared to PTV-based planning, the inclusion of treatment course scenarios in the optimization has the potential to reduce the dose to healthy tissues while retaining a high probability of target coverage. This may reduce the need for adaptive replanning.

Frequency and Trends of Prostatic Diseases in a Subset of Karachi Population: A Retrospective Study

Background: Prostatic diseases are a leading cause of frequent urinary complaints in elderly males. The most common diseases include prostatitis, benign prostatic hyperplasia, and prostate cancer. This study aimed to determine the frequency of the prostatic diseases, their trend over the years, and the association of age and diagnosis. Methods: A retrospective descriptive study was conducted in Basic Medical Sciences Institute (BMSI) at Jinnah Postgraduate Medical Centre, Karachi. Data was collected from the histopathological files and all the cases diagnosed from 2014 to 2018 were included. Statistical analysis was done using SPSS with 95% confidence interval and p-value of ≤ 0.05 was considered significant. The Chi-square test was applied to find the association with age and year of diagnosis. Results: Total 163 prostate cases were documented from 2014 to 2018, out of which 98 (60.1%) were of benign prostatic hyperplasia, which was most commonly diagnosed in men aged, 61-70. Prostatic adenocarcinomas having Gleason scores 8-10 were frequent and commonly seen in men aged 51-60 years. An increasing trend (p-value=0.053) was observed in the diagnosis of these prostatic diseases within these five years. Conclusion: Benign prostatic hyperplasia is the most frequently (p-value=0.140) diagnosed prostatic disease in men, followed by adenocarcinoma and prostatitis. Advanced stage prostatic adenocarcinoma was diagnosed more frequently 17(10.4%) and at an earlier age. There is an increase in the number (p-value=0.053) of cases of prostatic diseases diagnosed each year. National-level studies and health policies are needed to facilitate early diagnosis and treatment.

English

BACKGROUND Differentiating prostate carcinoma (PCa) arising in the neck of urinary bladder from high grade urothelial cancer (UCa) with prostatic extension can be a difficult task for histopathologist due to similar morphologic characteristics and overlapping clinical manifestations in the two diseases. These two tumours often occur in association with one another but have different potential therapeutic strategies and prognostic implications. We have investigated p63 immunohistochemical (IHC) marker as simple first line marker adjuvant to histopathological examination. METHODS In this prospective study, total 50 cases including 25 cases of urothelial carcinoma and 25 cases of prostatic carcinoma were taken. Tumour grade was determined according to standard H&E staining and scoring system. p63 expressions were determined by immunohistochemical staining of all the cases. The obtained results were analysed and evaluated using chi-square statistical test to determine whether p63 IHC can be used as simple first line marker tool with a high sensitivity and specificity. RESULTS p63 was not expressed in any of the 25 cases of prostatic carcinoma cases while in urothelial carcinoma it was expressed in 23 of 25 (92 %) cases. p63 IHC staining expression is positive in all histological grades of urothelial carcinomas. 2 out of 25 cases of urothelial carcinomas were negative for p63 IHC expression. None of the prostatic adenocarcinomas expressed p63 staining. Sensitivity of p63 stain in differentiating UCa with PCa was 92 % in our study, specificity of p63 stain in differentiating UCa with PCa was found to be 100 %. CONCLUSIONS p63 can be used as a screening first line IHC marker to distinguish urothelial carcinomas from prostatic adenocarcinomas. For challenging and unresolved cases both of these have limited sensitivity; thus, authors recommend two lineagespecific markers one each for UCa (GATA3, S100P) and PCa (NKX3.1, P501S, PSMA) should be used for definitive diagnosis. KEYWORDS p63 Immunohistochemistry, Urothelial Carcinoma, Prostatic Adenocarcinoma

Pareto Optimal Projection Search (POPS): Automated Radiation Therapy Treatment Planning by Direct Search of the Pareto Surface.

Radiation therapy treatment planning is a time-consuming, iterative process with potentially high inter-planner variability. Fully automated treatment planning processes could reduce a planner's active treatment planning time and remove inter-planner variability, with the potential to tremendously improve patient turnover and quality of care. In developing fully automated algorithms for treatment planning, we have two main objectives: to produce plans that are 1) Pareto optimal and 2) clinically acceptable. Here, we propose the Pareto optimal projection search (POPS) algorithm, which provides a general framework for directly searching the Pareto front. Our POPS algorithm is a novel automated planning method that combines two main search processes: 1) gradient-free search in the decision variable space and 2) projection of decision variables to the Pareto front using the bisection method. We demonstrate the performance of POPS by comparing with clinical treatment plans. As one possible quantitative measure of treatment plan quality, we construct a clinical acceptability scoring function (SF) modified from the previously developed general evaluation metric (GEM). On a dataset of 21 prostate cases collected as part of clinical workflow, our proposed POPS algorithm produces Pareto optimal plans that are clinically acceptable in regards to dose conformity, dose homogeneity, and sparing of organs-at-risk. Our proposed POPS algorithm provides a general framework for fully automated treatment planning that achieves clinically acceptable dosimetric quality without requiring active planning from human planners. Our fully automated POPS algorithm addresses many key limitations of other automated planning approaches, and we anticipate that it will substantially improve treatment planning workflow.

BRCA mutation rate and characteristics of prostate tumor in breast and ovarian cancer families: analysis of 6,591 Italian pedigrees.

Objective:As prostate cancer (PrC) shows a BRCA mutation rate as high as 30%, it becomes crucial to find the optimal selection criteria for genetic testing. The primary objective of this study was to evaluate the BRCA mutation rate in families with PrC associated with breast and/or ovarian cancers; secondary aims were to compare the characteristics of families and BRCA-related PrC outcome among BRCA1 and BRCA2 carriers.Methods:Following the Modena criteria for the BRCA test, we evaluated the mutation rate in families with breast and/or ovarian cancer with a Gleason score ≥7 PrCs, by testing breast or ovarian cases and inferring the mutation in the prostate cases. The characteristics of families and BRCA-related PrC outcomes were measured using the chi-square (χ2) test and Kaplan–Meier methods, respectively.Results:Among 6,591 families, 580 (8.8%) with a Gleason score ≥ 7 PrCs were identified, of which 332 (57.2%) met the Modena selection criteria for BRCA testing. Overall, 215 breast or ovarian cancer probands (64.8%) were tested, of which 41 resulted positive for BRCA and one for CHEK2 genes (19.5%). No statistically significant differences were found in BRCA-related PrC prognosis and in the characteristics of families among BRCA1, BRCA2 and non-tested patients. Ten of 23 (44%) mutations in the BRCA2 gene fell in the prostate cancer cluster region (PCCR) at the 3′ terminal of the 7914 codon.Conclusions:It appears the Modena criteria are very useful for BRCA testing selection in families with breast and/or ovarian cancer and PrC. A trend toward a worse prognosis has been found in BRCA2 carriers.

A Rare Prostate Pathology: Mantle Cell Lymphoma: A Case Report and Literature Review

Primary or secondary lymphoma of the prostate is a rare condition. Mantle cell lymphoma (MCL) represent 4-9% of all lymphomas. Prostate involvement with MCL is very rare, with only 11 reported cases up to now. Here we present a case with lower urinary tract symptoms and prostate-specific antigen (PSA) elevation diagnosed with MCL of the prostate. Prostate biopsy was performed in a 70-year-old patient due to increased PSA. After the pathology result was reported as prostatic MCL, imaging studies and sampling of additional pathological specimens were performed for staging. An improvement was observed in the urinary system complaints of the patient who started chemotherapy regimen. While prostatectomy was performed in some of the prostatic MCL cases reported previously, in some, no additional treatment was required after chemotherapy. Our case is the only prostatic MCL case with elevated PSA levels, but did not receive the diagnosis of prostate cancer. Physicians should keep in mind that, prostatic MCL can present with nonspecific symptoms. Staging should be performed in patients whose histopathologic diagnosis is lymphoma of the prostate so as to determine appropriate treatment options.

Catching the Wave: Quantifying the Impact of COVID on Radiotherapy Delivery.

The novel coronavirus of 2019 has had a broad impact of the delivery of healthcare, including cancer care. We chose to quantify the impact in the radiation oncology department of the largest academic center in the hardest hit city in Canada. With the approval of our ethics review board, data on each patient treated from March 13, 2020 to August 10, 2020 were compared to patients treated during the same period in 2019. We compared the case mix, delay from treatment decision to treatment start, and number of fractions per patient. We reviewed prospectively collected information regarding deviations from our usual practice. During the pandemic the caseload was reduced by 12%; this was more pronounced in prostate and CNS tumors. The average number of fractions per patient was reduced from 12.3 to 10.9. This reduction was most marked in prostate, breast, gastro-intestinal, and palliative cases. When physicians were questioned, they reported that 17% of treatment plans deviated from their usual practice because of the pandemic. The most common deviations were related to changes in department policies (77%) vs. patient-specific deviations (20%) or changes requested by the patient (3%). Rare deviations were due to patients contracting COVID-19 (2 patients). At its worse, the wait list contained 27% of patients who had a delay to radiotherapy of more than 28 days. However, the average wait time increased little (19.6 days vs. 18.2 days) as more pressing cases were prioritized. In an unprecedented health crisis, our radiation oncology department was able to reduce resource utilization, notably by decreasing the number of fractions per patient. It will be important to follow these patients’ health outcomes for insight into these practices. More quantitative tools to simulate and plan future practice changes in response to resource constraints will be implemented.

Variance-based sensitivity analysis for uncertainties in proton therapy: A framework to assess the effect of simultaneous uncertainties in range, positioning, and RBE model predictions on RBE-weighted dose distributions.

Treatment plans in proton therapy are more sensitive to uncertainties than in conventional photon therapy. In addition to setup uncertainties, proton therapy is affected by uncertainties in proton range and relative biological effectiveness (RBE). While to date a constant RBE of 1.1 is commonly assumed, the actual RBE is known to increase toward the distal end of the spread-out Bragg peak. Several models for variable RBE predictions exist. We present a framework to evaluate the combined impact and interactions of setup, range, and RBE uncertainties in a comprehensive, variance-based sensitivity analysis (SA). The variance-based SA requires a large number (104 -105 ) of RBE-weighted dose (RWD) calculations. Based on a particle therapy extension of the research treatment planning system CERR we implemented a fast, graphics processing unit (GPU) accelerated pencil beam modeling of patient and range shifts. For RBE predictions, two biological models were included: The mechanistic repair-misrepair-fixation (RMF) model and the phenomenological Wedenberg model. All input parameters (patient position, proton range, RBE model parameters) are sampled simultaneously within their assumed probability distributions. Statistical formalisms rank the input parameters according to their influence on the overall uncertainty of RBE-weighted dose-volume histogram (RW-DVH) quantiles and the RWD in every voxel, resulting in relative, normalized sensitivity indices (S=0: noninfluential input, S=1: only influential input). Results are visualized as RW-DVHs with error bars and sensitivity maps. The approach is demonstrated for two representative brain tumor cases and a prostate case. The full SA including RWD calculations took 39, 11, and 55min, respectively. Range uncertainty was an important contribution to overall uncertainty at the distal end of the target, while the relatively smaller uncertainty inside the target was governed by biological uncertainties. Consequently, the uncertainty of the RW-DVH quantile D98 for the target was governed by range uncertainty while the uncertainty of the mean target dose was dominated by the biological parameters. The SA framework is a powerful and flexible tool to evaluate uncertainty in RWD distributions and DVH quantiles, taking into account physical and RBE uncertainties and their interactions. The additional information might help to prioritize research efforts to reduce physical and RBE uncertainties and could also have implications for future approaches to biologically robust planning and optimization.

Development of generalized time-dependent TCP model and the investigation of the effect of repopulation and weekend breaks in fractionated external beam therapy

We developed a tumor control probability (TCP) model that incorporates variable time intervals between fractions and a kick-off time (Tk) for radiation-induced accelerated tumor proliferation. The resulting Lee-Rosen model, TCPLR, was used to compute TCPs for treatment courses with and without weekend treatment for tumors with different proliferation rates – slow (prostate), moderate (breast), and rapid (head and neck). TCPs were computed using ideal uniform dose distributions and actual patient plans. The doses for the uniform plans were the mean doses for the prostate and breast cases and the minimum tumor dose for the head and neck case. The TCPLR model predictions agreed with expectations that TCP increases with increasing Tk in all cases. For standard fractionation, as Tk increased from 0 to 4 weeks, TCP increased for the patient distributions by 74.7% for the head and neck cancer, by 6.2% for the breast cancer, and by 2.4% for the prostate cancers. For the uniform dose distributions, the increases were 79.2%, 5.7%, and 2.3%, respectively. TCP increased as the number of weekend breaks decreased. The effect of weekend breaks decreased as the tumor proliferation rate decreased. For the head and neck tumor, notable decreases in TCP of 6.0% (uniform dose distribution) and 6.8% (actual plan dose distribution) were observed with Friday starts compared to Monday starts for the standard 5 fx/wk schedule (Tk = 4 wk). The 7 fx/wk schedule produced increases in TCP of 17.0% and 20.5% for the uniform and patient dose distributions, respectively, compared to the standard schedule. For the breast cancer, starting the 5 fx/wk schedule on Friday decreased the TCP by 0.2% (Tk = 4 wk) compared to a Monday start. The 7 fx/wk schedule produced increases of 0.3% and 0.4% in TCP compared to the standard schedule for the uniform and patient dose distributions, respectively (Tk = 4 wk). For the prostate cancer, the change in TCP for 5 fx/wk schedules starting on different days was 0.1%. The 7 fx/wk schedule increased TCP by 0.8% compared to the standard schedule (Tk = 4 wk). TCP values for the uniform dose distributions for the standard schedule (Tk = 4 wk) agreed with the TCP values for the actual dose distributions within 4.5% for the head and neck tumor and within 0.2% for the breast and prostate tumors. This good agreement suggests that the doses chosen for the uniform dose distributions were good approximations to the clinical doses. The results for head and neck tumors support, in part, the current practice of hyperfractionated/accelerated radiotherapy. They also suggest that shortening the overall treatment time for conventional fractions by eliminating weekend breaks might be beneficial. The predicted effect on TCP of the various schedules studied was insignificant for prostate and breast tumors, suggesting that a weekend treatment might not be necessary for patients starting radiotherapy on a Friday. There is significant uncertainty in the values of the model parameters chosen for these calculations, and no consideration was given to the potential effects of these various schedules on normal tissues.

Prostate cancer and human papillomavirus infection: a recent literature review

Aim: Prostate cancer is one of the most frequent cancers in men and it is reported that about one in nine men experience the disease in their lifetime. It has been found that in some cases, HPV can be a culprit for prostate cancer. The present meta-analysis study aims to examine whether human papillomavirus (HPV) serves as a foundation of human prostate cancer. Methods: Related studies to HPV and prostate cancer from 1990 to 2020 were sought in PubMed and Google Scholar. Earlier published expert reviews and systematic meta-analysis were utilized as a supplementary source to recognize appropriate articles. Finally, data from 54 articles, with 7072 prostate cancer cases, were pooled and analyzed. Results: The pooled rating for the odds ratio was 17.42%. Stratified pooled analyses were subsequently performed according to the HPV detection of geographical regions, publication years, the number of prostate cases, and HPV-positive cases. Conclusion: The meta-analysis confirmed the variant frequencies of HPV positivity in prostate cancer of different geographic zones. It has been found that there can be a potential link between HPV and prostate cancer. Yet, further investigations of this cancer relating to HPV may be necessary.

Comparison of Treatment Plan Robustness Between Dynamic Trajectory Radiotherapy and VMAT

Dynamic trajectory radiotherapy (DTRT) was recently developed in our institute for a non-coplanar arc delivery technique utilizing additionally to VMAT table and collimator rotations. Recent studies on the dosimetric performance suggest a substantial improvement in organs at risks (OARs) sparing when compared with conventional C-arm VMAT delivery. In this work, the treatment plan robustness for DTRT and VMAT is compared with respect to setup errors. Robustness was assessed by generating DVH bands as well as so-called robustness maps (rMaps) by means of a false/true evaluation of certain dosimetric user-defined limits considered acceptable for selected structures with respect to a range of setup errors considered. The robustness was assessed for a clinically motivated head and neck, a lung and a prostate case. For each case systematic translational (ranging from -6 to 6 mm) and rotational (ranging from -3° to 3°) setup error scenarios were defined and for each scenario Monte Carlo dose calculations for the DTRT and VMAT treatment plans were performed. The resulting dose distributions served as input for the robustness assessment determining DVH bands and rMaps. The acceptance conditions for the OARs were defined such that the mean doses for parallel OARs and near maximum doses for serial OARs do not deteriorate more than 2 Gy. For the CTV V95% a deterioration of 1% was allowed in order to pass the robustness criteria. For the isotropic CTV to PTV margins 4 mm, 5 mm and 10 mm were applied for the head and neck, the prostate and the lung case, respectively, except for the dorsal direction of the prostate case, where 3 mm was used. For the head and neck and the prostate case the percentage of setup error scenarios passing the acceptance criteria were 29% and 63% (VMAT) and 23% and 58% (DTRT) for translations and 60% and 100% (VMAT) and 62% and 100% (DTRT) for rotations, respectively. Depending on the direction of the translation setup error, the VMAT plan is slightly more robust. However, for the lung case the VMAT treatment plan is more robust leading to passing rates of 48% (VMAT) and 20% (DTRT) for translations and 83% (VMAT) and 55% (DTRT) for rotations, respectively. In all cases, the robustness determined by the rMaps is dominated by the acceptance criteria for the OARs and not by the ones for the CTV. The results of this study indicate that DTRT treatment plans using additional dynamic table and collimator rotations leading to complex trajectories result in similar systematic setup error robustness as VMAT treatment plans for the head and neck and the prostate case. For the lung case investigated, the VMAT treatment plans show an improved robustness.

Plan-Delivery-Time-Constrained Inverse Optimization for High-Throughput PBS Proton RT

Proton RT remains a limited resource that can only accommodate small number of cancer patients. Given that most modern proton centers use the multi-room shared-beam layout to parallelize patient setup, the major throughput-limiting factor is plan delivery time (primarily dose delivery time and energy switching time). This project will develop novel plan-delivery-time-constrained inverse optimization algorithms to achieve the significant reduction of plan delivery time for high-throughput pencil beam scanning (PBS) proton RT. The PBS dose rate is linearly proportional to the minimum-monitor-unit (MU) constraint. Thus, the increase of MU threshold can increase dose rate and therefore reduce dose delivery time. However, the room to increase this threshold is very limited with a single fixed MU threshold for all PBS spots as is assumed by current methods, since the plan quality is often significantly deteriorated before reaching any meaningful reduction of dose delivery time. To allow a significant reduction of dose delivery time while ensuring the plan quality, we propose to use variable energy-dependent MU thresholds to relax the tradeoff between dose delivery time and plan quality. On the other hand, although energy switching time is the secondary factor for total plan delivery time, it becomes relatively more important as dose delivery time is significantly reduced. Thus, energy switching time is modeled via group sparsity. New optimization algorithms via iterative convex relaxation are developed to solve these non-convex optimization problems. In addition, our methods can provide the efficiency-quality Pareto surface via multi-criteria optimization regarding the tradeoff between delivery efficiency and plan quality. With variable energy-dependent MU thresholds, our new method achieved 46.7%, 32.6%, and 33.3% reduction of dose delivery time respectively for prostate, lung and brain cases. Compared with plans optimized with a single MU threshold that corresponded to a 26.7% reduction of dose delivery time, our new method significantly improved plan quality in terms of both CTV coverage and OAR sparing. Moreover, the dose delivery time was further reduced to 25.7%, 34.9%, and 41.3% respectively, accepting a slightly degraded plan quality that still met all clinical planning constraints. On the other hand, our group-sparsity-regularized method reduced number of energy layers (or equivalently energy switching time) to 78%, 76%, and 61% respectively for prostate, lung and HN cases, while comparable plan quality was preserved. Moreover, the energy switching time was further reduced to 54%, 57%, and 37% respectively, accepting a slightly degraded plan quality that still met all clinical planning constraints. Novel plan-delivery-time-constrained optimization methods have been developed for high-throughput PBS proton RT.