Notes

The consequence involving adipose-derived mesenchymal stem cell remedy in mTOR and p-mTOR phrase within ovarian harm because of cyclophosphomide.
This study aimed to investigate whether a disease site-specific, multi-institutional knowledge based-planning (KBP) model can improve the quality of intensity modulated radiation therapy treatment planning for patients enrolled in the head and neck NRG-HN001clinical trial and to establish a threshold of improvements of treatment plans submitted to the clinical trial.

Fifty treatment plans for patients enrolled in the NRG-HN001 clinical trial were used to build a KBP model; the model was then used to reoptimize 50 other plans. We compared the dosimetric parameters of the submitted and KBP reoptimized plans. We compared differences between KBP and submitted plans for single- and multi-institutional treatment plans.

Mean values for the dose received by 95% of the planning target volume (PTV_6996) and for the maximum dose (D0.03cc) of PTV_6996 were 0.5 Gy and 2.1 Gy higher in KBP plans than in the submitted plans, respectively. Mean values for D0.03cc to the brain stem, spinal cord, optic nerve_R, optic ner and the model is being used as an offline quality assurance tool.
To develop and evaluate a fast patient localization tool using megavoltage (MV)-topogram on helical tomotherapy.

Eighty-one MV-topogram pairs for 18 pelvis patients undergoing radiation were acquired weekly under an institutional review board-approved clinical trial. The MV-topogram imaging protocol requires 2 orthogonal acquisitions at static gantry angles of 0 degrees and 90 degrees for a programed scan length. A MATLAB based in-house software was developed to reconstruct the MV-topograms offline. Reference images (digitally reconstructed topograms, digitally reconstructed topograms) were generated using the planning computed tomography and tomotherapy geometry. The MV-topogram based alignment was determined by registering the MV-topograms to the digitally reconstructed topogram using bony landmark on commercial MIM software. The daily shifts in 3 translational directions determined from MV-topograms were compared with the megavoltage computed tomography (MVCT) based patient shifts. Linear-regression ansed patient alignment on tomotherapy.
MV-topograms showed equivalent clinical performance to the standard MVCT with significantly less acquisition time for pelvis and H&N patients. The MV-topogram can be used as an alternative or complimentary tool for bony landmark-based patient alignment on tomotherapy.
Manual delineation (MD) of organs at risk (OAR) is time and labor intensive. Auto-delineation (AD) can reduce the need for MD, but because current algorithms are imperfect, manual review and modification is still typically used. Recognizing that many OARs are sufficiently far from important dose levels that they do not pose a realistic risk, we hypothesize that some OARs can be excluded from MD and manual review with no clinical effect. The purpose of this study was to develop a method that automatically identifies these OARs and enables more efficient workflows that incorporate AD without degrading clinical quality.

Preliminary dose map estimates were generated for n = 10 patients with head and neck cancers using only prescription and target-volume information. Conservative estimates of clinical OAR objectives were computed using AD structures with spatial expansion buffers to account for potential delineation uncertainties. OARs with estimated dose metrics below clinical tolerances were deemed low priority and excluded from MD and/or manual review. Final plans were then optimized using high-priority MD OARs and low-priority AD OARs and compared with reference plans generated using all MD OARs. Multiple different spatial buffers were used to accommodate different potential delineation uncertainties.

Sixty-seven out of 201 total OARs were identified as low-priority using the proposed methodology, which permitted a 33% reduction in structures requiring manual delineation/review. Plans optimized using low-priority AD OARs without review or modification metall planning objectives that were met when all MD OARs were used, indicating clinical equivalence.

Prioritizing OARs using estimated dose distributions allowed a substantial reduction in required MD and review without affecting clinically relevant dosimetry.
Prioritizing OARs using estimated dose distributions allowed a substantial reduction in required MD and review without affecting clinically relevant dosimetry.The current reproducibility crisis is fundamentally a crisis of knowledge, thus in reality it is an epistemological crisis. The current reigning paradigm of null hypothesis testing using a P value of less then .05 has made the medical literature prone to be filled with spurious correlations rather than true knowledge. This article brings attention to 3 foundational issues to help navigate the current crisis The problem of induction, the concept of epistemological access, and the iatrogenics of information. Scientific reasoning is inductive reasoning and the problem of induction highlights the limitations of such knowledge. The concept of epistemological access is introduced to describe the inability of low-level data to extract true findings. This lack of true knowledge brings with it the iatrogenics of information, where having more data are in fact harmful and can lead to patients receiving ineffective treatments.
Stereotactic body radiation therapy (SBRT) has emerged as a potential therapeutic option for locally recurrent rectal cancer (LRRC) but contemporaneous clinical data are limited. We aimed to evaluate the local control, toxicity, and survival outcomes in a cohort of patients previously treated with neoadjuvant pelvic radiation therapy for nonmetastatic locally recurrent rectal cancer, now treated with SBRT.

Inoperable rectal cancer patients with ≤3 sites of pelvic recurrence and >6 months since prior pelvic radiation therapy were identified from a prospective registry over 4 years. SBRT dose was 30 Gy in 5 fractions, daily or alternate days, using cumulative organ at risk dose constraints. Primary outcome was local control (LC). Secondary outcomes were progression free survival, overall survival, toxicity, and patient reported quality of life scores using the EQ visual analog scale (EQ-VAS) tool.

Thirty patients (35 targets) were included. Median gross tumor volume size was 14.3 cm
. In addition, 27 lapses from rectal cancer, reirradiation with 30 Gy in 5 fractions is well tolerated and achieves an excellent balance between high local control rates with limited toxicity.
Reirradiation is rarely administered to patients with recurrent craniopharyngioma owing to concerns regarding visual and endocrine side effects. The purpose of this case series was to evaluate our institutional experience of patients with craniopharyngioma treated with 2 courses of fractionated radiation therapy.

A retrospective study was performed of all patients with craniopharyngioma treated with 2 courses of fractionated radiation therapy at a single institution. Electronic medical records and radiation therapy records were reviewed.

We identified 4 eligible patients with recurrent craniopharyngioma. With a median follow-up of 33 months after reirradiation, 3 patients attained disease control; 1 patient developed progressive disease, 27 months after reirradiation. In 3 evaluable patients, vision remained stable or improved after reirradiation; one patient had no light perception before reirradiation. None of the patients experienced additional endocrine toxicities after reirradiation, apart from one patient who had low serum thyroid stimulating hormone before reirradiation and later developed hypothyroidism after treatment.

Reirradiation may represent a safe and effective therapeutic option for selected patients with recurrent, refractory craniopharyngioma and without other salvage treatment options. Larger studies with longer-term follow up are warranted to better understand outcomes in these patients.
Reirradiation may represent a safe and effective therapeutic option for selected patients with recurrent, refractory craniopharyngioma and without other salvage treatment options. Larger studies with longer-term follow up are warranted to better understand outcomes in these patients.
We combined clinical practice changes, standardizations, and technology to automate aggregation, integration, and harmonization of comprehensive patient data from the multiple source systems used in clinical practice into a big data analytics resource system (BDARS). We then developed novel artificial intelligence algorithms, coupled with the BDARS, to identify structure dose volume histograms (DVH) metrics associated with dysphagia.

From the BDARS harmonized data of ≥22,000 patients, we identified 132 patients recently treated for head and neck cancer who also demonstrated dysphagia scores that worsened from base line to a maximum grade ≥2. We developed a method that used both physical and biologically corrected (α/β = 2.5) DVH curves to test both absolute and percentage volume based DVH metrics. Combining a statistical categorization algorithm with machine learning (SCA-ML) provided more extensive detailing of response threshold evidence than either approach alone. A sensitivity guided, minimum input, my provides practical demonstration of combining big data with artificial intelligence to increase volume of evidence in clinical learning paradigms.
This study provides practical demonstration of combining big data with artificial intelligence to increase volume of evidence in clinical learning paradigms.
This study aimed to investigate radiomic features extracted from magnetic resonance imaging (MRI) scans performed before and after neoadjuvant chemoradiotherapy (nCRT) in predicting response of locally advanced rectal cancer (LARC).

Thirty-nine patients who underwent nCRT for LARC were included, with 294 radiomic features extracted from MRI that was performed before (pre-CRT) and 6 to 8 weeks after completing nCRT (post-CRT). Based on tumor regression grade (TRG), 26 patients were classified as having a histopathologic good response (GR; TRG 0-1) and 13 as non-GR (TRG 2-3). Tumor downstaging (T-downstaging) occurred in 25 patients. Univariate analyses were performed to assess potential radiomic and delta-radiomic predictors for TRG in pathologic complete response (pCR) versus non-pCR, GR versus non-GR, and T-downstaging. The support vector machine-based multivariate model was used to select the best predictors for TRG and T-downstaging.

We identified 13 predictive features for pCR versus non-pCR, 14 forRT in LARC. These data, if validated in larger cohorts, can provide important predictive information to aid in clinical decision making.Although many researchers talk about a "patient database," they typically are not referring to a database at all, but instead to a spreadsheet of curated facts about a cohort of patients. This article describes relational database systems and how they differ from spreadsheets. At their core, spreadsheets are only capable of describing one-to-one (11) relationships. However, this article demonstrates that clinical medical data encapsulate numerous one-to-many relationships. Consequently, spreadsheets are very inefficient relative to relational database systems, which gracefully manage such data. Databases provide other advantages, in that the data fields are "typed" (that is, they contain specific kinds of data). This prevents users from entering spurious data during data import. Biricodar nmr Because each record contains a "key," it becomes impossible to add duplicate information (ie, add the same patient twice). Databases store data in very efficient ways, minimizing space and memory requirements on the host system. Likewise, databases can be queried or manipulated using a highly complex language called SQL.
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