I’m mixing it up a little bit with this post. Yesterday I was able to successfully extract the text using pyPDF2 but the text was jumbled. It cleaned up okay using the .replace() function but the text was still out of order.
After looking at GhostScript, I figured I might give my go-to PAID pdf app a shot and it didn’t fail me. I used NitroPro to export text and it was largely unpurturbed from the original format.
There are still a few formatting issues which yesterday’s python can easily clean up. No need for imported modules.
You may ask why go through the trouble of extracting the text? I often summarize my learning points on this site so I can easily reference them and include tables to add to my reference page. If you copy from the web page, you end up with this text appended.
with open('C:\\Users\\g\\Downloads\\ajr.txt', 'r', encoding='utf-8') as file_obj: in_text = file_obj.read() with open('C:\\Users\\g\\Downloads\\ajr_clean.txt', 'w+', encoding='utf-8') as outfile: in_text.replace('\n',' ') in_text = (in_text.replace('- ','')) outfile.write(in_text)
- Multiple studies in the literature support a correlation between local recurrence of soft tissue sarcoma and high-risk factors such as intermediateor high-grade tumor, tumor larger than 5 cm, deep location, multifocally positive surgical margins, and absence of wide resection [1, 12–14]. Mortality from soft tissue sarcoma has been associated with local recurrence, tumor larger than 10 cm, deep location, high grade, and positive surgical margins
- While CT scan is often preferred due to its greater sensitivity in detecting small lung nodules, it is unknown whether this provides benefit over CXR alone. Both modalities are considered highly appropriate for this purpose by the American College of Radiology (ACR) .
- This is questionably accurate. CT is recommended by the ACR. While CXR is appropriate and would be considered reasonable, CT is preferred
- Although chest radiographs were historically used , unenhanced chest CT has become the recommended modality. Surveillance intervals vary from 3 to 6 months in the first several years to annually up to 10 years (Tables 1 and 2).
- A retrospective review performed in the United Kingdom found that CXR alone detected two-thirds of pulmonary metastases in patients with soft tissue sarcoma; when compared with CT as the “gold standard,” the sensitivity, specificity, positive predictive value, and negative predictive value of CXR were 60.8, 99.6, 93.3, and 96.7 percent, respectively . The use of CXR only to stage the lungs would have missed one-third of all patients with lung metastases, but because of the infrequency of lung metastases overall (96 of 1170 patients), the initial staging would have been inaccurate in only 3.1 percent of cases.
- Commentary: There is a CME question on this one and I believe the question is either vague or their answer is just wrong. First, it isn’t in the article. A review of primary literature sources showed a rate far lower than 1/3 and the summary above
- Radiation-induced sarcomas have different histologic composition than the patients’ original treated tumors; within the field of treatment, therefore, MRI characteristics widely differ . High-grade undifferentiated pleomorphic sarcoma is the most common postradiation sarcoma of the soft tissues, representing two-thirds of radiation-induced sarcoma. Extraskeletal osteosarcoma and fibrosarcoma follow, representing 13% and 11% of cases . Conversely, osteosarcoma is by far the most common radiation-induced malignancy affecting bone, accounting for approximately 60% of cases . Undifferentiated pleomorphic sarcoma is a distant second, accounting for approximately 20% of cases .