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A new study published in The Bone and Joint Journal showed that for the diagnosis of infections in the lower limbs associated with refractory fractures, positron emission tomography (PET)/CT is a useful diagnostic technique.

A significant clinical problem is fracture-related infection (FRI), which frequently arises following fractures or surgical operations that specifically impact the lower limbs. FRI is still difficult to diagnose, especially in chronic patients that frequently exhibit a wide range of unusual clinical symptoms. Even if a consensus has been presented by the AO international expert group, there are still no reliable and consistent diagnostic techniques, particularly when contrasted with the recognized standards for periprosthetic joint infections (PJIs).

By determining ideal maximum standardized uptake value (SUVmax) thresholds and examining sub-group-specific diagnostic performance, this study seeks to assess the diagnostic accuracy of 18F-FDG PET/CT for refractory FRIs in the lower limbs.

A total of 429 PET/CT images from a tertiary orthopaedic center conducted between November 2016 and October 2021 were included in this retrospective analysis. Included were patients with probable refractory FRI, which is defined as an infection that has persisted after at least 2 previous therapies.

Microbiological cultures, histological examination, intraoperative results, and follow-up data were all included in the reference standard. Receiver operating characteristic curve analysis was used to compute diagnostic performance parameters, such as sensitivity, specificity, and area under the curve (AUC). The patients were classified in sub-group analyses according to the time since prior surgery and the clinical presentation.

AUC for PET/CT was 0.84, indicating strong diagnostic performance. With a sensitivity of 70.7% and specificity of 85.6%, the ideal SUVmax threshold was 4.75. According to subgroup studies, customized thresholds increased diagnosis accuracy; at a threshold of 5.05., the “No signs + Early phase” group had the best accuracy (87.5%) and specificity (89.4%).

By separating infection from leftover metabolic activity, a more stringent cut-off of 3.95 in the “No signs + Over phase” group, on the other hand, reduced overdiagnosis. Given the difficulties in identifying chronic infections, the “Over phase” group had the highest false-positive rate (42.4%) and the best specificity (90.1%) at a cut-off of 4.65. These results highlight how SUVmax thresholds vary depending on the clinical context.

Overall, 18F-FDG With stratified SUVmax criteria that improve diagnosis accuracy dependent on the period since prior surgery and symptom manifestation, PET/CT is a dependable diagnostic tool for refractory FRI. By enhancing infection control and lowering recurrence rates, PET/CT proves to be cost-effective over the long run, even with its high initial cost.

Source:

Cai, W., Lu, Y., Ren, Z., Zhang, Y., Cheng, P., Chen, X., Han, P., & Xu, Z. (2025). Real-world experience of the role of 18F-fluorodeoxyglucose positron emission tomography/CT refractory fracture-related infection on lower limbs : a retrospective diagnostic study: A retrospective diagnostic study. The Bone & Joint Journal, 107-B(8), 846–856. https://doi.org/10.1302/0301-620X.107B8.BJJ-2024-1158.R2

The FDA has approved Ajovy (fremanezumab-vfrm) for preventive treatment of episodic migraine in pediatric patients aged 6 to 17 years who weigh at least 45 kg.

With this approval, AJOVY becomes the first and only calcitonin gene-related peptide (CGRP) antagonist indicated for the preventive treatment of episodic migraine in pediatric patients and migraine in adults, marking a meaningful advancement in expanding preventive treatment options for those living with migraine.

Preventative treatment can help reduce the frequency of migraine attacks, helping children and adolescents to better manage the condition day-to-day. AJOVY is administered once a month and available for in-office or at home use, offering a treatment option that is intended to support adherence and reduce treatment burden for families.

“Migraines are a common yet invisible condition that can severely disrupt daily life for children and adolescents, often leaving them overlooked and misunderstood,” said Chris Fox, Executive Vice President, U.S. Commercial and Innovative Franchise Lead and Head of Global Marketing Business at Teva. “With this FDA approval, AJOVY now offers younger patients a new treatment option, addressing a long-standing gap in care and offering families added support as they navigate the challenges of this condition.”

1 in 10 children and adolescents in the U.S. suffer from migraine, one of the most common and disabling neurological conditions. Despite its widespread prevalence, pediatric migraine is often underrecognized and undertreated, contributing to missed school days, difficulties with schoolwork, and disrupted social activities.

“Pediatric migraine is a complex condition that can significantly impact a child’s daily life, from school performance to emotional well-being,” said Dr. Jennifer McVige, MD, MA, Pediatric Neurologist at the DENT Neurologic Institute. “Having an FDA-approved treatment like AJOVY offers an important option, providing a targeted approach to preventive treatment for episodic migraine that can help reduce the frequency of attacks in younger patients and help clinicians manage this often-overlooked condition.”

Building on its established success in adult patients since its U.S. approval in 2018, this expanded indication strengthens Teva’s commitment to broadening access to neuroscience therapies across age groups.2 AJOVY continues to demonstrate efficacy in addressing the underlying biology of migraine and now provides a treatment pathway for a patient population with historically limited preventive options.

About Migraine

Migraine attacks cause disabling pain, nausea, vomiting and sensitivities to light and sound, resulting in serious effects on the ability to complete daily tasks.5 Migraine can cause significant disability in children and adolescents, leading to absence from school, impaired educational performance and missed social activities.3

About AJOVY

AJOVY is indicated for preventive treatment of migraine in adults and episodic migraine in children and adolescent patients aged 6-17 years who weigh 45 kilograms (99 pounds) or more. AJOVY is available as a 225 mg/1.5 mL single dose injection in a pre-filled autoinjector or in a pre-filled syringe. AJOVY can be administered either by a healthcare professional or at home by a patient or caregiver. No starting dose is required to begin treatment.

The MRI image shows a brain tumor in an inauspicious location, – and a brain biopsy will entail high risks for the patient, who had consulted us due to double vision. Situations such as this case discussion, cited by way of example, in a multidisciplinary team of cancer medicine experts prompted researchers at Charité – Universitätsmedizin Berlin, together with cooperation partners, to look for new diagnostic procedures. The result is an AI model. The model makes use of specific characteristics in the genetic material of tumors – their epigenetic fingerprint, obtained for example from cerebrospinal fluid, among other things. As the team shows in the journal Nature Cancer*, the new model classifies tumors quickly and very reliably.

Today, far more types of tumors are known than the organs from which they arise. Each tumor has its own characteristics, certain tissue features, growth rates and metabolic peculiarities. Nevertheless, tumor types with similar molecular characteristics can be grouped together. The treatment of the individual disease depends decisively on the type of tumor. New, targeted therapies address certain structures of tumor cells or block their signaling pathways in order to halt the pathological tissue growth. Chemotherapies can be selected according to tumor type and their dosage adjusted accordingly. Particularly in the case of rare tumor types, it may be possible to pursue innovative therapies as part of studies.

“Against the backdrop of increasingly personalized, rapidly developing cancer medicine, precise diagnosis at a certified tumor center is the way forward for successful treatment,” as Prof. Martin E. Kreis, Chief Medical Officer at Charité, stated. While a comprehensive molecular, cellular and functional analysis of a tumor based on tissue samples provides the necessary information, physicians are also confronted with cases in which it is not possible or very risky to extract tissue samples from the tumor. What’s more, even a histological examination alone is not capable of providing as precise a diagnosis as the new AI model.

Looking into the genome instead of into the tissue

A method has been established for characterizing brain tumors that is not based on conventional microscopic diagnostics, but instead on modifications of the tumor‘s genetic material, the epigenetic characteristics. They are part of the memory of every cell and determine which parts of the genetic information are read and when. “Hundreds of thousands of epigenetic modifications act as on and off switches for individual gene sections. Their patterns form a unique, unmistakable fingerprint,” explains Dr. Philipp Euskirchen, scientist at the Berlin site of the German Cancer Consortium and at the Institute of Neuropathology at Charité, who heads the recently published study. “In tumor cells, the epigenetic information is altered in a characteristic way. Based on their profiles, we can differentiate between tumors and classify them.” In the case of brain tumors, even a sample of the cerebrospinal fluid is sufficient in some cases, and can be obtained relatively easily – dispensing with surgery altogether.

In order to compare an unknown fingerprint with thousands of known fingerprints of different cancers and assign it to a specific tumor type, machine learning methods, i.e., artificial intelligence, are required given that the data are very extensive and complex. What’s more, different DNA sequencing methods were applied in the past. In addition, epigenetic analyses are usually limited to defined patterns and gene segments that are typical for individual tumor types. “Consequently, our aim was to develop a model that accurately classifies tumors, even if they are only based on parts of the entire tumor epigenome or the profiles were collected by means of different techniques and varying degrees of accuracy,” as bioinformatician Dr. Sören Lukassen, head of the Medical Omics working group at the Berlin Institute of Health at Charité (BIH), stated.

Reliable and traceable

A newly developed AI model goes by the name of crossNN, whose architecture is based on a simple neural network. The model was trained with a large number of reference tumors and subsequently tested on more than 5,000 tumors. “Our model allows a very precise diagnosis of brain tumors in 99.1 percent of all cases and is more accurate than the AI solutions at work to date,” as Philipp Euskirchen related. “In addition, we were able to train an AI model in the same way that can differentiate between over 170 tumor types from all organs, while achieving accuracy of 97.8 percent. This means that it can be used for cancers of all organs, in addition to the relatively rare brain tumors.” The decisive factor for future approvals in clinical application is that the models are fully explainable, i.e., it must be possible to understand how the decisions are arrived at.

The molecular fingerprint that the AI model receives for determination can stem from a tissue sample or from body fluids. In the case of specific brain tumors, the Department of Neuropathology at Charité already offers non-invasive diagnostics based on cerebrospinal fluid, known as liquid biopsy. This allows a diagnosis to be made without a stressful operation, also in difficult situations. The patient who consulted us with double vision was one of the beneficiaries. “We examined the cerebrospinal fluid using nanopore sequencing, a novel, very fast and efficient form of genetic analysis. The classification by our models revealed that it was a lymphoma of the central nervous system, enabling us to promptly initiate appropriate chemotherapy,” Philipp Euskirchen explains.

crossNN in clinical trials

The accuracy of the methodology even took the researchers by surprise. “Although the architecture of our AI model is far more simple than previous approaches and therefore remains explainable, it delivers more precise predictions and therefore greater diagnostic certainty,” says Sören Lukassen. Together with the German Cancer Consortium (DKTK), the research team is therefore planning clinical trials with crossNN at all eight DKTK locations in Germany. In addition, intraoperative use is also to be tested. The aim is to transfer the precise and comparatively inexpensive tumor determination based on DNA samples to routine care.

Reference:

Yuan, D., Jugas, R., Pokorna, P. et al. crossNN is an explainable framework for cross-platform DNA methylation-based classification of tumors. Nat Cancer 6, 1283–1294 (2025). https://doi.org/10.1038/s43018-025-00976-5.

Researchers have discovered in a new study that patients in regions with higher sunlight exposure appear to have lower rates of postoperative hypoparathyroidism, suggesting sunlight may play a protective role in its prevention.

Odisha- The Odisha Joint Entrance Examination (OJEE) has revised the tentative schedule in line with the Medical Counselling Committee (MCC) Counselling extension for the state quota counselling and admission in the MBBS and BDS Courses for the academic year 2025-26.